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Smartphone

Two smartphones: a Samsung Galaxy J5 (left) and an iPhone 6S (right)

Smartphones are a class of multi-purpose mobile computing device. They are distinguished from feature phones by their stronger hardware capabilities and extensive mobile operating systems, which facilitate wider software, internet (including web browsing over mobile broadband), and multimedia functionality (including music, video, cameras, and gaming), alongside core phone functions such as voice calls and text messaging. Smartphones typically include various sensors that can be leveraged by their software, such as a magnetometer, proximity sensors, barometer, gyroscope and accelerometer, and support wireless communications protocols such as Bluetooth, Wi-Fi, and satellite navigation.

Early smartphones were marketed primarily towards the enterprise market, attempting to bridge the functionality of standalone personal digital assistant (PDA) devices with support for cellular telephony, but were limited by their battery life, bulky form factors, and the immaturity of wireless data services. In the 2000's, BlackBerry, Nokia's Symbian platform, and Windows Phone began to gain market traction, with models often featuring QWERTY keyboards or resistive touchscreen input, and emphasizing access to push email and wireless internet. Since the 2007 unveiling of the iPhone, the majority of smartphones have featured thin, slate-like form factors, with large, capacitive screens with support for multi-touch gestures rather than physical keyboards, and offer the ability for users to download or purchase additional applications from a centralized store, and use cloud storage and synchronization, virtual assistants, as well as mobile payment services.

Improving hardware and faster wireless standards (such as LTE) have bolstered the growth of the smartphone industry. In the third quarter of 2012, one billion smartphones were in use worldwide.[1] Global smartphone sales surpassed the sales figures for feature phones in early 2013.[2]

History

Forerunner

IBM Simon and charging base (1994)[3]

The first commercially available device that could be properly referred to as a "smartphone" began as a prototype called "Angler" developed by Frank Canova in 1992 while at IBM and demonstrated in November of that year at the COMDEX computer industry trade show.[4][5][6] A refined version was marketed to consumers in 1994 by BellSouth under the name Simon Personal Communicator. In addition to placing and receiving cellular calls, the touchscreen-equipped Simon could send and receive faxes and emails. It included an address book, calendar, appointment scheduler, calculator, world time clock, and notepad, as well as other visionary mobile applications such as maps, stock reports and news.[7] The term "smart phone" or "smartphone" was not coined until a year after the introduction of the Simon, appearing in print as early as 1995, describing AT&T's PhoneWriter Communicator.[8][non-primary source needed]

Early integration of data signals with telephony

The first caller identification receiver (1971)

The first integration of data signals with telephony was conceptualized by Nikola Tesla in 1909 and pioneered by Theodore Paraskevakos beginning in 1968 with his work on transmission of electronic data through telephone lines. In 1971, while he was working with Boeing in Huntsville, Alabama, Paraskevakos demonstrated a transmitter and receiver that provided additional ways to communicate with remote equipment. This formed the original basis for what is now known as caller ID.[9] The first caller ID equipment was installed at Peoples' Telephone Company in Leesburg, Alabama and was demonstrated to several telephone companies. The original and historic working models are still in the possession of Paraskevakos.[10]

PDA/phone hybrids

In the mid-late 1990s, many people who had mobile phones carried a separate dedicated PDA device, running early versions of operating systems such as Palm OS, Newton OS, Symbian or Windows CE/Pocket PC. These operating systems would later evolve into early mobile operating systems. Most of the "smartphones" in this era were hybrid devices that combined these existing familiar PDA OSes with basic phone hardware. The results were devices that were bulkier than either dedicated mobile phones or PDAs, but allowed a limited amount of cellular Internet access. The trend at the time, however, that manufacturers competed on in both mobile phones and PDAs was to make devices smaller and slimmer. The bulk of these smartphones combined with their high cost and expensive data plans, plus other drawbacks such as expansion limitations and decreased battery life compared to separate standalone devices, generally limited their popularity to "early adopters" and business users who needed portable connectivity.

In March 1996, Hewlett-Packard released the OmniGo 700LX, a modified HP 200LX palmtop PC with a Nokia 2110 mobile phone piggybacked onto it and ROM-based software to support it. It had a 640×200 resolution CGA compatible four-shade gray-scale LCD screen and could be used to place and receive calls, and to create and receive text messages, emails and faxes. It was also 100% DOS 5.0 compatible, allowing it to run thousands of existing software titles, including early versions of Windows.

The Nokia 9000 Communicator (right) and the updated 9110 model (left)

In August 1996, Nokia released the Nokia 9000 Communicator, a digital cellular PDA based on the Nokia 2110 with an integrated system based on the PEN/GEOS 3.0 operating system from Geoworks. The two components were attached by a hinge in what became known as a clamshell design, with the display above and a physical QWERTY keyboard below. The PDA provided e-mail; calendar, address book, calculator and notebook applications; text-based Web browsing; and could send and receive faxes. When closed, the device could be used as a digital cellular telephone.

In June 1999 Qualcomm released the "pdQ Smartphone", a CDMA digital PCS smartphone with an integrated Palm PDA and Internet connectivity.[11]

Subsequent landmark devices included:

  • The Ericsson R380 (2000) by Ericsson Mobile Communications.[12] The first device marketed as a "smartphone",[13] it was the first Symbian-based phone, with PDA functionality and limited Web browsing on a resistive touchscreen utilizing a stylus.[14] Users could not install their own software on the device, however.
  • The Kyocera 6035 (early 2001), a dual-nature device with a separate Palm OS PDA operating system and CDMA mobile phone firmware. It supported limited Web browsing with the PDA software treating the phone hardware as an attached modem.[15][16]
  • Handspring's Treo 180 (2002), the first smartphone that fully integrated the Palm OS on a GSM mobile phone having telephony, SMS messaging and Internet access built in to the OS. The 180 model had a thumb-type keyboard and the 180g version had a Graffiti handwriting recognition area, instead.[17]

Japanese cell phones

In 1999, Japanese wireless provider NTT DoCoMo launched i-mode, a new mobile internet platform which provided data transmission speeds up to 9.6 kilobits per second, and access web services available through the platform such as online shopping. NTT DoCoMo's i-mode used cHTML, a language which restricted some aspects of traditional HTML in favor of increasing data speed for the devices. Limited functionality, small screens and limited bandwidth allowed for phones to use the slower data speeds available. The rise of i-mode helped NTT DoCoMo accumulate an estimated 40 million subscribers by the end of 2001, and ranked first in market capitalization in Japan and second globally. This power would later wane in the face of the rise of 3G and new phones with advanced wireless network capabilities. Japanese cell phones increasingly diverged from global standards and trends to offer other forms of advanced services and functionality, such as mobile payments, near-field communication (NFC), and 1seg mobile television.[18][19][20][21][22]

Early smartphones

Several BlackBerry smartphones, which were highly popular in the mid-late 2000s

Smartphones were still rare outside Japan until the introduction of the Danger Hiptop in 2002, which saw moderate success among U.S. consumers as the T-Mobile Sidekick. Later, in the mid-2000s, business users in the U.S. started to adopt devices based on Microsoft's Windows Mobile, and then BlackBerry smartphones from Research In Motion. American users popularized the term "CrackBerry" in 2006 due to the BlackBerry's addictive nature.[23]

Outside the U.S. and Japan, Nokia was seeing success with its smartphones based on Symbian, originally developed by Psion for their personal organisers, and it was the most popular smartphone OS in Europe during the middle to late 2000s. Initially, Nokia's Symbian smartphones were focused on business with the Eseries,[24] similar to Windows Mobile and BlackBerry devices at the time. From 2006 onwards, Nokia started producing consumer-focused smartphones, popularized by the entertainment-focused Nseries. Until 2010, Symbian was the world's most widely used smartphone operating system.[25]

Form factor shift

The original Apple iPhone; its introduction contributed to the steady rise of smartphones that feature large touchscreen interfaces without physical keypads

In the 2000s, it was common for smartphones to have a physical T9 numeric keypad or QWERTY keyboard in either a candybar or sliding form factor. Some smartphones had resistive touchscreens, which allowed for virtual keyboards and handwriting input with a finger or a stylus, thus also allowing easy entry of Asian characters.[26]

In 2007, the LG Prada was the first mobile phone released with a large capacitive touchscreen.[27] Later that year, Apple Computer introduced the iPhone. The iPhone was also designed around a large capacitive touchscreen, but added support for multi-touch gestures (for interactions such as "pinching" to zoom in and out on photos and web pages). Such phones were notable for abandoning the use of a stylus, keyboard, or keypad typical for smartphones at the time, in favor of a capacitive touchscreen for direct finger input as its only input type.

The iPhone was "not a smartphone by conventional terms, being that a smartphone is a platform device that allows software to be installed,"[28] until the opening of Apple's App Store a year later, which became a common means for smartphone software distribution and installation. The first iPhone also faced criticism for not supporting the latest 3G wireless network standards, but was praised for its hardware and software design, and its June 2007 release was met with heavy demand, with customers waiting in lines outside Apple Store locations to be among the first to purchase it.[29]

The screen focused hardware of phones centered around a capacitive touchscreen, stimulated the software to focus on features such as a web browser designed to render full web pages (as opposed to stripped down WAP services), multimedia functionality (such as music and videos), and online services such as maps apps.

The advantages of a design around a capacitive touchscreen, affected the development of another smartphone OS platform, Android, with a more BlackBerry-esque prototype device scrapped in favor of a touchscreen device with a slide-out physical keyboard.[30][31][32] The first Android device, the HTC Dream, was released in September 2008.[33] Although Android's adoption was relatively slow at first, it started to gain widespread popularity in 2010, and in early 2012 dominated the smartphone market share worldwide, which continues to this day.[34]

Android and iPhone devices popularized the smartphone form factor based on a large capacitive touchscreen, and led to the decline of earlier, keyboard- and keypad-focused platforms. Microsoft, for instance, discontinued Windows Mobile and started a new touchscreen-oriented OS from scratch, called Windows Phone. Nokia abandoned Symbian and partnered with Microsoft to use Windows Phone on its smartphones. Windows Phone became the third-most-popular smartphone OS, before being replaced by Windows 10 Mobile, which declined in share to become "largely irrelevant" at less than 0.5% of the smartphone market.[35] Palm replaced their Palm OS with webOS, which was bought by Hewlett-Packard and later sold to LG Electronics for use on LG smart TVs. BlackBerry Limited, formerly known as Research In Motion, made a new platform based on QNX, BlackBerry 10, with which it was possible to control a device without having to press any physical buttons; this platform was later discontinued.

By the mid-2010s, almost all smartphones were touchscreen-only, and Android and iPhone smartphones dominated the market.

Developments in the 2010s

In 2013, Fairphone launched its first "socially ethical" smartphone at the London Design Festival to address concerns regarding the sourcing of materials in the manufacturing.[36] In late 2013, QSAlpha commenced production of a smartphone designed entirely around security, encryption and identity protection.[37] Some companies began to release smartphones incorporating flexible displays to create curved form factors, such as the Samsung Galaxy Round and LG G Flex.[38][39][40]

In October 2013, Motorola Mobility announced Project Ara, a concept for a modular smartphone platform that would allow users to customize and upgrade their phones with add-on modules that attached magnetically to a frame.[41][42] Ara was retained by Google following its sale of Motorola Mobility to Lenovo,[43] but was shelved in 2016.[44] That year, LG and Motorola both unveiled smartphones featuring a limited form of modularity for accessories; the LG G5 allowed accessories to be installed via the removal of its battery compartment,[45] while the Moto Z utilizes accessories attached magnetically to the rear of the device.[46]

The first smartphone with a fingerprint reader was the Motorola Atrix 4G in 2011.[47] In September 2013, the iPhone 5S was unveiled as the first smartphone on a major U.S. carrier since the Atrix to feature this technology.[48]

By 2014, 1440p displays began to appear on high-end smartphones.[49] In 2015, Sony released the Xperia Z5 Premium, featuring a 4K resolution display, although only images and videos could actually be rendered at that resolution (all other software is upscaled from 1080p).[50] Microsoft, expanding upon the concept of Motorola's short-lived "Webtop", unveiled functionality for its Windows 10 operating system for phones that allows supported devices to be docked for use with a PC-styled desktop environment.[51][52] Other major technologies began to trend in 2016, including a focus on virtual reality and augmented reality experiences catered towards smartphones, the newly introduced USB-C connector, and improving LTE technologies.[53] As of 2015, the global median for smartphone ownership was 43%.[54] Statista forecast that 2.87 billion people would own smartphones in 2020.[55]

New trends for smartphone displays began to emerge in 2017, with both LG and Samsung releasing flagship smartphones utilizing displays with taller aspect ratios than the common 16:9 ratio. These designs allow the display to have a larger physical size, but with a slimmer width than 16:9 displays with an equivalent screen size.[56][57][58] Another trend popularized that year were designs—colloquially known as a "notch"—where the front-facing camera, and sometimes other sensors typically located along the top bezel of a device, are contained into a tab-like area at the top of the device that the display wraps around. These designs allow for "edge-to-edge" displays that take up nearly the entire height of the device, with little to no bezel along the top. This design characteristic was popularized by the Essential Phone (which featured a circular tab for its camera) and iPhone X (which used a wider tab to contain a camera and facial scanning system).[59][60][61][62] In 2018, the first smartphones featuring fingerprint readers embedded within OLED displays were announced.[63]

Future possible developments

An example of a flexible display

Foldable OLED smartphones have been anticipated for years but have failed to materialize because of the relatively high failure rate when producing these screens.[citation needed] Creating a battery that can be folded is another hurdle.[64] Samsung has attempted to make a smartphone with a flexible display. Samsung is still on some finishing touches which after then may become the first OLED or flexible smartphone made.[citation needed]

Hardware

Central processing unit

Smartphones have central processing units (CPUs), similar to those in computers, but optimised to operate in low power environments.

Mobile CPU performance depends not only on the clock rate (generally given in multiples of hertz)[65] but also the memory hierarchy also greatly affects overall performance. Because of these problems, the performance of mobile phone CPUs is often more appropriately given by scores derived from various standardized tests to measure the real effective performance in commonly used applications.

Display

A smartphone touchscreen

One of the main characteristics of smartphones is the screen. Depending on the device's design, the screen fills most or nearly all of the space on a device's front surface. Many smartphone displays have an aspect ratio of 16:9, but taller aspect ratios became more common in 2017.

