Ambient intelligence

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An (expected) evolution of computing from 1960 to 2010 Evolution computer 1960-2010-fr.jpg
An (expected) evolution of computing from 1960 to 2010

Ambient intelligence (AmI) is a term used in computing to refer to electronic environments that are both sensitive and responsive to the presence of people. The term is generally applied to consumer electronics, telecommunications, and computing.

Contents

Ambient intelligence is intended to enable devices to work in concert with people in carrying out their everyday life activities in an intuitive way by using information and intelligence hidden in the network connecting these devices. An example of ambient intelligence is the Internet of Things (IoT). A typical context of the ambient intelligence environment is the home, but it may also be used in workspace (offices, co-working), public spaces (based on technologies such as smart streetlights), and hospital environments. [1]

The concept of ambient intelligence was originally developed in the late 1990's by Eli Zelkha and his team at Palo Alto Ventures for the time frame 2010–2020. [2] [3] [4] [5] Developers theorise that as devices grow smaller, more connected, and more integrated into human environments, the technological framework behind them will disappear into the surroundings until only the user interface remains perceivable by people.

Overview

The ambient intelligence concept builds upon pervasive computing, ubiquitous computing, profiling, context awareness, and human-centric computer interaction design. It is characterised by systems and technologies that are: [6]

Implementation of ambient intelligence requires several technologies to exist. These include hidden hardware such as miniaturization, nanotechnology, and smart devices, as well as human-centric computer interfaces (intelligent agents, multimodal interaction, context awareness, etc). These systems and devices operate through a seamless mobile/fixed communication and computing infrastructure characterised by interoperability, wired and wireless networks, and service-oriented architecture. Systems and devices must also be dependable and secure, which may be achieved through self-testing and self-repairing software and privacy-ensuring technology.

Ambient intelligence has a relationship with—and depends on advances in—sensor technology and sensor networks. [7]

User experience became more important to developers in the late 1990's as a result of digital products and services that were difficult to understand or use. In response, the user experience design emerged to create new technologies and media around the user's personal experience. Ambient intelligence is influenced by user-centred design, where the user is placed in the centre of the design activity and gives feedback to the designer.

History and invention

In 1998, Philips' management board commissioned a series of presentations and internal workshops organised by Eli Zelkha and Brian Epstein of Palo Alto Ventures. They investigated future scenarios and how consumer devices might advance over the next quarter-century. Zelkha and Epstein described the high-volume consumer electronics industry of the 1990's as "fragmented with features"; they envisioned that by 2020, an industry where user-friendly devices would support ubiquitous information, communication, and entertainment. [8] This outcome coined the term "ambient intelligence".

While developing the ambient intelligence concept, Palo Alto Ventures created the keynote address for Roel Pieper of Philips for the Digital Living Room Conference in 1998. [9] The group included Eli Zelkha, Brian Epstein, Simon Birrell, Doug Randall, and Clark Dodsworth. In 2000, there were plans to construct a feasibility and usability facility dedicated to ambient intelligence; these led to the opening of HomeLab on 24 April 2002. In 2005, Philips joined the Oxygen Alliance, an international consortium of industrial partners within the context of the MIT Oxygen project, [10] aimed at developing technology for the computer of the 21st century.

Along with developing the vision at Philips, several parallel initiatives started to explore ambient intelligence in more detail. Following the advice of the Information Society and Technology Advisory Group (ISTAG), the European Commission used the vision for the launch of their sixth framework (FP6) in Information, Society and Technology, with a budget of 3.7 billion euros.

During the first decade of the 21st century, several significant initiatives have been started. The Fraunhofer Society started several activities, including multimedia, micro-system design, and augmented spaces. The Massachusetts Institute of Technology started an ambient intelligence research group at their Media Lab. [11] Several more research projects started in a variety of countries such as the US, Canada, Spain, France, and the Netherlands. Since 2004, the European Symposium on Ambient Intelligence (EUSAI) and many other conferences have been held that address special topics in ambient intelligence.

Social and political aspects

The ISTAG advisory group suggests that society may be encouraged to use ambient intelligence, if AmI projects meet these criteria:[ citation needed ]

Business models

The ISTAG group concluded that ambient intelligence technologies can contribute to profitable businesses in a number of ways. The methods identified were:[ citation needed ]

Technologies

A variety of technologies can be used to enable ambient intelligence environments, such as: [12]

Criticism

The ambient intelligence concept is subject to criticism (e.g. David Wright, Serge Gutwirth, Michael Friedewald, et al., Safeguards in a World of Ambient Intelligence, Springer, Dordrecht, 2008). Ambient intelligence can be immersive, personalised, context-aware, and anticipatory; these characteristics bring up societal, political, and cultural concerns about the loss of privacy. Proponents of AmI argue that applications of ambient intelligence can function without necessarily reducing privacy. [13] [14] [15]

Critics also discuss power concentration in large organisations; a fragmented, decreasingly private society; and hyper-real environments where the virtual is indistinguishable from the real. [16] Several research groups and communities have investigated the socioeconomic, political and cultural aspects of ambient intelligence.

Uses in fiction

See also

Related Research Articles

Ubiquitous computing is a concept in software engineering, hardware engineering and computer science where computing is made to appear anytime and everywhere. In contrast to desktop computing, ubiquitous computing can occur using any device, in any location, and in any format. A user interacts with the computer, which can exist in many different forms, including laptop computers, tablets, smart phones and terminals in everyday objects such as a refrigerator or a pair of glasses. The underlying technologies to support ubiquitous computing include Internet, advanced middleware, operating system, mobile code, sensors, microprocessors, new I/O and user interfaces, computer networks, mobile protocols, location and positioning, and new materials.