Screen sizes are measured in diagonal inches; phones with screens larger than 5.2 inches are often called "phablets." Smartphones with screens over 4.5 inches in size are commonly difficult to use with only a single hand, since most thumbs cannot reach the entire screen surface; they may need to be shifted around in the hand, held in one hand and manipulated by the other, or used in place with both hands. Due to design advances, some modern smartphones with large screen sizes and "edge-to-edge" designs have compact builds that improve their ergonomics, while the shift to taller aspect ratios have resulted in phones that have larger screen sizes whilst maintaining the ergonomics associated with smaller 16:9 displays.[66][67][68]

Liquid-crystal displays are the most common; others are IPS, LED, OLED, and AMOLED displays. Some displays are integrated with pressure-sensitive digitizers, such as those developed by Wacom and Samsung,[69] and Apple's "3D Touch" system.

Sound

Some audio quality enhancing features, such as Voice over LTE and HD Voice, have appeared and are often available on newer smartphones. Sound quality can remain a problem due to the design of the phone, the quality of the cellular network and compression algorithms used in long distance calls.[70][71] Audio quality can be improved using a VoIP application over WiFi.[72] Cellphones have small speakers so that the user can use a speakerphone feature and talk to a person on the phone without holding it to their ear. The small speakers can also be used to listen to digital audio files of music or speech or watch videos with an audio component, without holding the phone close to the ear.

Battery

A high-capacity portable battery charger

By the end of 2017, smartphone battery life has become generally adequate;[73] however, earlier smartphone battery life was poor due to the weak batteries that could not handle the significant power requirements of the smartphones' computer systems and color screens.[74][75][76]

Smartphone users purchase additional chargers for use outside the home, at work, and in cars and by buying portable external "battery packs". External battery packs include generic models which are connected to the smartphone with a cable and custom-made models that "piggyback" onto a smartphone's case. In 2016, Samsung had to recall millions of the Galaxy Note 7 smartphones due to an explosive battery issue.[77] For consumer convenience, wireless charging stations have been introduced in some hotels, bars, and other public spaces.[78]

Accessories

A wide range of accessories are sold for smartphones, including cases, screen protectors, power charging cables, wireless power stations, USB On-The-Go adapters (for connecting USB drives and or, in some cases, a HDMI cable to an external monitor), add-on batteries, headphones, combined headphone-microphones (which, for example, allow a person to privately conduct calls on the device without holding it to the ear), and Bluetooth-enabled powered speakers that enable users to listen to media from their smartphones wirelessly.

Cases range from relatively inexpensive rubber or soft plastic cases which provide moderate protection from bumps and good protection from scratches to more expensive, heavy-duty cases that combine a rubber padding with a hard outer shell. Some cases have a "book"-like form, with a cover that the user opens to use the device; when the cover is closed, it protects the screen. Some "book"-like cases have additional pockets for credit cards, thus enabling people to use them as wallets.

Accessories include products sold by the manufacturer of the smartphone and compatible products made by other manufacturers.

Software

Mobile operating systems

A mobile operating system (or mobile OS) is an operating system for phones, tablets, smartwatches, or other mobile devices.

Mobile operating systems combine features of a personal computer operating system with other features useful for mobile or handheld use; usually including, and most of the following considered essential in modern mobile systems; a touchscreen, cellular, Bluetooth, Wi-Fi Protected Access, Wi-Fi, Global Positioning System (GPS) mobile navigation, video- and single-frame picture cameras, speech recognition, voice recorder, music player, near field communication, and infrared blaster. By Q1 2018, over 383 million smartphones were sold with 85.9 percent running Android, 14.1 percent running iOS and other OSes negligible.[79] Android alone is more popular than the popular desktop operating system Windows, and in general smartphone use (even without tablets) outnumber desktop use.

Mobile devices with mobile communications abilities (e.g., smartphones) contain two mobile operating systems – the main user-facing software platform is supplemented by a second low-level proprietary real-time operating system which operates the radio and other hardware. Research has shown that these low-level systems may contain a range of security vulnerabilities permitting malicious base stations to gain high levels of control over the mobile device.[80]

Mobile app

A mobile app is a computer program designed to run on a mobile device, such as a smartphone. The term "app" is a shortening of the term "software application".

Application stores

The introduction of Apple's App Store for the iPhone and iPod Touch in July 2008 popularized manufacturer-hosted online distribution for third-party applications (software and computer programs) focused on a single platform. There are a huge variety of apps, including video games, music products and business tools. Up until that point, smartphone application distribution depended on third-party sources providing applications for multiple platforms, such as GetJar, Handango, Handmark, and PocketGear. Following the success of the App Store, other smartphone manufacturers launched application stores, such as Google's Android Market (later renamed to the Google Play Store) and RIM's BlackBerry App World and Android-related app stores like F-Droid. In February 2014, 93% of mobile developers were targeting smartphones first for mobile app development.[81]

Sales

Since 1996, smartphone shipments have had positive growth. In November 2011, 27% of all photographs created were taken with camera-equipped smartphones.[82] In September 2012, a study concluded that 4 out of 5 smartphone owners use the device to shop online.[83] Global smartphone sales surpassed the sales figures for feature phones in early 2013.[2] Worldwide shipments of smartphones topped 1 billion units in 2013, up 38% from 2012's 725 million, while comprising a 55% share of the mobile phone market in 2013, up from 42% in 2012.[84] In Q1 2016 for the first time the shipments dropped by 3 percent year on year. The situation was caused by the maturing China market.[85]

By manufacturer

Worldwide Smartphones Vendors Market Share
Source Date Samsung Huawei Apple Inc. Xiaomi Oppo Others Reference
Gartner Q2 2018 19.3% 13.3% 11.9% 8.8% 7.6% 39.0% [86]
IDC Q2 2018 21.0% 15.9% 12.1% 9.5% 8.6% 32.9% [87]

In 2011, Samsung had the highest shipment market share worldwide, followed by Apple. In 2013, Samsung had 31.3% market share, a slight increase from 30.3% in 2012, while Apple was at 15.3%, a decrease from 18.7% in 2012. Huawei, LG and Lenovo were at about 5% each, significantly better than 2012 figures, while others had about 40%, the same as the previous years figure. Only Apple lost market share, although their shipment volume still increased by 12.9 percent; the rest had significant increases in shipment volumes of 36 to 92 percent.[88] In Q1 2014, Samsung had a 31% share and Apple had 16%.[89] In Q4 2014, Apple had a 20.4% share and Samsung had 19.9%.[90] In Q2 2016, Samsung had a 22.3% share and Apple had 12.9%.[86] In Q1 2017, IDC reported that Samsung was first placed, with 80 million units, followed by Apple with 50.8 million, Huawei with 34.6 million, Oppo with 25.5 million and Vivo with 22.7 million.[91]

Samsung's mobile business is half the size of Apple's, by revenue. Apple business has been increasing very rapidly over the past 4 years.[92]

By operating system

Use

Social

A 2012 University of Southern California study found that unprotected adolescent sexual activity was more common among owners of smartphones.[93] A study conducted by the Rensselaer Polytechnic Institute's (RPI) Lighting Research Center (LRC) concluded that smartphones, or any backlit devices, can seriously affect sleep cycles.[94] Some persons might become psychologically attached to smartphones resulting in anxiety when separated from the devices.[95] A "smombie" (a combination of "smartphone" and "zombie") is a walking person using a smartphone and not paying attention as they walk, possibly risking an accident in the process, an increasing social phenomenon.[96] The issue of slow-moving smartphone users led to the temporary creation of a "mobile lane" for walking in Chongqing, China.[97] The issue of distracted smartphone users led the city of Augsburg, Germany to embed pedestrian traffic lights in the pavement.[98]

Mobile banking and payment

Mobile payment system.

In many countries, mobile phones are used to provide mobile banking services, which may include the ability to transfer cash payments by secure SMS text message. Kenya's M-PESA mobile banking service, for example, allows customers of the mobile phone operator Safaricom to hold cash balances which are recorded on their SIM cards. Cash can be deposited or withdrawn from M-PESA accounts at Safaricom retail outlets located throughout the country and can be transferred electronically from person to person and used to pay bills to companies.

Branchless banking has been successful in South Africa and the Philippines. A pilot project in Bali was launched in 2011 by the International Finance Corporation and an Indonesian bank, Bank Mandiri.[99]

Another application of mobile banking technology is Zidisha, a US-based nonprofit micro-lending platform that allows residents of developing countries to raise small business loans from Web users worldwide. Zidisha uses mobile banking for loan disbursements and repayments, transferring funds from lenders in the United States to borrowers in rural Africa who have mobile phones and can use the Internet.[100]

Mobile payments were first trialled in Finland in 1998 when two Coca-Cola vending machines in Espoo were enabled to work with SMS payments. Eventually, the idea spread and in 1999, the Philippines launched the country's first commercial mobile payments systems with mobile operators Globe and Smart.

Some mobile phones can make mobile payments via direct mobile billing schemes, or through contactless payments if the phone and the point of sale support near field communication (NFC).[101] Enabling contactless payments through NFC-equipped mobile phones requires the co-operation of manufacturers, network operators, and retail merchants.[102][103]

While driving

A New York City driver holding two phones
A user consulting a mapping app on a phone

Mobile phone use while driving—including calling, text messaging, playing media, web browsing, gaming, using mapping apps or operating other phone features—is common but controversial, since it is widely considered dangerous due to what is known as distracted driving. Being distracted while operating a motor vehicle has been shown to increase the risk of accidents. In September 2010, the US National Highway Traffic Safety Administration (NHTSA) reported that 995 people were killed by drivers distracted by phones. In March 2011 a US insurance company, State Farm Insurance, announced the results of a study which showed 19% of drivers surveyed accessed the Internet on a smartphone while driving.[104] Many jurisdictions prohibit the use of mobile phones while driving. In Egypt, Israel, Japan, Portugal and Singapore, both handheld and hands-free calling on a mobile phone (which uses a speakerphone) is banned. In other countries including the UK and France and in many US states, only the use of calling on handheld phones is banned, while hands-free use is permitted.

A 2011 study reported that over 90% of college students surveyed text (initiate, reply or read) while driving.[105] The scientific literature on the danger of driving while sending a text message from a mobile phone, or texting while driving, is limited. A simulation study at the University of Utah found a sixfold increase in distraction-related accidents when texting.[106] Due to the complexity of smartphones that began to grow more after, this has introduced additional difficulties for law enforcement officials when attempting to distinguish one usage from another in drivers using their devices. This is more apparent in countries which ban both handheld and hands-free usage, rather than those which ban handheld use only, as officials cannot easily tell which function of the phone is being used simply by looking at the driver. This can lead to drivers being stopped for using their device illegally for a call when, in fact, they were using the device legally, for example, when using the phone's incorporated controls for car stereo, GPS or satnav.

A sign along Bellaire Boulevard in Southside Place, Texas (Greater Houston) states that using mobile phones while driving is prohibited from 7:30 am to 9:30 am and from 2:00 pm to 4:15 pm

A 2010 study reviewed the incidence of phone use while cycling and its effects on behavior and safety.[107] In 2013 a national survey in the US reported the number of drivers who reported using their phones to access the Internet while driving had risen to nearly one of four.[108] A study conducted by the University of Vienna examined approaches for reducing inappropriate and problematic use of mobile phones, such as using phones while driving.[109]

Accidents involving a driver being distracted by being in a call on a phone have begun to be prosecuted as negligence similar to speeding. In the United Kingdom, from 27 February 2007, motorists who are caught using a handheld phone while driving will have three penalty points added to their license in addition to the fine of £60.[110] This increase was introduced to try to stem the increase in drivers ignoring the law.[111] Japan prohibits all use of phones while driving, including use of hands-free devices. New Zealand has banned handheld phone use since 1 November 2009. Many states in the United States have banned text messaging on phones while driving. Illinois became the 17th American state to enforce this law.[112] As of July 2010, 30 states had banned texting while driving, with Kentucky becoming the most recent addition on July 15.[113]

Public Health Law Research maintains a list of distracted driving laws in the United States. This database of laws provides a comprehensive view of the provisions of laws that restrict the use of mobile devices while driving for all 50 states and the District of Columbia between 1992, when first law was passed through December 1, 2010. The dataset contains information on 22 dichotomous, continuous or categorical variables including, for example, activities regulated (e.g., texting versus talking, hands-free versus handheld calls, web browsing, gaming), targeted populations, and exemptions.[114]

Legal

A "patent war" between Samsung and Apple started when the latter claimed that the original Galaxy S Android phone copied the interface‍—‌and possibly the hardware‍—‌of Apple's iOS for the iPhone 3GS. There was also smartphone patents licensing and litigation involving Sony Mobile, Google, Apple Inc., Samsung, Microsoft, Nokia, Motorola, HTC, Huawei and ZTE, among others. The conflict is part of the wider "patent wars" between multinational technology and software corporations. To secure and increase market share, companies granted a patent can sue to prevent competitors from using the methods the patent covers. Since the 2010's the number of lawsuits, counter-suits, and trade complaints based on patents and designs in the market for smartphones, and devices based on smartphone OSes such as Android and iOS, has increased significantly. Initial suits, countersuits, rulings, license agreements, and other major events began in 2009 as the smartphone market stated to grow more rapidly by 2012.

Facsimile

Some apps allows for sending and receiving facsimile (Fax), over a smartphone, including facsimile data (composed of raster bi-level graphics) generated directly and digitally from document and image file formats.

Medical

With the rise in number of mobile medical apps in the market place, government regulatory agencies raised concerns on the safety of the use of such applications. These concerns were transformed into regulation initiatives worldwide with the aim of safeguarding users from untrusted medical advice.[115]

Security

Smartphone malware is easily distributed through an insecure app store.[116][117] Often, malware is hidden in pirated versions of legitimate apps, which are then distributed through third-party app stores.[118][119] Malware risk also comes from what is known as an "update attack", where a legitimate application is later changed to include a malware component, which users then install when they are notified that the app has been updated.[120] As well, one out of three robberies in 2012 in the United States involved the theft of a mobile phone. An online petition has urged smartphone makers to install kill switches in their devices.[121] In 2014, Apple's "Find my iPhone" and Google's "Android Device Manager" can locate, disable, and wipe the data from phones that have been lost or stolen. With BlackBerry Protect in OS version 10.3.2, devices can be rendered unrecoverable to even BlackBerry's own Operating System recovery tools if incorrectly authenticated or dissociated from their account.[122]

Leaked documents published by WikiLeaks, codenamed Vault 7 and dated from 2013–2016, detail the capabilities of the United States Central Intelligence Agency (CIA) to perform electronic surveillance and cyber warfare, including the ability to compromise the operating systems of most smartphones (including iOS and Android).[123][124]

Sleep

Using smartphones late at night can disturb sleep, due to the blue light and brightly lit screen, which affects melatonin levels and sleep cycles. In an effort to alleviate these issues, several apps that change the color temperature of a screen to a warmer hue based on the time of day to reduce the amount of blue light generated have been developed for Android, while iOS 9.3 integrated similar, system-level functionality known as "Night Shift". Amazon released a feature known as "blue shade" in their Fire OS "Bellini" 5.0 and later. It has also been theorized that for some users, addicted use of their phones, especially before they go to bed, can result in "ego depletion". Many people also use their phones as alarm clocks, which can also lead to loss of sleep.[125][126][127][128][129]

Bokeh cameras

Pocket cameras have difficulty producing bokeh in images, but nowadays, some smartphones have dual-lens cameras that produce the bokeh effect easily, and can even rearrange the level of bokeh after shooting. The iPhone 7 Plus debuted with a dual-lens camera in the back of the smartphone.[130] More advanced smartphones may come with 'quad cameras', or two dual-lens cameras such as the Honor 9 Lite smartphone. The back and front of the smartphone each have a 13MP main lens and a 2MP lens for capturing depth information.[131] The Evercoss U50A Max smartphone has 4 cameras, and costs less than $100.[132]

Huawei P20 Pro smartphone with triple lenses in the back of the smartphone has been launched as bokeh camera smartphone with optical zoom. First lens has 40MP RGB, second lens has 20MP monochrome and third lens has 8MP RGB telephoto 3x. The zoom can be enhanced to 5x with combination of the optical zoom and megapixel lens 40MP RGB to produce undeteriorated (optical+digital) zoom or digital zoom without loss of quality.[133]

See also

References

  1. ^ Don Reisinger (October 17, 2012). "Worldwide smartphone user base hits 1 billion". CNet. Retrieved July 26, 2013.
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External links

LTE Advanced

LTE Advanced logo
LTE Advanced (with carrier aggregation) signal indicator in Android

LTE Advanced is a mobile communication standard and a major enhancement of the Long Term Evolution (LTE) standard. It was formally submitted as a candidate 4G to ITU-T in late 2009 as meeting the requirements of the IMT-Advanced standard, and was standardized by the 3rd Generation Partnership Project (3GPP) in March 2011 as 3GPP Release 10.[1]

Background[edit]

The LTE format was first proposed by NTT DoCoMo of Japan and has been adopted as the international standard.[2] LTE standardization has matured to a state where changes in the specification are limited to corrections and bug fixes. The first commercial services were launched in Sweden and Norway in December 2009[3] followed by the United States and Japan in 2010. More LTE networks were deployed globally during 2010 as a natural evolution of several 2G and 3G systems, including Global system for mobile communications (GSM) and Universal Mobile Telecommunications System (UMTS) in the 3GPP family as well as CDMA2000 in the 3GPP2 family.

The work by 3GPP to define a 4G candidate radio interface technology started in Release 9 with the study phase for LTE-Advanced. Being described as a 3.9G (beyond 3G but pre-4G), the first release of LTE did not meet the requirements for 4G (also called IMT Advanced as defined by the International Telecommunication Union) such as peak data rates up to 1 Gb/s. The ITU has invited the submission of candidate Radio Interface Technologies (RITs) following their requirements in a circular letter, 3GPP Technical Report (TR) 36.913, "Requirements for Further Advancements for E-UTRA (LTE-Advanced)."[4] These are based on ITU's requirements for 4G and on operators’ own requirements for advanced LTE. Major technical considerations include the following:

  • Continual improvement to the LTE radio technology and architecture
  • Scenarios and performance requirements for working with legacy radio technologies
  • Backward compatibility of LTE-Advanced with LTE. An LTE terminal should be able to work in an LTE-Advanced network and vice versa. Any exceptions will be considered by 3GPP.
  • Consideration of recent World Radiocommunication Conference (WRC-07) decisions regarding frequency bands to ensure that LTE-Advanced accommodates the geographically available spectrum for channels above 20 MHz. Also, specifications must recognize those parts of the world in which wideband channels are not available.

Likewise, 'WiMAX 2', 802.16m, has been approved by ITU as the IMT Advanced family. WiMAX 2 is designed to be backward compatible with WiMAX 1 devices. Most vendors now support conversion of 'pre-4G', pre-advanced versions and some support software upgrades of base station equipment from 3G.

The mobile communication industry and standards organizations have therefore started work on 4G access technologies, such as LTE Advanced.[when?] At a workshop in April 2008 in China, 3GPP agreed the plans for work on Long Term Evolution (LTE).[5] A first set of specifications were approved in June 2008.[6] Besides the peak data rate 1 Gb/s as defined by the ITU-R, it also targets faster switching between power states and improved performance at the cell edge. Detailed proposals are being studied within the working groups.[when?]

Proposals[edit]

The target of 3GPP LTE Advanced is to reach and surpass the ITU requirements. LTE Advanced should be compatible with first release LTE equipment, and should share frequency bands with first release LTE. In the feasibility study for LTE Advanced, 3GPP determined that LTE Advanced would meet the ITU-R requirements for 4G. The results of the study are published in 3GPP Technical Report (TR) 36.912.[7]

One of the important LTE Advanced benefits is the ability to take advantage of advanced topology networks; optimized heterogeneous networks with a mix of macrocells with low power nodes such as picocells, femtocells and new relay nodes. The next significant performance leap in wireless networks will come from making the most of topology, and brings the network closer to the user by adding many of these low power nodes — LTE Advanced further improves the capacity and coverage, and ensures user fairness. LTE Advanced also introduces multicarrier to be able to use ultra wide bandwidth, up to 100 MHz of spectrum supporting very high data rates.

In the research phase many proposals have been studied as candidates for LTE Advanced (LTE-A) technologies. The proposals could roughly be categorized into:[8]

  • Support for relay node base stations
  • Coordinated multipoint (CoMP) transmission and reception
  • UE Dual TX antenna solutions for SU-MIMO and diversity MIMO, commonly referred to as 2x2 MIMO
  • Scalable system bandwidth exceeding 20 MHz, up to 100 MHz
  • Carrier aggregation of contiguous and non-contiguous spectrum allocations
  • Local area optimization of air interface
  • Nomadic / Local Area network and mobility solutions
  • Flexible spectrum usage
  • Cognitive radio
  • Automatic and autonomous network configuration and operation
  • Support of autonomous network and device test, measurement tied to network management and optimization
  • Enhanced precoding and forward error correction
  • Interference management and suppression
  • Asymmetric bandwidth assignment for FDD
  • Hybrid OFDMA and SC-FDMA in uplink
  • UL/DL inter eNB coordinated MIMO
  • SONs, Self Organizing Networks methodologies

Within the range of system development, LTE-Advanced and WiMAX 2 can use up to 8x8 MIMO and 128-QAM in downlink direction. Example performance: 100 MHz aggregated bandwidth, LTE-Advanced provides almost 3.3 Gbit peak download rates per sector of the base station under ideal conditions. Advanced network architectures combined with distributed and collaborative smart antenna technologies provide several years road map of commercial enhancements.

The 3GPP standards Release 12 added support for 256-QAM.

A summary of a study carried out in 3GPP can be found in TR36.912.[9]

Timeframe and introduction of additional features[edit]

Original standardization work for LTE-Advanced was done as part of 3GPP Release 10, which was frozen in April 2011. Trials were based on pre-release equipment. Major vendors support software upgrades to later versions and ongoing improvements.

In order to improve the quality of service for users in hotspots and on cell edges, heterogenous networks (HetNet) are formed of a mixture of macro-, pico- and femto base stations serving corresponding-size areas. Frozen in December 2012, 3GPP Release 11[10] concentrates on better support of HetNet. Coordinated Multi-Point operation (CoMP) is a key feature of Release 11 in order to support such network structures. Whereas users located at a cell edge in homogenous networks suffer from decreasing signal strength compounded by neighbor cell interference, CoMP is designed to enable use of a neighboring cell to also transmit the same signal as the serving cell, enhancing quality of service on the perimeter of a serving cell. In-device Co-existence (IDC) is another topic addressed in Release 11. IDC features are designed to ameliorate disturbances within the user equipment caused between LTE/LTE-A and the various other radio subsystems such as WiFi, Bluetooth, and the GPS receiver. Further enhancements for MIMO such as 4x4 configuration for the uplink were standardized.

The higher number of cells in HetNet results in user equipment changing the serving cell more frequently when in motion. The ongoing work on LTE-Advanced[11] in Release 12, amongst other areas, concentrates on addressing issues that come about when users move through HetNet, such as frequent hand-overs between cells. It also included use of 256-QAM.

First technology demonstrations and field trials[edit]

This list covers technology demonstrations and field trials up to the year 2014, paving the way for a wider commercial deployment of the VoLTE technology worldwide. From 2014 onwards various further operators trialled and demonstrated the technology for future deployment on their respective networks. These are not covered here. Instead a coverage of commercial deployments can be found in the section below.

Company Country Date Note
NTT DoCoMo  Japan February 2007 [12] The operator announced the completion of a 4G trial where it achieved a maximum packet transmission rate of approximately 5 Gbit/s in the downlink using 12 transmit and 12 receive antennas and 100 MHz frequency bandwidth to a mobile station moving at 10 km/h.
Agilent Technologies  Spain February 2011 [13] The vendor demonstrated at Mobile World Congress the industry's first test solutions for LTE-Advanced with both signal generation and signal analysis solutions.
Ericsson  Sweden June 2011 [14] The vendor demonstrated LTE-Advanced in Kista.
touch  Lebanon April 2013 [15] The operator trialed LTE-Advanced with Chinese vendor Huawei and combined 800 MHz spectrum and 1.8 GHz spectrum. touch achieved 250 Mbit/s.
Vodafone  New Zealand May 2013 [16] The operator trialed LTE-Advanced with Nokia Networks and combined 1.8 GHz spectrum and 700 MHz spectrum. Vodafone achieved just below 300 Mbit/s.
A1  Austria June 2013 [17] The operator trialed LTE-Advanced with Ericsson and NSN using 4x4 MIMO. A1 achieved 580 Mbit/s.
Turkcell  Turkey August 2013 [18] The operator trialed LTE-Advanced in Istanbul with Chinese vendor Huawei. Turkcell achieved 900 Mbit/s.
Telstra  Australia August 2013 [19] The operator trialed LTE-Advanced with Swedish vendor Ericsson and combined 900 MHz spectrum and 1.8 GHz spectrum.
SMART  Philippines August 2013 [20] The operator trialed LTE-Advanced with Chinese vendor Huawei and combined 2.1 GHz spectrum and 1.80 GHz spectrum bands and achieved 200 Mbit/s.
SoftBank  Japan September 2013 [21] The operator trialed LTE-Advanced in Tokyo with Chinese vendor Huawei. Softbank used the 3.5 GHz spectrum band and achieved 770 Mbit/s.
beCloud/ MTS  Belarus October 2013 [22] The operator trialed LTE-Advanced with Chinese vendor Huawei.
SFR  France October 2013 [23] The operator trialed LTE-Advanced in Marseille and combined 800 MHz spectrum and 2.6 GHz spectrum. SFR achieved 174 Mbit/s.
EE  United Kingdom November 2013 [24] The operator trialed LTE-Advanced in London with Chinese vendor Huawei and combined 20 MHz of 1.8 GHz spectrum and 20 MHz of 2.6 GHz spectrum. EE achieved 300 Mbit/s which is equal to category 6 LTE.
O2  Germany November 2013 [25] The operator trialed LTE-Advanced in Munich with Chinese vendor Huawei and combined 10 MHz of 800 MHz spectrum and 20 MHz of 2.6 GHz spectrum. O2 achieved 225 Mbit/s.
SK Telecom  South Korea November 2013 [26] The operator trialed LTE-Advanced and combined 10 MHz of 850 MHz spectrum and 20 MHz of 1.8 GHz spectrum. SK Telecom achieved 225 Mbit/s.
Vodafone  Germany November 2013 [27] The operator trialed LTE-Advanced in Dresden with Swedish vendor Ericsson and combined 10 MHz of 800 MHz spectrum and 20 MHz of 2.6 GHz spectrum. Vodafone achieved 225 Mbit/s.
Telstra  Australia December 2013 [28] The operator trialed LTE-Advanced with Swedish vendor Ericsson and combined 20 MHz of 1.8 GHz spectrum and 20 MHz of 2.6 GHz spectrum. Telstra achieved 300 Mbit/s which is equal to category 6 LTE.
Optus  Australia December 2013 [29] The operator trialed TD-LTE-Advanced with Chinese vendor Huawei and combined two 20 MHz channels of 2.3 GHz spectrum. Optus achieved over 160 Mbit/s.
Entel Chile  Chile September 2015 [30] The operator trialed LTE-Advanced in Rancagua using 15 MHz of 700 Mhz and 20 MHz of 2600 MHz spectrum, achieving over 200 MB/s.
Claro Brasil  Brazil December 2015 [31] The Claro Brasil presented in Rio Verde the first tests with 4.5G technology, LTE Advanced, which offers an internet speed of up to 300MB/s.
AIS  Thailand March 2016 [32] The operator launched the first 4.5G on LTE-U/LAA network in Bangkok with the combination of 1800 MHz spectrum and 2100 MHz spectrum using Carrier Aggregation (CA), 4x4 MIMO, DL256QAM/UL64QAM and the use of LTE-Unlicensed (LTE-U) to facilitate high-speed network. AIS achieved download speed up to 784.5 Mbit/s and upload speed 495 Mbit/s.[33] This was made possible by Joint Development Center (JIC) the special R&D program between AIS and Huawei.
MagtiCom  Georgia May 2016 [34] The operator trialed LTE-Advanced in Tbilisi and combined the 800MHz with its existing 1800MHz spectrum. MagtiCom achieved download speed 185 Mbit/s and upload speed 75 Mbit/s.
Ucom  Armenia September 2016 [35] The operator trialed LTE-Advanced with Swedish vendor Ericsson. Ucom achieved 250 Mbit/s download speed which is equal to category 6 LTE.
Altel  Kazakhstan April 2017 [36] The operator launched LTE-Advanced in 12 cities across Kazakhstan. Altel achieved 225 Mbit/s download speed. LTE-Advanced (4G+) Technology is up to be launched in 5 more cities in Kazakhstan in May 2017.
Bite Latvija  Latvia September 2016 [37] The operator launched 8 4.5G cell stations in Riga after testing in partnership with Huawei and the Riga Technical University on June 15, 2017.
Wi-Tribe  Pakistan May 2017 [38] The operator first tested their LTE-A network in May 2017 over the 3.5GHz band, and it was then made officially available in Lahore, Pakistan, with more cities to follow. Wi-Tribe achieved speeds of up to 200 Mbit/s over their new LTE-A network. This was done using equipment from Huawei.
Telcel  Mexico March 2018 [39] The operator offered the service in Mexico City and other 10 cities nationwide on March 14, 2018.
Airtel India April 2012 On 10 April 2012, Airtel launched 4G services through dongles and modems using TD-LTE technology in Kolkata, becoming the first company in India to offer 4G services. The Kolkata launch was followed by launches in Bangalore (7 May 2012), Pune (18 October 2012), and Chandigarh, Mohali and Panchkula (25 March 2013).

Deployment[edit]

An LTE Advanced base station installed in Iraq for provisioning of broadband wireless Internet service.

Deployment of LTE-Advanced in progress in various LTE networks.

See also[edit]

Bibliography[edit]

  • Qualcomm
  • Harri Holma, Antti Toskala, LTE for UMTS - OFDMA and SC-FDMA Based Radio Access, John Wiley & Sons 2009, ISBN 978-0-470-99401-6 Chapter 2.6: LTE Advanced for IMT-advanced, pp 19–21.
  • Moray Rumney (editor), LTE and the Evolution to 4G Wireless: Design and Measurement Challenges, Agilent Technologies Publication 2009, ISBN 978-0-470-68261-6, Chapter 8.7: Proving LTE Advanced, p 425
  • Preben E. Mogensen, Tommi Koivisto, Klaus I. Pedersen 1, et al.; Nokia Siemens Networks;LTE Advanced: The Path towards Gigabit/s in Wireless Mobile Communications[permanent dead link], Wireless VITAE'09.
  • Sajal Kumar Das, Mobile Terminal Receiver Design: LTE and LTE-Advanced , John Wiley & Sons 2016, ISBN 9781119107309.

References[edit]

  1. ^ Stefan Parkvall, Erik Dahlman, Anders Furuskär et al.; Ericsson, Robert Syputa, Maravedis; ITU global standard for international mobile telecommunications ´IMT-Advanced´LTE Advanced - Evolving LTE towards IMT-Advanced; Vehicular Technology Conference, 2008. VTC 2008-Fall. IEEE 68th 21-24 Sept. 2008 Page(s):1 - 5.
  2. ^ Faster cell phone services planned
  3. ^ "TeliaSonera launches world's first 4G mobile network". swedishwire. Retrieved 25 November 2013.
  4. ^ "Requirements for further advancements for Evolved Universal Terrestrial Radio Access (E-UTRA) (LTE-Advanced)"
  5. ^ "Beyond 3G: "LTE Advanced" Workshop, Shenzhen, China". Archived from the original on 2008-09-13. Retrieved 2008-09-12.
  6. ^ 3GPP specification: Requirements for further advancements for E-UTRA (LTE Advanced)
  7. ^ Agilent "Archived copy" (PDF). Archived from the original (PDF) on 2011-03-03. Retrieved 2011-07-28., Introducing LTE-Advanced, pg. 6 , March 8, 2011, accessed July 28, 2011.
  8. ^ Nomor Research: White Paper on LTE Advanced
  9. ^ 3GPP Technical Report: Feasibility study for Further Advancements for E-UTRA (LTE Advanced)
  10. ^ Introduction to LTE-Advanced Rel.11
  11. ^ 3GPP News & Events, Dec.12th, 2012 and Apr.8th, 2013 entries
  12. ^ "NTT DoCoMo Achieves World's First 5 Gbit/s Packet Transmission in 4G Field Experiment". NTT DoCoMo. Archived from the original on 2008-09-25. Retrieved 2008-09-12.
  13. ^ "Agilent Technologies Introduces Industry's First LTE-Advanced Signal Generation, Analysis Solutions". Agilent.
  14. ^ "Ericsson demonstrates LTE Advanced in Sweden". Telecompaper. 2011-06-28. Retrieved 2014-08-13.
  15. ^ "Touch, Huawei trial 250Mbps LTE FDD 800MHz/1800MHz carrier aggregation". TeleGeography. 2013-04-08. Retrieved 2014-08-24.
  16. ^ "Vodafone shows off next-gen mobile broadband". NZ Herald. 2013-05-24.
  17. ^ "A1 TELEKOM AUSTRIA DEMOS 580MBPS LTE-A SPEEDS WITH ERICSSON, NSN HARDWARE". Mobile Europe. 2013-06-06. Retrieved 2014-04-30.
  18. ^ "Turkish delight? Turkcell unveils 900Mbps transmission speeds in LTE-A trial". TeleGeography. 2013-08-02. Retrieved 2014-11-14.
  19. ^ "World's first commercial LTE-Advanced call on 1800MHz and 900MHz". Ericsson. 2013-08-12. Retrieved 2014-04-30.
  20. ^ J.M. Tuazon (21 August 2013). "200MBPS IN DAVAO - Smart tests LTE-Advanced system down south". Interaksyon. Retrieved 21 August 2013.
  21. ^ "Softbank's trial LTE-A in 3.5GHz band achieves 770Mbps". TeleGeography. 2013-09-13. Retrieved 2014-08-13.
  22. ^ "beCloud to test LTE-A". TeleGeography. 2013-10-10. Retrieved 2014-08-13.
  23. ^ "SFR completes 'first' LTE Advanced trials in France". FierceWirelessEurope. 2013-10-18. Retrieved 2014-04-30.
  24. ^ "EE launches 'world's fastest' LTE-A network in London". Telecoms.com. 2013-11-05. Retrieved 2013-12-27.
  25. ^ "Now available at Telefónica: The fastest LTE radio cell in Germany and mobile VoLTE in live network". Telefónica. 2013-11-14. Retrieved 2014-04-30.
  26. ^ "[넓고 빠른 광대역 LTE-A] #1. 3배 빠른 광대역 LTE-A 시대가 열린다!" (in Korean). SK Telecom. 2013-11-28. Retrieved 2014-05-16.
  27. ^ "Vodafone zeigt in Dresden das schnellste Mobilfunknetz der Republik" (in German). Vodafone. 2013-11-15. Retrieved 2014-04-30.
  28. ^ "Telstra hits 300 Mbps in LTE-A trial". Computerworld. 2013-12-06. Retrieved 2014-03-24.
  29. ^ "Optus tests TD-LTE carrier aggregation in Melbourne". iTnews. 2013-12-19. Retrieved 2014-03-29.
  30. ^ "Entel Chile carries out first LTE-A trial". BNAmericas. 2015-09-22. Retrieved 2018-04-10.
  31. ^ "Claro faz primeiro teste externo com LTE Advanced na faixa de 700 MHZ". Telesintese. 2015-12-15. Retrieved 2016-03-29.
  32. ^ "AIS launches the world's first 4.5G network in Thailand". 2016-03-24. Retrieved 2017-12-26.
  33. ^ "Take tour on the new AIS Next-G ready network" (in Thai). Retrieved 2017-12-27.
  34. ^ "MagtiCom launches LTE-Advanced network in Georgia". www.ucom.am. Retrieved 2016-06-06.
  35. ^ "Ucom Deployed Ericsson's Latest 4G+ Technology for the First Time in Armenia". www.ucom.am. Retrieved 2017-02-06.
  36. ^ "Altel: LTE-Advanced (4G+) Technology for the First Time in Kazakhstan". dknews.kz.
  37. ^ "By sounding off the Baltic Drummers' Summit, Bite unveils the first 4.5G network in Latvia with power" (in Latvian). Retrieved 2017-09-18.
  38. ^ "Wi-tribe Becomes Pakistan's First Operator to Cross 200Mbps Internet Speeds". 2017-08-28. Retrieved 2017-10-11.
  39. ^ "Llega a México la GigaRed 4.5G de Telcel".

External links[edit]

Resources (white papers, technical papers, application notes)[edit]

Internet of Things (IoT)

Drawing representing the Internet of things (IoT).

The Internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect, collect and exchange data.[1][2][3][4]

IoT involves extending Internet connectivity beyond standard devices, such as desktops, laptops, smartphones and tablets, to any range of traditionally dumb or non-internet-enabled physical devices and everyday objects. Embedded with technology, these devices can communicate and interact over the Internet, and they can be remotely monitored and controlled.

History[edit]

The definition of the Internet of things has evolved due to convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems.[5] Traditional fields of embedded systems, wireless sensor networks, control systems, automation (including home and building automation), and others all contribute to enabling the Internet of things.[6]

The concept of a network of smart devices was discussed as early as 1982, with a modified Coke machine at Carnegie Mellon University becoming the first Internet-connected appliance,[7] able to report its inventory and whether newly loaded drinks were cold.[8] Mark Weiser's 1991 paper on ubiquitous computing, "The Computer of the 21st Century", as well as academic venues such as UbiComp and PerCom produced the contemporary vision of IoT.[9][10] In 1994, Reza Raji described the concept in IEEE Spectrum as "[moving] small packets of data to a large set of nodes, so as to integrate and automate everything from home appliances to entire factories".[11] Between 1993 and 1997, several companies proposed solutions like Microsoft's at Work or Novell's NEST. The field gained momentum when Bill Joy envisioned Device to Device (D2D) communication as a part of his "Six Webs" framework, presented at the World Economic Forum at Davos in 1999.[12]

The term "Internet of things" was likely coined by Kevin Ashton of Procter & Gamble, later MIT's Auto-ID Center, in 1999,[13] though he prefers the phrase "Internet for things".[14] At that point, he viewed Radio-frequency identification (RFID) as essential to the Internet of things,[15] which would allow computers to manage all individual things.[16][17][18]

A research article mentioning the Internet of things was submitted to the conference for Nordic Researchers in Logistics, Norway, in June 2002,[19] which was preceded by an article published in Finnish in January 2002.[20] The implementation described there was developed by Kary Främling and his team at Helsinki University of Technology and more closely matches the modern one, i.e. an information system infrastructure for implementing smart, connected objects.[21]

Defining the Internet of things as "simply the point in time when more 'things or objects' were connected to the Internet than people", Cisco Systems estimated that IoT was "born" between 2008 and 2009, with the things/people ratio growing from 0.08 in 2003 to 1.84 in 2010.[22]

Applications[edit]

A Nest learning thermostat reporting on energy usage and local weather.

The extensive set of applications for IoT devices[23] is often divided into consumer, commercial, industrial, and infrastructure spaces.[24][25]

Consumer applications[edit]

A growing portion of IoT devices are created for consumer use, including connected vehicles, home automation, wearable technology, connected health, and appliances with remote monitoring capabilities.[26]

Smart home[edit]

IoT devices are a part of the larger concept of home automation, which can include lighting, heating and air conditioning, media and security systems.[27][28] Long term benefits could include energy savings by automatically ensuring lights and electronics are turned off.

A smart home or automated home could be based on a platform or hubs that control smart devices and appliances.[29] For instance, using Apple's HomeKit, manufacturers can get their home products and accessories be controlled by an application in iOS devices such as the iPhone and the Apple Watch.[30][31] This could be a dedicated app or iOS native applications such as Siri.[32] This can be demonstrated in the case of Lenovo's Smart Home Essentials, which is a line of smart home devices that are controlled through Apple's Home app or Siri without the need for a Wi-Fi bridge.[32] There are also dedicated smart home hubs that are offered as standalone platforms to connect different smart home products and these include the Amazon Echo, Apple's HomePod, and Samsung's SmartThings Hub.[33]

Elder care[edit]

One key application of smart home is to provide assistance for those with disabilities and elderly individuals. These home systems use assistive technology to accommodate an owner's specific disabilities.[34] Voice control can assist users with sight and mobility limitations while alert systems can be connected directly to cochlear implants worn by hearing impaired users.[35] They can also be equipped with additional safety features. These features can include sensors that monitor for medical emergencies such as falls or seizures.[36] Smart home technology applied in this way can provide users with more freedom and a higher quality of life.[37]

The term "Enterprise IoT" refers to devices used in business and corporate settings. By 2019, it is estimated that EIoT will account for 9.1 billion devices.[24]

Commercial applications[edit]

Medical and healthcare[edit]

The Internet of Medical Things (also called the internet of health things) is an application of the IoT for medical and health related purposes, data collection and analysis for research, and monitoring.[38][39][40][41][42] This ‘Smart Healthcare’,[43] as it can also be called, led to the creation of a digitized healthcare system, connecting available medical resources and healthcare services.[44]

IoT devices can be used to enable remote health monitoring and emergency notification systems. These health monitoring devices can range from blood pressure and heart rate monitors to advanced devices capable of monitoring specialized implants, such as pacemakers, Fitbit electronic wristbands, or advanced hearing aids.[45] Some hospitals have begun implementing "smart beds" that can detect when they are occupied and when a patient is attempting to get up. It can also adjust itself to ensure appropriate pressure and support is applied to the patient without the manual interaction of nurses.[38] A 2015 Goldman Sachs report indicated that healthcare IoT devices "can save the United States more than $300 billion in annual healthcare expenditures by increasing revenue and decreasing cost."[46][47] Moreover, the use of mobile devices to support medical follow-up led to the creation of ‘m-health’, used “to analyze, capture, transmit and store health statistics from multiple resources, including sensors and other biomedical acquisition systems”.[48]

Specialized sensors can also be equipped within living spaces to monitor the health and general well-being of senior citizens, while also ensuring that proper treatment is being administered and assisting people regain lost mobility via therapy as well.[49] These sensors create a network of intelligent sensors that are able to collect, process, transfer and analyse valuable information in different environments, such as connecting in-home monitoring devices to hospital-based systems.[50] Other consumer devices to encourage healthy living, such as connected scales or wearable heart monitors, are also a possibility with the IoT.[51] End-to-end health monitoring IoT platforms are also available for antenatal and chronic patients, helping one manage health vitals and recurring medication requirements.[52]

As of 2018 IoMT was not only being applied in the clinical laboratory industry,[40] but also in the healthcare and health insurance industries. IoMT in the healthcare industry is now permitting doctors, patients and others involved (i.e. guardians of patients, nurses, families, etc.) to be part of a system, where patient records are saved in a database, allowing doctors and the rest of the medical staff to have access to the patient’s information.[44] Moreover, IoT-based systems are patient-centered, which involves being flexible to the patient’s medical conditions.[44] IoMT in the insurance industry provides access to better and new types of dynamic information. This includes sensor-based solutions such as biosensors, wearables, connected health devices and mobile apps to track customer behaviour. This can lead to more accurate underwriting and new pricing models.[53]

Transportation[edit]

Digital variable speed-limit sign.

The IoT can assist in the integration of communications, control, and information processing across various transportation systems. Application of the IoT extends to all aspects of transportation systems (i.e. the vehicle,[54] the infrastructure, and the driver or user). Dynamic interaction between these components of a transport system enables inter and intra vehicular communication,[55] smart traffic control, smart parking, electronic toll collection systems, logistic and fleet management, vehicle control, and safety and road assistance.[45][56] In Logistics and Fleet Management for example, The IoT platform can continuously monitor the location and conditions of cargo and assets via wireless sensors and send specific alerts when management exceptions occur (delays, damages, thefts, etc.). If combined with Machine Learning then it also helps in reducing traffic accidents by introducing drowsiness alerts to drivers and providing self driven cars too.

Building and home automation[edit]

IoT devices can be used to monitor and control the mechanical, electrical and electronic systems used in various types of buildings (e.g., public and private, industrial, institutions, or residential)[45] in home automation and building automation systems. In this context, three main areas are being covered in literature:[57]

  • The integration of the Internet with building energy management systems in order to create energy efficient and IOT driven “smart buildings”.[57]
  • The possible means of real-time monitoring for reducing energy consumption[58] and monitoring occupant behaviors.[57]
  • The integration of smart devices in the built environment and how they might to know who to be used in future applications.[57]

Industrial applications[edit]

Manufacturing[edit]

The IoT can realize the seamless integration of various manufacturing devices equipped with sensing, identification, processing, communication, actuation, and networking capabilities. Based on such a highly integrated smart cyberphysical space, it opens the door to create whole new business and market opportunities for manufacturing.[59] Network control and management of manufacturing equipment, asset and situation management, or manufacturing process control bring the IoT within the realm of industrial applications and smart manufacturing as well.[60] The IoT intelligent systems enable rapid manufacturing of new products, dynamic response to product demands, and real-time optimization of manufacturing production and supply chain networks, by networking machinery, sensors and control systems together.[45]

Digital control systems to automate process controls, operator tools and service information systems to optimize plant safety and security are within the purview of the IoT.[61] But it also extends itself to asset management via predictive maintenance, statistical evaluation, and measurements to maximize reliability.[62] Smart industrial management systems can also be integrated with the Smart Grid, thereby enabling real-time energy optimization. Measurements, automated controls, plant optimization, health and safety management, and other functions are provided by a large number of networked sensors.[45]

The term industrial Internet of things (IIoT) is often encountered in the manufacturing industries, referring to the industrial subset of the IoT. IIoT in manufacturing could generate so much business value that it will eventually lead to the fourth industrial revolution, so the so-called Industry 4.0. It is estimated that in the future, successful companies will be able to increase their revenue through Internet of things by creating new business models and improve productivity, exploit analytics for innovation, and transform workforce.[63] The potential of growth by implementing IIoT may generate $12 trillion of global GDP by 2030.[63]

Design architecture of cyber-physical systems-enabled manufacturing system[64]

While connectivity and data acquisition are imperative for IIoT, they should not be the purpose, rather the foundation and path to something bigger. Among all the technologies, predictive maintenance is probably a relatively "easier win" since it is applicable to existing assets and management systems. The objective of intelligent maintenance systems is to reduce unexpected downtime and increase productivity. And to realize that alone would generate around up to 30% over the total maintenance costs.[63] Industrial big data analytics will play a vital role in manufacturing asset predictive maintenance, although that is not the only capability of industrial big data.[65][66] Cyber-physical systems (CPS) is the core technology of industrial big data and it will be an interface between human and the cyber world. Cyber-physical systems can be designed by following the 5C (connection, conversion, cyber, cognition, configuration) architecture,[64] and it will transform the collected data into actionable information, and eventually interfere with the physical assets to optimize processes.

An IoT-enabled intelligent system of such cases was proposed in 2001 and later demonstrated in 2014 by the National Science Foundation Industry/University Collaborative Research Center for Intelligent Maintenance Systems (IMS) at the University of Cincinnati on a bandsaw machine in IMTS 2014 in Chicago.[67][68][69] Bandsaw machines are not necessarily expensive, but the bandsaw belt expenses are enormous since they degrade much faster. However, without sensing and intelligent analytics, it can be only determined by experience when the band saw belt will actually break. The developed prognostics system will be able to recognize and monitor the degradation of band saw belts even if the condition is changing, advising users when is the best time to replace the belt. This will significantly improve user experience and operator safety and ultimately save on costs.[69]

Agriculture[edit]

There are numerous IoT applications in farming[70] such as collecting data on temperature, rainfall, humidity, wind speed, pest infestation, and soil content. This data can be used to automate farming techniques, take informed decisions to improve quality and quantity, minimize risk and waste, and reduce effort required to manage crops. For example, farmers can now monitor soil temperature and moisture from afar, and even apply IoT-acquired data to precision fertilization programs.[71]

In August 2018, Toyota Tsusho began a partnership with Microsoft to create fish farming tools using the Microsoft Azure application suite for IoT technologies related to water management. Developed in part by researchers from Kindai University, the water pump mechanisms use artificial intelligence to count the number of fish on a conveyor belt, analyze the number of fish, and deduce the effectiveness of water flow from the data the fish provide. The specific computer programs used in the process fall under the Azure Machine Learning and the Azure IoT Hub platforms.[72]

Infrastructure applications[edit]

Monitoring and controlling operations of sustainable urban and rural infrastructures like bridges, railway tracks and on- and offshore wind-farms is a key application of the IoT.[61] The IoT infrastructure can be used for monitoring any events or changes in structural conditions that can compromise safety and increase risk. IoT can benefit the construction industry by cost saving, time reduction, better quality workday, paperless workflow and increase in productivity. It can help in taking faster decisions and save money with Real-Time Data Analytics. It can also be used for scheduling repair and maintenance activities in an efficient manner, by coordinating tasks between different service providers and users of these facilities.[45] IoT devices can also be used to control critical infrastructure like bridges to provide access to ships. Usage of IoT devices for monitoring and operating infrastructure is likely to improve incident management and emergency response coordination, and quality of service, up-times and reduce costs of operation in all infrastructure related areas.[73] Even areas such as waste management can benefit[74] from automation and optimization that could be brought in by the IoT.[75]

Metropolitan scale deployments[edit]

There are several planned or ongoing large-scale deployments of the IoT, to enable better management of cities and systems. For example, Songdo, South Korea, the first of its kind fully equipped and wired smart city, is gradually being built, with approximately 70 percent of the business district completed as of June 2018. Much of the city is planned to be wired and automated, with little or no human intervention.[76]

Another application is a currently undergoing project in Santander, Spain. For this deployment, two approaches have been adopted. This city of 180,000 inhabitants has already seen 18,000 downloads of its city smartphone app. The app is connected to 10,000 sensors that enable services like parking search, environmental monitoring, digital city agenda, and more. City context information is used in this deployment so as to benefit merchants through a spark deals mechanism based on city behavior that aims at maximizing the impact of each notification.[77]

Other examples of large-scale deployments underway include the Sino-Singapore Guangzhou Knowledge City;[78] work on improving air and water quality, reducing noise pollution, and increasing transportation efficiency in San Jose, California;[79] and smart traffic management in western Singapore.[80] French company, Sigfox, commenced building an ultra-narrowband wireless data network in the San Francisco Bay Area in 2014, the first business to achieve such a deployment in the U.S.[81][82] It subsequently announced it would set up a total of 4000 base stations to cover a total of 30 cities in the U.S. by the end of 2016, making it the largest IoT network coverage provider in the country thus far.[83][84]

Another example of a large deployment is the one completed by New York Waterways in New York City to connect all the city's vessels and be able to monitor them live 24/7. The network was designed and engineered by Fluidmesh Networks, a Chicago-based company developing wireless networks for critical applications. The NYWW network is currently providing coverage on the Hudson River, East River, and Upper New York Bay. With the wireless network in place, NY Waterway is able to take control of its fleet and passengers in a way that was not previously possible. New applications can include security, energy and fleet management, digital signage, public Wi-Fi, paperless ticketing and others.[85]

Energy management[edit]

Significant numbers of energy-consuming devices (e.g. switches, power outlets, bulbs, televisions, etc.) already integrate Internet connectivity, which can allow them to communicate with utilities to balance power generation and energy usage[86] and optimize energy consumption as a whole.[45] These devices allow for remote control by users, or central management via a cloud-based interface, and enable functions like scheduling (e.g., remotely powering on or off heating systems, controlling ovens, changing lighting conditions etc.).[45] The smart grid is a utility-side IoT application; systems gather and act on energy and power-related information to improve the efficiency of the production and distribution of electricity.[86] Using advanced metering infrastructure (AMI) Internet-connected devices, electric utilities not only collect data from end-users, but also manage distribution automation devices like transformers.[45]

Environmental monitoring[edit]

Environmental monitoring applications of the IoT typically use sensors to assist in environmental protection[87] by monitoring air or water quality,[88] atmospheric or soil conditions,[89] and can even include areas like monitoring the movements of wildlife and their habitats.[90] Development of resource-constrained devices connected to the Internet also means that other applications like earthquake or tsunami early-warning systems can also be used by emergency services to provide more effective aid. IoT devices in this application typically span a large geographic area and can also be mobile.[45] It has been argued that the standardization IoT brings to wireless sensing will revolutionize this area.[91]

Trends and characteristics[edit]

Technology roadmap: Internet of things.

The IoT's major significant trend in recent years is the explosive growth of devices connected and controlled by the Internet.[92] The wide range of applications for IoT technology mean that the specifics can be very different from one device to the next but there are basic characteristics shared by most.

IoT creates opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions.[93][94][95][96]

The number of IoT devices increased 31% year-over-year to 8.4 billion in the year 2017[97] and it is estimated that there will be 30 billion devices by 2020.[98] The global market value of IoT is projected to reach $7.1 trillion by 2020.[99]

Intelligence[edit]

Ambient intelligence and autonomous control are not part of the original concept of the Internet of things. Ambient intelligence and autonomous control do not necessarily require Internet structures, either. However, there is a shift in research (by companies such as Intel) to integrate the concepts of IoT and autonomous control, with initial outcomes towards this direction considering objects as the driving force for autonomous IoT.[100]

In the future, the Internet of Things may be a non-deterministic and open network in which auto-organized or intelligent entities (web services, SOA components) and virtual objects (avatars) will be interoperable and able to act independently (pursuing their own objectives or shared ones) depending on the context, circumstances or environments. Autonomous behavior through the collection and reasoning of context information as well as the object's ability to detect changes in the environment (faults affecting sensors) and introduce suitable mitigation measures constitutes a major research trend,[101] clearly needed to provide credibility to the IoT technology. Modern IoT products and solutions in the marketplace use a variety of different technologies to support such context-aware automation, but more sophisticated forms of intelligence are requested to permit sensor units and intelligent cyber-physical systems to be deployed in real environments.[102]

Architecture[edit]

IIoT system architecture,[103] in its simplistic view, consists of three tiers: Tier 1: devices, Tier 2: the Edge Gateway, and Tier 3: the cloud

Tier 1 of the IIoT architecture consists of networked things, typically sensors and actuators, from the IIoT equipment, which use protocols such as Modbus, Zigbee, or proprietary protocols, to connect to an Edge Gateway. Tier 2 includes sensor data aggregation systems called Edge Gateways that provide functionality, such as pre-processing of the data, securing connectivity to cloud, using systems such as WebSockets, the event hub, and, even in some cases, edge analytics or fog computing. Tier 3 includes the cloud application built for IIoT using the microservices architecture, which are usually polyglot and inherently secure in nature using HTTPS/OAuth. Tier 3 also includes storage of sensor data using various database systems, such as time series databases or asset stores using backend data storage systems such as Cassandra or Postgres. In addition to the data storage, we analyze the data using various analytics, predictive or threshold-based or regression-based, to get more insights on the IIoT equipment.

Building on the Internet of things, the web of things is an architecture for the application layer of the Internet of things looking at the convergence of data from IoT devices into Web applications to create innovative use-cases. In order to program and control the flow of information in the Internet of things, a predicted architectural direction is being called BPM Everywhere which is a blending of traditional process management with process mining and special capabilities to automate the control of large numbers of coordinated devices.[citation needed]

Network architecture[edit]

The Internet of things requires huge scalability in the network space to handle the surge of devices.[104] IETF 6LoWPAN would be used to connect devices to IP networks. With billions of devices[105] being added to the Internet space, IPv6 will play a major role in handling the network layer scalability. IETF's Constrained Application Protocol, ZeroMQ, and MQTT would provide lightweight data transport.

Fog computing is a viable alternative to prevent such large burst of data flow through Internet.[106] The edge devices' computation power can be used to analyse and process data, thus providing easy real time scalability.[citation needed]

Complexity[edit]

In semi-open or closed loops (i.e. value chains, whenever a global finality can be settled) IoT will often be considered and studied as a complex system[107] due to the huge number of different links, interactions between autonomous actors, and its capacity to integrate new actors. At the overall stage (full open loop) it will likely be seen as a chaotic environment (since systems always have finality). As a practical approach, not all elements in the Internet of things run in a global, public space. Subsystems are often implemented to mitigate the risks of privacy, control and reliability. For example, domestic robotics (domotics) running inside a smart home might only share data within and be available via a local network.[108] Managing and controlling high dynamic ad hoc IoT things/devices network is a tough task with the traditional networks architecture, Software Defined Networking (SDN) provides the agile dynamic solution that can cope with the special requirements of the diversity of innovative IoT applications.[109]

Size considerations[edit]

The Internet of things would encode 50 to 100 trillion objects, and be able to follow the movement of those objects. Human beings in surveyed urban environments are each surrounded by 1000 to 5000 trackable objects.[110] In 2015 there were already 83 million smart devices in people`s homes. This number is about to grow up to 193 million devices in 2020 and will for sure go on growing in the near future.[28]

The figure of online capable devices grew 31% from 2016 to 8.4 billion in 2017.[97]

Space considerations[edit]

In the Internet of things, the precise geographic location of a thing—and also the precise geographic dimensions of a thing—will be critical.[111] Therefore, facts about a thing, such as its location in time and space, have been less critical to track because the person processing the information can decide whether or not that information was important to the action being taken, and if so, add the missing information (or decide to not take the action). (Note that some things in the Internet of things will be sensors, and sensor location is usually important.[112]) The GeoWeb and Digital Earth are promising applications that become possible when things can become organized and connected by location. However, the challenges that remain include the constraints of variable spatial scales, the need to handle massive amounts of data, and an indexing for fast search and neighbor operations. In the Internet of things, if things are able to take actions on their own initiative, this human-centric mediation role is eliminated. Thus, the time-space context that we as humans take for granted must be given a central role in this information ecosystem. Just as standards play a key role in the Internet and the Web, geospatial standards will play a key role in the Internet of things.[113][114]

A solution to "basket of remotes"[edit]

Many IoT devices have a potential to take a piece of this market. Jean-Louis Gassée (Apple initial alumni team, and BeOS co-founder) has addressed this topic in an article on Monday Note,[115] where he predicts that the most likely problem will be what he calls the "basket of remotes" problem, where we'll have hundreds of applications to interface with hundreds of devices that don't share protocols for speaking with one another.[115] For improved user interaction, some technology leaders are joining forces to create standards for communication between devices to solve this problem. Others are turning to the concept of predictive interaction of devices, "where collected data is used to predict and trigger actions on the specific devices" while making them work together.[116]

Enabling technologies for IoT[edit]

There are many technologies that enable IoT. Crucial to the field is the network used to communicate between devices of an IoT installation, a role that several wireless or wired technologies may fulfill:[117][118][119]

Addressability[edit]

The original idea of the Auto-ID Center is based on RFID-tags and unique identification through the Electronic Product Code, however, this has evolved into objects having an IP address or URI.[120] An alternative view, from the world of the Semantic Web[121] focuses instead on making all things (not just those electronic, smart, or RFID-enabled) addressable by the existing naming protocols, such as URI. The objects themselves do not converse, but they may now be referred to by other agents, such as powerful centralized servers acting for their human owners.[122] Integration with the Internet implies that devices will use an IP address as a unique identifier. Due to the limited address space of IPv4 (which allows for 4.3 billion unique addresses), objects in the IoT will have to use the next generation of the Internet protocol (IPv6) to scale to the extremely large address space required.[123][124][125] Internet-of-things devices additionally will benefit from the stateless address auto-configuration present in IPv6,[126] as it reduces the configuration overhead on the hosts,[124] and the IETF 6LoWPAN header compression. To a large extent, the future of the Internet of things will not be possible without the support of IPv6; and consequently, the global adoption of IPv6 in the coming years will be critical for the successful development of the IoT in the future.[125]

Short-range wireless[edit]

Medium-range wireless[edit]

  • LTE-Advanced – High-speed communication specification for mobile networks. Provides enhancements to the LTE standard with extended coverage, higher throughput, and lower latency.

Long-range wireless[edit]


Wired[edit]

Standards and standards organizations[edit]

This is a list of technical standards for the IoT, most of which are open standards, and the standards organizations that aspire to successfully setting them.[127][128]

Short name Long name Standards under development Other notes
Auto-ID Labs Auto Identification Center Networked RFID (radiofrequency identification) and emerging sensing technologies
EPCglobal Electronic Product code Technology Standards for adoption of EPC (Electronic Product Code) technology
FDA U.S. Food and Drug Administration UDI (Unique Device Identification) system for unique identifiers for medical devices
GS1 Standards for UIDs (unique identifiers) and RFID of fast-moving consumer goods (consumer packaged goods), health care supplies, and other things Parent organization comprises member organizations such as GS1 US
IEEE Institute of Electrical and Electronics Engineers Underlying communication technology standards such as IEEE 802.15.4
IETF Internet Engineering Task Force Standards that comprise TCP/IP (the Internet protocol suite)
MTConnect Institute MTConnect is a manufacturing industry standard for data exchange with machine tools and related industrial equipment. It is important to the IIoT subset of the IoT.
O-DF Open Data Format O-DF is a standard published by the Internet of Things Work Group of The Open Group in 2014, which specifies a generic information model structure that is meant to be applicable for describing any "Thing", as well as for publishing, updating and querying information when used together with O-MI (Open Messaging Interface).
O-MI Open Messaging Interface O-MI is a standard published by the Internet of Things Work Group of The Open Group in 2014, which specifies a limited set of key operations needed in IoT systems, notably different kinds of subscription mechanisms based on the Observer pattern.
OCF Open Connectivity Foundation Standards for simple devices using CoAP (Constrained Application Protocol) OCF (Open Connectivity Foundation) supersedes OIC (Open Interconnect Consortium)
OMA Open Mobile Alliance OMA DM and OMA LWM2M for IoT device management, as well as GotAPI, which provides a secure framework for IoT applications
XSF XMPP Standards Foundation Protocol extensions of XMPP (Extensible Messaging and Presence Protocol), the open standard of instant messaging

Politics and civic engagement[edit]

Some scholars and activists argue that the IoT can be used to create new models of civic engagement if device networks can be open to user control and inter-operable platforms. Philip N. Howard, a professor and author, writes that political life in both democracies and authoritarian regimes will be shaped by the way the IoT will be used for civic engagement. For that to happen, he argues that any connected device should be able to divulge a list of the "ultimate beneficiaries" of its sensor data and that individual citizens should be able to add new organizations to the beneficiary list. In addition, he argues that civil society groups need to start developing their IoT strategy for making use of data and engaging with the public.[129]

Government regulation on IoT[edit]

One of the key drivers of the IoT is data. The success of the idea of connecting devices to make them more efficient is dependent upon access to and storage & processing of data. For this purpose, companies working on IoT collect data from multiple sources and store it in their cloud network for further processing. This leaves the door wide open for privacy and security dangers and single point vulnerability of multiple systems.[130] The other issues pertain to consumer choice and ownership of data[131] and how it is used. Though still in their infancy, regulations and governance regarding these issues of privacy, security, and data ownership continue to develop.[132][133][134] IoT regulation depends on the country. Some examples of legislation that is relevant to privacy and data collection are: the US Privacy Act of 1974, OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data of 1980, and the EU Directive 95/46/EC of 1995.[135]

Current regulatory environment:

A report published by the Federal Trade Commission (FTC) in January 2015 made the following three recommendations:[136]

  • Data security – At the time of designing IoT companies should ensure that data collection, storage and processing would be secure at all times. Companies should adopt a “defence in depth” approach and encrypt data at each stage.[137]
  • Data consent – users should have a choice as to what data they share with IoT companies and the users must be informed if their data gets exposed.
  • Data minimization – IoT companies should collect only the data they need and retain the collected information only for a limited time.

However, the FTC stopped at just making recommendations for now. According to an FTC analysis, the existing framework, consisting of the FTC Act, the Fair Credit Reporting Act, and the Children's Online Privacy Protection Act, along with developing consumer education and business guidance, participation in multi-stakeholder efforts and advocacy to other agencies at the federal, state and local level, is sufficient to protect consumer rights.[138]

A resolution passed by the Senate in March 2015, is already being considered by the Congress.[139] This resolution recognized the need for formulating a National Policy on IoT and the matter of privacy, security and spectrum. Furthermore, to provide an impetus to the IoT ecosystem, in March 2016, a bipartisan group of four Senators proposed a bill, The Developing Innovation and Growing the Internet of Things (DIGIT) Act, to direct the Federal Communications Commission to assess the need for more spectrum to connect IoT devices.

Several standards for the IoT industry are actually being established relating to automobiles because most concerns arising from use of connected cars apply to healthcare devices as well. In fact, the National Highway Traffic Safety Administration (NHTSA) is preparing cybersecurity guidelines and a database of best practices to make automotive computer systems more secure.[140]

A recent report from the World Bank examines the challenges and opportunities in government adoption of IoT.[141] These include -

  • Still early days for IoT in government 
  • Underdeveloped policy and regulatory frameworks 
  • Unclear business models, despite strong value proposition 
  • Clear institutional and capacity gap in government AND the private sector 
  • Inconsistent data valuation and management 
  • Infrastructure a major barrier 
  • Government as an enabler 
  • Most successful pilots share common characteristics (public-private partnership, local, leadership)

Criticism and controversies[edit]

Platform fragmentation[edit]

IoT suffers from platform fragmentation and lack of technical standards[142][143][144][145][146][147][148] a situation where the variety of IoT devices, in terms of both hardware variations and differences in the software running on them, makes the task of developing applications that work consistently between different inconsistent technology ecosystems hard.[1] Customers may be hesitant to bet their IoT future on a proprietary software or hardware devices that uses proprietary protocols that may fade or become difficult to customize and interconnect.[2]

IoT's amorphous computing nature is also a problem for security, since patches to bugs found in the core operating system often do not reach users of older and lower-price devices.[149][150][151] One set of researchers say that the failure of vendors to support older devices with patches and updates leaves more than 87% of active Android devices vulnerable.[152][153]

Privacy, autonomy, and control[edit]

Philip N. Howard, a professor and author, writes that the Internet of things offers immense potential for empowering citizens, making government transparent, and broadening information access. Howard cautions, however, that privacy threats are enormous, as is the potential for social control and political manipulation.[154]

Concerns about privacy have led many to consider the possibility that big data infrastructures such as the Internet of things and data mining are inherently incompatible with privacy.[155] Writer Adam Greenfield claims that these technologies are not only an invasion of public space but are also being used to perpetuate normative behavior, citing an instance of billboards with hidden cameras that tracked the demographics of passersby who stopped to read the advertisement.[156]

The Internet of Things Council compared the increased prevalence of digital surveillance due to the Internet of things to the conceptual panopticon described by Jeremy Bentham in the 18th Century.[157] The assertion was defended by the works of French philosophers Michel Foucault and Gilles Deleuze. In Discipline and Punish: The Birth of the Prison Foucault asserts that the panopticon was a central element of the discipline society developed during the Industrial Era.[158] Foucault also argued that the discipline systems established in factories and school reflected Bentham's vision of panopticism.[158] In his 1992 paper "Postscripts on the Societies of Control," Deleuze wrote that the discipline society had transitioned into a control society, with the computer replacing the panopticon as an instrument of discipline and control while still maintaining the qualities similar to that of panopticism.[159]

The privacy of households could be compromised by solely analyzing smart home network traffic patterns without dissecting the contents of encrypted application data, yet a synthetic packet injection scheme can be used to safely overcome such invasion of privacy.[160]

Peter-Paul Verbeek, a professor of philosophy of technology at the University of Twente, Netherlands, writes that technology already influences our moral decision making, which in turn affects human agency, privacy and autonomy. He cautions against viewing technology merely as a human tool and advocates instead to consider it as an active agent.[161]

Justin Brookman, of the Center for Democracy and Technology, expressed concern regarding the impact of IoT on consumer privacy, saying that "There are some people in the commercial space who say, 'Oh, big data — well, let's collect everything, keep it around forever, we'll pay for somebody to think about security later.' The question is whether we want to have some sort of policy framework in place to limit that."[162]

Tim O'Reilly believes that the way companies sell the IoT devices on consumers are misplaced, disputing the notion that the IoT is about gaining efficiency from putting all kinds of devices online and postulating that "IoT is really about human augmentation. The applications are profoundly different when you have sensors and data driving the decision-making."[163]

Editorials at WIRED have also expressed concern, one stating "What you're about to lose is your privacy. Actually, it's worse than that. You aren't just going to lose your privacy, you're going to have to watch the very concept of privacy be rewritten under your nose."[164]

The American Civil Liberties Union (ACLU) expressed concern regarding the ability of IoT to erode people's control over their own lives. The ACLU wrote that "There's simply no way to forecast how these immense powers – disproportionately accumulating in the hands of corporations seeking financial advantage and governments craving ever more control – will be used. Chances are big data and the Internet of things will make it harder for us to control our own lives, as we grow increasingly transparent to powerful corporations and government institutions that are becoming more opaque to us."[165]

In response to rising concerns about privacy and smart technology, in 2007 the British Government stated it would follow formal Privacy by Design principles when implementing their smart metering program. The program would lead to replacement of traditional power meters with smart power meters, which could track and manage energy usage more accurately.[166] However the British Computer Society is doubtful these principles were ever actually implemented.[167] In 2009 the Dutch Parliament rejected a similar smart metering program, basing their decision on privacy concerns. The Dutch program later revised and passed in 2011.[167]

Data storage[edit]

A challenge for producers of IoT applications is to clean, process and interpret the vast amount of data which is gathered by the sensors. There is a solution proposed for the analytics of the information referred to as Wireless Sensor Networks.[168] These networks share data among sensor nodes that are sent to a distributed system for the analytics of the sensory data.[169]

Another challenge is the storage of this bulk data. Depending on the application, there could be high data acquisition requirements, which in turn lead to high storage requirements. Currently the Internet is already responsible for 5% of the total energy generated,[168] and a "daunting challenge to power" IoT devices to collect and even store data still remains.[170]

Security[edit]

Concerns have been raised that the IoT is being developed rapidly without appropriate consideration of the profound security challenges involved[171] and the regulatory changes that might be necessary.[172][173] Most of the technical security concerns are similar to those of conventional servers, workstations and smartphones, but security challenges unique to the IoT continue to develop, including industrial security controls, hybrid systems, IoT-specific business processes, and end nodes.[174]

Security is the biggest concern in adopting Internet of things technology.[175] In particular, as the Internet of things spreads widely, cyber attacks are likely to become an increasingly physical (rather than simply virtual) threat.[176] In a January 2014 article in Forbes, cyber-security columnist Joseph Steinberg listed many Internet-connected appliances that can already "spy on people in their own homes" including televisions, kitchen appliances,[177] cameras, and thermostats.[178] Computer-controlled devices in automobiles such as brakes, engine, locks, hood and trunk releases, horn, heat, and dashboard have been shown to be vulnerable to attackers who have access to the on-board network. In some cases, vehicle computer systems are Internet-connected, allowing them to be exploited remotely.[179] By 2008 security researchers had shown the ability to remotely control pacemakers without authority. Later hackers demonstrated remote control of insulin pumps[180] and implantable cardioverter defibrillators.[181]

The U.S. National Intelligence Council in an unclassified report maintains that it would be hard to deny "access to networks of sensors and remotely-controlled objects by enemies of the United States, criminals, and mischief makers... An open market for aggregated sensor data could serve the interests of commerce and security no less than it helps criminals and spies identify vulnerable targets. Thus, massively parallel sensor fusion may undermine social cohesion, if it proves to be fundamentally incompatible with Fourth-Amendment guarantees against unreasonable search."[182] In general, the intelligence community views the Internet of things as a rich source of data.[183]

In 2016, a distributed denial of service attack powered by Internet of things devices running the Mirai malware took down a DNS provider and major web sites.[184] The Mirai Botnet had infected roughly 65,000 IoT devices within the first 20 hours.[185] Eventually the infections increased to 200,000 to 300,000 infections.[185] Brazil, Columbia and Vietnam made up of 41.5% of the infections.[185] The Mirai Botnet had singled out specific IoT devices that consisted of DVRs, IP cameras, routers and printers.[185] Top vendors that contained the most infected devices were identified as Dahua, Huawei, ZTE, Cisco, ZyXEL and MikroTik.[185] In May 2017, Junade Ali, a Computer Scientist at Cloudflare noted that native DDoS vulnerabilities exist in IoT devices due to a poor implementation of the Publish–subscribe pattern.[186][187] These sorts of attacks have caused security experts to view IoT as a real threat to Internet services.[188]

There have been a range of responses to concerns over security. The Internet of Things Security Foundation (IoTSF) was launched on 23 September 2015 with a mission to secure the Internet of things by promoting knowledge and best practice. Its founding board is made from technology providers and telecommunications companies. In addition, large IT companies are continuously developing innovative solutions to ensure the security for IoT devices. In 2017, Mozilla launched Project Things, which allows to route IoT devices through a safe Web of Things gateway.[189]As per the estimates from KBV Research,[190] the overall IoT security market[191] would grow at 27.9% rate during 2016–2022 as a result of growing infrastructural concerns and diversified usage of Internet of things.[192][193]

Governmental regulation is argued by some to be necessary to secure IoT devices and the wider Internet - as market incentives to secure IoT devices is insufficient.[194][172][173]

Safety[edit]

IoT systems are typically controlled by event-driven smart apps that take as input either sensed data, user inputs, or other external triggers (from the Internet) and command one or more actuators towards providing different forms of automation [195]. Examples of sensors include smoke detectors, motion sensors, and contact sensors. Examples of actuators include smart locks, smart power outlets, and door controls. Popular control platforms on which third-party developers can build smart apps that interact wirelessly with these sensors and actuators include Samsung's SmartThings[196], Apple's HomeKit[197], and Amazon's Alexa[198], among others.

A problem specific to IoT systems is that buggy apps, unforeseen bad app interactions, or device/communication failures, can cause unsafe and dangerous physical states, e.g., "unlock the entrance door when no one is at home" or "turn off the heater when the temperature is below 0 degrees Celcius and people are sleeping at night"[195]. Detecting flaws that lead to such states, requires a holistic view of installed apps, component devices, their configurations, and more importantly, how they interact. Recently, researchers from the University of California Riverside have proposed IotSan, a novel practical system that uses model checking as a building block to reveal "interaction-level" flaws by identifying events that can lead the system to unsafe states[195]. They have evaluated IotSan on the Samsung SmartThings platform. From 76 manually configured systems, IotSan detects 147 vulnerabilities (i.e., violations of safe physical states/properties).

Design[edit]

Given widespread recognition of the evolving nature of the design and management of the Internet of things, sustainable and secure deployment of IoT solutions must design for "anarchic scalability."[199] Application of the concept of anarchic scalability can be extended to physical systems (i.e. controlled real-world objects), by virtue of those systems being designed to account for uncertain management futures. This hard anarchic scalability thus provides a pathway forward to fully realize the potential of Internet-of-things solutions by selectively constraining physical systems to allow for all management regimes without risking physical failure.[199]

Brown University computer scientist Michael Littman has argued that successful execution of the Internet of things requires consideration of the interface's usability as well as the technology itself. These interfaces need to be not only more user-friendly but also better integrated: "If users need to learn different interfaces for their vacuums, their locks, their sprinklers, their lights, and their coffeemakers, it's tough to say that their lives have been made any easier."[200]

Environmental sustainability impact[edit]

A concern regarding Internet-of-things technologies pertains to the environmental impacts of the manufacture, use, and eventual disposal of all these semiconductor-rich devices.[201] Modern electronics are replete with a wide variety of heavy metals and rare-earth metals, as well as highly toxic synthetic chemicals. This makes them extremely difficult to properly recycle. Electronic components are often incinerated or placed in regular landfills. Furthermore, the human and environmental cost of mining the rare-earth metals that are integral to modern electronic components continues to grow. This leads to societal questions concerning the environmental impacts of IoT devices over its lifetime.[202]

Intentional obsolescence of devices[edit]

The Electronic Frontier Foundation has raised concerns that companies can use the technologies necessary to support connected devices to intentionally disable or "brick" their customers' devices via a remote software update or by disabling a service necessary to the operation of the device. In one example, home automation devices sold with the promise of a "Lifetime Subscription" were rendered useless after Nest Labs acquired Revolv and made the decision to shut down the central servers the Revolv devices had used to operate.[203] As Nest is a company owned by Alphabet (Google's parent company), the EFF argues this sets a "terrible precedent for a company with ambitions to sell self-driving cars, medical devices, and other high-end gadgets that may be essential to a person's livelihood or physical safety."[204]

Owners should be free to point their devices to a different server or collaborate on improved software. But such action violates the United States DMCA section 1201, which only has an exemption for "local use". This forces tinkerers who want to keep using their own equipment into a legal grey area. EFF thinks buyers should refuse electronics and software that prioritize the manufacturer's wishes above their own.[204]

Examples of post-sale manipulations include Google Nest Revolv, disabled privacy settings on Android, Sony disabling Linux on PlayStation 3, enforced EULA on Wii U.[204]

Confusing terminology[edit]

Kevin Lonergan at Information Age, a business-technology magazine, has referred to the terms surrounding IoT as a “terminology zoo”.[205] The lack of clear terminology is not “useful from a practical point of view” and a “source of confusion for the end user”.[205] A company operating in the IoT space could be working in anything related to sensor technology, networking, embedded systems, or analytics.[205] According to Lonergan, the term IoT was coined before smart phones, tablets, and devices as we know them today existed, and there is a long list of terms with varying degrees of overlap and technological convergence: Internet of things, Internet of everything (IoE), Internet of Goods (Supply Chain), industrial Internet, pervasive computing, pervasive sensing, ubiquitous computing, cyber-physical systems (CPS), wireless sensor networks (WSN), smart objects, digital twin, cyberobjects or avatars,[107] cooperating objects, machine to machine (M2M), ambient intelligence (AmI), Operational technology (OT), and information technology (IT).[205] Regarding IIoT, an industrial sub-field of IoT, the Industrial Internet Consortium's Vocabulary Task Group has created a "common and reusable vocabulary of terms"[206] to ensure "consistent terminology"[206][207] across publications issued by the Industrial Internet Consortium. IoT One has created an IoT Terms Database including a New Term Alert[208] to be notified when a new term is published. As of March 2017, this database aggregates 711 IoT-related terms, while keeping material "transparent and comprehensive."[209][210]

IoT adoption barriers[edit]

GE Digital CEO William Ruh speaking about GE's attempts to gain a foothold in the market for IoT services at the first IEEE Computer Society TechIgnite conference.

Lack of interoperability and unclear value propositions[edit]

Despite a shared belief in the potential of IoT, industry leaders and consumers are facing barriers to adopt IoT technology more widely. Mike Farley argued in Forbes that while IoT solutions appeal to early adopters, they either lack interoperability or a clear use case for end-users.[211] A study by Ericsson regarding the adoption of IoT among Danish companies suggests that many struggle “to pinpoint exactly where the value of IoT lies for them”.[212]

Privacy and security concerns[edit]

According to a recent study by Noura Aleisa and Karen Renaud at the University of Glasgow, "the Internet of things' potential for major privacy invasion is a concern"[213] with much of research "disproportionally focused on the security concerns of IoT."[213] Among the "proposed solutions in terms of the techniques they deployed and the extent to which they satisfied core privacy principles",[213] only very few turned out to be fully satisfactory. Louis Basenese, investment director at Wall Street Daily, has criticized the industry's lack of attention to security issues:

"Despite high-profile and alarming hacks, device manufacturers remain undeterred, focusing on profitability over security. Consumers need to have ultimate control over collected data, including the option to delete it if they choose...Without privacy assurances, wide-scale consumer adoption simply won't happen."[214]

In a post-Snowden world of global surveillance disclosures, consumers take a more active interest in protecting their privacy and demand IoT devices to be screened for potential security vulnerabilities and privacy violations before purchasing them. According to the 2016 Accenture Digital Consumer Survey, in which 28000 consumers in 28 countries were polled on their use of consumer technology, security “has moved from being a nagging problem to a top barrier as consumers are now choosing to abandon IoT devices and services over security concerns.”[215] The survey revealed that “out of the consumers aware of hacker attacks and owning or planning to own IoT devices in the next five years, 18 percent decided to terminate the use of the services and related services until they get safety guarantees.”[215] This suggests that consumers increasingly perceive privacy risks and security concerns to outweigh the value propositions of IoT devices and opt to postpone planned purchases or service subscriptions.[215]

Traditional governance structures[edit]

Town of Internet of Things in Hangzhou, China

A study issued by Ericsson regarding the adoption of Internet of things among Danish companies identified a "clash between IoT and companies' traditional governance structures, as IoT still presents both uncertainties and a lack of historical precedence."[212] Among the respondents interviewed, 60 percent stated that they "do not believe they have the organizational capabilities, and three of four do not believe they have the processes needed, to capture the IoT opportunity."[212] This has led to a need to understand organizational culture in order to facilitate organizational design processes and to test new innovation management practices. A lack of digital leadership in the age of digital transformation has also stifled innovation and IoT adoption to a degree that many companies, in the face of uncertainty, "were waiting for the market dynamics to play out",[212] or further action in regards to IoT "was pending competitor moves, customer pull, or regulatory requirements."[212] Some of these companies risk being 'kodaked' – "Kodak was a market leader until digital disruption eclipsed film photography with digital photos"[216] – failing to "see the disruptive forces affecting their industry"[217] and "to truly embrace the new business models the disruptive change opens up."[217] Scott Anthony has written in Harvard Business Review that Kodak "created a digital camera, invested in the technology, and even understood that photos would be shared online"[217] but ultimately failed to realize that "online photo sharing was the new business, not just a way to expand the printing business."[217]

Business planning and models[edit]

According to 2018 study, 70–75% of IoT deployments were stuck in the pilot or prototype stage, unable to reach scale due in part to a lack of business planning.[218][page needed]

Studies on IoT literature and projects show a disproportionate prominence of technology in the IoT projects, which are often driven by technological interventions rather than business model innovation.[219][220][improper synthesis?]

See also[edit]

References[edit]

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Bibliography[edit]

External links[edit]

Machine to Machine (M2M)

Machine to machine (commonly abbreviated as M2M) refers to direct communication between devices using any communications channel, including wired and wireless.[1][2] Machine to machine communication can include industrial instrumentation, enabling a sensor or meter to communicate the data it records (such as temperature, inventory level, etc.) to application software that can use it (for example, adjusting an industrial process based on temperature or placing orders to replenish inventory).[3] Such communication was originally accomplished by having a remote network of machines relay information back to a central hub for analysis, which would then be rerouted into a system like a personal computer.[4]

More recent machine to machine communication has changed into a system of networks that transmits data to personal appliances. The expansion of IP networks around the world has made machine to machine communication quicker and easier while using less power.[5] These networks also allow new business opportunities for consumers and suppliers.[6]

History[edit]

Wired communication machines have been using signaling to exchange information since the early 20th century. Machine to machine has taken more sophisticated forms since the advent of computer networking automation[7] and predates cellular communication. It has been utilized in applications such as telemetry, industrial, automation, SCADA.

Machine to machine devices that combined telephony and computing were first conceptualized by Theodore Paraskevakos while working on his Caller ID system in 1968, later patented in the U.S. in 1973. This system, similar but distinct from the panel call indicator of the 1920s and automatic number identification of the 1940s, which communicated telephone numbers to machines, was the predecessor to what is now caller ID, which communicates numbers to people.

The first caller identification receiver
Processing Chips

After several attempts and experiments, he realized that in order for the telephone to be able to read the caller's telephone number, it must possess intelligence so he developed the method in which the caller's number is transmitted to the called receiver's device. His portable transmitter and receiver were reduced to practice in 1971 in a Boeing facility in Huntsville, Alabama, representing the world's first working prototypes of caller identification devices (shown at right). They were installed at Peoples' Telephone Company in Leesburg, Alabama and in Athens, Greece where they were demonstrated to several telephone companies with great success. This method was the basis for modern-day Caller ID technology. He was also the first to introduce the concepts of intelligence, data processing and visual display screens into telephones which gave rise to the smartphone.[8]

In 1977, Paraskevakos started Metretek, Inc. in Melbourne, Florida to conduct commercial automatic meter reading and load management for electrical services which led to the "smart grid" and "smart meter". To achieve mass appeal, Paraskevakos sought to reduce the size of the transmitter and the time of transmission through telephone lines by creating a single chip processing and transmission method. Motorola was contracted in 1978 to develop and produce the single chip, but the chip was too large for Motorola's capabilities at that time. As a result, it became two separate chips (shown at right).

While cellular is becoming more common, many machines still use landlines (POTS, DSL, cable) to connect to the IP network. The cellular M2M communications industry emerged in 1995 when Siemens set up a department inside its mobile phones business unit to develop and launch a GSM data module called "M1"[9] based on the Siemens mobile phone S6 for M2M industrial applications, enabling machines to communicate over wireless networks. In October 2000, the modules department formed a separate business unit inside Siemens called "Wireless Modules" which in June 2008 became a standalone company called Cinterion Wireless Modules. The first M1 module was used for early point of sale (POS) terminals, in vehicle telematics, remote monitoring and tracking and tracing applications. Machine to machine technology was first embraced by early implementers such as GM and Hughes Electronics Corporation who realized the benefits and future potential of the technology. By 1997, machine to machine wireless technology became more prevalent and sophisticated as ruggedized modules were developed and launched for the specific needs of different vertical markets such as automotive telematics.

21st century machine to machine data modules have newer features and capabilities such as onboard global positioning (GPS) technology, flexible land grid array surface mounting, embedded machine to machine optimized smart cards (like phone SIMs) known as MIMs or machine to machine identification modules, and embedded Java, an important enabling technology to accelerate the Internet of things (IOT). Another example of an early use is OnStar's system of communication.[10]

The hardware components of a machine to machine network are manufactured by a few key players. In 1998, Quake Global started designing and manufacturing machine to machine satellite and terrestrial modems.[11] Initially relying heavily on ORBCOMM network for its satellite communication services, Quake Global expanded its telecommunication product offerings by engaging both satellite and terrestrial networks, which gave Quake Global an edge in offering network-neutral[12] products.

In the 2000s[edit]

In 2004, Digi International began producing wireless gateways and routers. Shortly after in 2006, Digi purchased Max Stream, the manufacturer of XBee radios. These hardware components allowed users to connect machines no matter how remote their location. Since then, Digi has partnered with several companies to connect hundreds of thousands of devices around the world.[citation needed]

In 2004, Christopher Lowery, a UK telecoms entrepreneur, founded Wyless Group, one of the first Mobile Virtual Network Operators (MVNO) in the M2M space. Operations began in the UK and Lowery published several patents introducing new features in data protection & management, including Fixed IP Addressing combined with Platform Managed Connectivity over VPNs. The company expanded to the US in 2008 and became T-Mobile's largest partners on both sides of the Atlantic.[citation needed]

In 2006, Machine-to-Machine Intelligence (M2Mi) Corp started work with NASA to develop automated machine to machine intelligence. Automated machine to machine intelligence enables a wide variety of mechanisms including wired or wireless tools, sensors, devices, server computers, robots, spacecraft and grid systems to communicate and exchange information efficiently.[13]

In 2009, AT&T and Jasper Technologies, Inc. entered into an agreement to support the creation of machine to machine devices jointly. They have stated that they will be trying to drive further connectivity between consumer electronics and machine to machine wireless networks, which would create a boost in speed and overall power of such devices.[14] 2009 also saw the introduction of real-time management of GSM and CDMA network services for machine to machine applications with the launch of the PRiSMPro™ Platform from machine to machine network provider KORE Telematics. The platform focused on making multi-network management a critical component for efficiency improvements and cost-savings in machine to machine device and network usage.[15]

Also in 2009, Wyless Group introduced PORTHOS™, its multi-operator, multi-application, device agnostic Open Data Management Platform. The company introduced a new industry definition, Global Network Enabler, comprising customer-facing platform management of networks, devices and applications.[citation needed]

Also in 2009, the Norwegian incumbent Telenor concluded ten years of machine to machine research by setting up two entities serving the upper (services) and lower (connectivity) parts of the value-chain. Telenor Connexion[16] in Sweden draws on Vodafone's former research capabilities in subsidiary Europolitan and is in Europe's market for services across such typical markets as logistics, fleet management, car safety, healthcare, and smart metering of electricity consumption.[17] Telenor Objects has a similar role supplying connectivity to machine to machine networks across Europe. Telefonica set up a business branch of Telefónica Digital specialized in machine to machine with global solutions for managed connectivity, transport and utilities and sustainability[18] In the UK, Business MVNO Abica, commenced trials with Telehealth and Telecare applications which required secure data transit via Private APN and HSPA+/4G LTE connectivity with static IP address.

In the 2010s[edit]

In early 2010 in the U.S., AT&T, KPN, Rogers, Telcel / America Movil and Jasper Technologies, Inc. began to work together in the creation of a machine to machine site, which will serve as a hub for developers in the field of machine to machine communication electronics.[19] In February 2010, Vodafone, Verizon Wireless and nPhase (a joint partnership of Qualcomm and Verizon) announced their strategic alliance to provide global machine to machine solutions that would offer their customers an easy way to roll out machine to machine solutions across Europe and the US.[20] In March 2010, Sprint and Axeda Corporation announced their strategic alliance for global M2M solutions.[21] In January 2011, Aeris Communications, Inc. announced that it is providing machine to machine telematics services for Hyundai Motor Corporation.[22] Partnerships like these make it easier, faster and more cost-efficient for businesses to use machine to machine. In June 2010, mobile messaging operator Tyntec announced the availability of its high-reliability SMS services for M2M applications.

In March 2011, machine to machine network service provider KORE Wireless teamed with Vodafone Group and Iridium Communications Inc., respectively, to make KORE Global Connect network services available via cellular and satellite connectivity in more than 180 countries, with a single point for billing, support, logistics and relationship management. Later that year, KORE acquired Australia-based Mach Communications Pty Ltd. in response to increased M2M demand within Asia-Pacific markets.[23][24]

In April 2011, Ericsson acquired Telenor Connexion's machine to machine platform, in an effort to get more technology and know-how in the growing sector.[25]

In August 2011, Ericsson announced that they have successfully completed the asset purchase agreement to acquire Telenor Connexion's (machine to machine) technology platform.[26]

Cloud connectivity is becoming a significant piece of the machine to machine solution as cellular and wireless connection speeds increase. Machine to machine solutions providers now offer platforms as a service (PaaS), which simplify machine networks by allowing users to manage deployments remotely. Device Cloud by Etherios is a PaaS that can integrate into the Salesforce.com platform and offers API's that can be used to develop a custom application.

According to the independent wireless analyst firm Berg Insight, the number of cellular network connections worldwide used for machine to machine communication was 47.7 million in 2008. The company forecasts that the number of machine to machine connections will grow to 187 million by 2014.[27]

A research study from the E-Plus Group[28] shows that in 2010 2.3 million machine to machine smart cards will be in the German market. According to the study, this figure will rise in 2013 to over 5 million smart cards. The main growth driver is segment "tracking and tracing" with an expected average growth rate of 30 percent. The fastest growing M2M segment in Germany, with an average annual growth of 47 percent, will be the consumer electronics segment.

In April 2013, OASIS MQTT standards group is formed with the goal of working on a lightweight publish/subscribe reliable messaging transport protocol suitable for communication in M2M/IoT contexts.[29] IBM and StormMQ chair this standards group and Machine-to-Machine Intelligence (M2Mi) Corp is the secretary.[30] In May 2014, the committee published the MQTT and NIST Cybersecurity Framework Version 1.0 committee note to provide guidance for organizations wishing to deploy MQTT in a way consistent with the NIST Framework for Improving Critical Infrastructure Cybersecurity.[31]

In May 2013, machine to machine network service providers KORE Telematics, Oracle, Deutsche Telekom, Digi International, ORBCOMM and Telit formed the International Machine to Machine Council (IMC). The first trade organization to service the entire machine to machine ecosystem, the IMC aims at making machine to machine ubiquitous by helping companies install and manage the communication between machines.[32][33]

Applications[edit]

Commonplace consumer application

Wireless networks that are all interconnected can serve to improve production and efficiency in various areas, including machinery that works on building cars and on letting the developers of products know when certain products need to be taken in for maintenance and for what reason. Such information serves to streamline products that consumers buy and works to keep them all working at highest efficiency.[6]

Another application is to use wireless technology to monitor systems, such as utility meters. This would allow the owner of the meter to know if certain elements have been tampered with, which serves as a quality method to stop fraud.[citation needed] In Quebec, Rogers will connect Hydro Quebec's central system with up to 600 Smart Meter collectors, which aggregate data relayed from the province's 3.8-million Smart Meters.[citation needed] In the UK, Telefonica won on a €1.78 billion ($2.4 billion) smart-meter contract to provide connectivity services over a period of 15 years in the central and southern regions of the country. The contract is the industry’s biggest deal yet.[34]

A third application is to use wireless networks to update digital billboards. This allows advertisers to display different messages based on time of day or day-of-week, and allows quick global changes for messages, such as pricing changes for gasoline.[citation needed]

The industrial machine to machine market is undergoing a fast transformation as enterprises are increasingly realizing the value of connecting geographically dispersed people, devices, sensors and machines to corporate networks. Today, industries such as oil and gas, precision agriculture, military, government, smart cities/municipalities, manufacturing, and public utilities, among others, utilize machine to machine technologies for a myriad of applications. Many companies have enabled complex and efficient data networking technologies to provide capabilities such as high-speed data transmission, mobile mesh networking, and 3G/4G cellular backhaul.

Telematics and in-vehicle entertainment is an area of focus for machine to machine developers. Recent examples include Ford Motor Company, which has teamed with AT&T to wirelessly connect Ford Focus Electric with an embedded wireless connection and dedicated app that includes the ability for the owner to monitor and control vehicle charge settings, plan single- or multiple-stop journeys, locate charging stations, pre-heat or cool the car.[citation needed] In 2011, Audi partnered with T-Mobile and RACO Wireless to offer Audi Connect. Audi Connect allows users access to news, weather, and fuel prices while turning the vehicle into a secure mobile Wi-Fi hotspot, allowing passengers access to the Internet.[35]

Networks in prognostics and health management[edit]

Machine to machine wireless networks can serve to improve the production and efficiency of machines, to enhance the reliability and safety of complex systems, and to promote the life-cycle management for key assets and products. By applying Prognostic and Health Management (PHM) techniques in machine networks, the following goals can be achieved or improved:

  • Near-zero downtime performance of machines and system;
  • Health management of a fleet of similar machines.

The application of intelligent analysis tools and Device-to-Business (D2B) TM informatics platform form the basis of e-maintenance machine network that can lead to near-zero downtime performance of machines and systems.[36] The e-maintenance machine network provides integration between the factory floor system and e-business system, and thus enables the real time decision making in terms of near-zero downtime, reducing uncertainties and improved system performance.[37] In addition, with the help of highly interconnected machine networks and advance intelligent analysis tools, several novel maintenance types are made possible nowadays. For instance, the distant maintenance without dispatching engineers on-site, the online maintenance without shutting down the operating machines or systems, and the predictive maintenance before a machine failure become catastrophic. All these benefits of e-maintenance machine network add up improve the maintenance efficiency and transparency significantly.

As described in,[38] The framework of e-maintenance machine network consists of sensors, data acquisition system, communication network, analytic agents, decision-making support knowledge base, information synchronization interface and e-business system for decision making. Initially, the sensors, controllers and operators with data acquisition are used to collect the raw data from equipment and send it out to Data Transformation Layer automatically via internet or intranet. The Data Transform Layer then employs signal processing tools and feature extraction methods to convert the raw data into useful information. This converted information often carries rich information about the reliability and availability of machines or system and is more agreeable for intelligent analysis tools to perform subsequent process. The Synchronization Module and Intelligent Tools comprise the major processing power of the e-maintenance machine network and provide optimization, prediction, clustering, classification, bench-marking and so on. The results from this module can then be synchronized and shared with the e-business system on for decision making. In real application, the synchronization module will provide connection with other departments at the decision making level, like Enterprise Resource Planning (ERP), Customer Relation Management (CRM) and Supply Chain Management (SCM).

Another application of machine to machine network is in the health management for a fleet of similar machines using clustering approach. This method was introduced to address the challenge of developing fault detection models for applications with non-stationary operating regimes or with incomplete data. The overall methodology consists of two stages: 1) Fleet Clustering to group similar machines for sound comparison; 2) Local Cluster Fault Detection to evaluate the similarity of individual machines to the fleet features. The purpose of fleet clustering is to aggregate working units with similar configurations or working conditions into a group for sound comparison and subsequently create local fault detection models when global models cannot be established. Within the framework of peer to peer comparison methodology, the machine to machine network is crucial to ensure the instantaneous information share between different working units and thus form the basis of fleet level health management technology.

The fleet level health management using clustering approach was patented for its application in wind turbine health monitoring[39] after validated in a wind turbine fleet of three distributed wind farms.[40] Different with other industrial devices with fixed or static regimes, wind turbine's operating condition is greatly dictated by wind speed and other ambient factors. Even though the multi-modeling methodology can be applicable in this scenario, the number of wind turbines in a wind farm is almost infinite and may not present itself as a practical solution. Instead, by leveraging on data generated from other similar turbines in the network, this problem can be properly solved and local fault detection models can be effective built. The results of wind turbine fleet level health management reported in[39][41] demonstrated the effectiveness of applying a cluster-based fault detection methodology in the wind turbine networks.

Fault detection for a horde of industrial robots experiences similar difficulties as lack of fault detection models and dynamic operating condition. Industrial robots are crucial in automotive manufacturing and perform different tasks as welding, material handling, painting, etc. In this scenario, robotic maintenance becomes critical to ensure continuous production and avoid downtime. Historically, the fault detection models for all the industrial robots are trained similarly. Critical model parameters like training samples, components, and alarming limits are set the same for all the units regardless of their different functionalities. Even though these identical fault detection models can effectively identify faults sometimes, numerous false alarms discourage users from trusting the reliability of the system. However, within a machine network, industrial robots with similar tasks or working regimes can be group together; the abnormal units in a cluster can then be prioritized for maintenance via training based or instantaneous comparison. This peer to peer comparison methodology inside a machine network could improve the fault detection accuracy significantly.[40]

Open initiatives[edit]

See also[edit]

References[edit]

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  7. ^ Consultative Committee for Space Data (May 1996). "Packet Telemetry Service" (PDF). National Aeronautics and Space Administration.
  8. ^ U.S. Patent #3,812,296/5-21-1974 (Apparatus for Generating and Transmitting Digital Information), U.S. Patent #3,727,003/4-10-1973 (Decoding and Display Apparatus for Groups of Pulse Trains), U.S. Patent #3,842,208/10-15-1974 (Sensor Monitoring Device), U.S. Patent #4,241,237/12-23-1980 ("Apparatus and Method for Remote Sensor Monitoring, Metering and Control")
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  21. ^ Sprint and Axeda Announce Alliance for Global M2M Solutions, Sprint press release
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  33. ^<