<span class="mw-page-title-main">Home automation</span> Building automation for a home

Home automation or domotics is building automation for a home. A home automation system will monitor and/or control home attributes such as lighting, climate, entertainment systems, and appliances. It may also include home security such as access control and alarm systems.

Context awareness refers, in information and communication technologies, to a capability to take into account the situation of entities, which may be users or devices, but are not limited to those. Location is only the most obvious element of this situation. Narrowly defined for mobile devices, context awareness does thus generalize location awareness. Whereas location may determine how certain processes around a contributing device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to contextual application design and business process management issues.

<span class="mw-page-title-main">Smart device</span> Type of electronic device

A smart device is an electronic device, generally connected to other devices or networks via different wireless protocols that can operate to some extent interactively and autonomously. Several notable types of smart devices are smartphones, smart speakers, smart cars, smart thermostats, smart doorbells, smart locks, smart refrigerators, phablets and tablets, smartwatches, smart bands, smart keychains, smart glasses, and many others. The term can also refer to a device that exhibits some properties of ubiquitous computing, including—although not necessarily—machine learning.

Smart environments link computers and other smart devices to everyday settings and tasks. Smart environments include smart homes, smart cities, and smart manufacturing.

Intelligent Environments (IE) are spaces with embedded systems and information and communication technologies creating interactive spaces that bring computation into the physical world and enhance occupants experiences. "Intelligent environments are spaces in which computation is seamlessly used to enhance ordinary activity. One of the driving forces behind the emerging interest in highly interactive environments is to make computers not only genuine user-friendly but also essentially invisible to the user".

<span class="mw-page-title-main">Edge computing</span> Distributed computing paradigm

Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data, so that a user of a cloud application is likely to be physically closer to a server than if all servers were in one place. This is meant to make applications faster. More broadly, it refers to any design that pushes computation physically closer to a user, so as to reduce the latency compared to when an application runs on a single data centre. In the extreme case, this may simply refer to client-side computing.

Context-aware computing refers to a general class of mobile systems that can sense their physical environment, and adapt their behavior accordingly.

The Internet of things (IoT) describes devices with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks. The Internet of things encompasses electronics, communication, and computer science engineering. "Internet of things" has been considered a misnomer because devices do not need to be connected to the public internet; they only need to be connected to a network and be individually addressable.

Ubiquitous robot is a term used in an analogous way to ubiquitous computing. Software useful for "integrating robotic technologies with technologies from the fields of ubiquitous and pervasive computing, sensor networks, and ambient intelligence".

Anind Dey is a computer scientist. He is the Dean of the University of Washington Information School. Dey is formerly the director of the Human-Computer Interaction Institute at Carnegie Mellon University. His research interests lie at the intersection of human–computer interaction and ubiquitous computing, focusing on how to make novel technologies more usable and useful. In particular, he builds tools that make it easier to build useful ubiquitous computing applications and supporting end users in controlling their ubiquitous computing systems.

A smart object is an object that enhances the interaction with not only people but also with other smart objects. Also known as smart connected products or smart connected things (SCoT), they are products, assets and other things embedded with processors, sensors, software and connectivity that allow data to be exchanged between the product and its environment, manufacturer, operator/user, and other products and systems. Connectivity also enables some capabilities of the product to exist outside the physical device, in what is known as the product cloud. The data collected from these products can be then analyzed to inform decision-making, enable operational efficiencies and continuously improve the performance of the product.

Visual privacy is the relationship between collection and dissemination of visual information, the expectation of privacy, and the legal issues surrounding them. These days digital cameras are ubiquitous. They are one of the most common sensors found in electronic devices, ranging from smartphones to tablets, and laptops to surveillance cams. However, privacy and trust implications surrounding it limit its ability to seamlessly blend into computing environment. In particular, large-scale camera networks have created increasing interest in understanding the advantages and disadvantages of such deployments. It is estimated that over 4 million CCTV cameras deployed in the UK. Due to increasing security concerns, camera networks have continued to proliferate across other countries such as the United States. While the impact of such systems continues to be evaluated, in parallel, tools for controlling how these camera networks are used and modifications to the images and video sent to end-users have been explored.

Location awareness refers to devices that can determine their location. Navigational instruments provide location coordinates for vessels and vehicles. Surveying equipment identifies location with respect to a well-known location wireless communications device.

Spatial contextual awareness consociates contextual information such as an individual's or sensor's location, activity, the time of day, and proximity to other people or objects and devices. It is also defined as the relationship between and synthesis of information garnered from the spatial environment, a cognitive agent, and a cartographic map. The spatial environment is the physical space in which the orientation or wayfinding task is to be conducted; the cognitive agent is the person or entity charged with completing a task; and the map is the representation of the environment which is used as a tool to complete the task.

Mobile Cloud Computing (MCC) is the combination of cloud computing and mobile computing to bring rich computational resources to mobile users, network operators, as well as cloud computing providers. The ultimate goal of MCC is to enable execution of rich mobile applications on a plethora of mobile devices, with a rich user experience. MCC provides business opportunities for mobile network operators as well as cloud providers. More comprehensively, MCC can be defined as "a rich mobile computing technology that leverages unified elastic resources of varied clouds and network technologies toward unrestricted functionality, storage, and mobility to serve a multitude of mobile devices anywhere, anytime through the channel of Ethernet or Internet regardless of heterogeneous environments and platforms based on the pay-as-you-use principle."

Albrecht Schmidt is a computer scientist best known for his work in ubiquitous computing, pervasive computing, and the tangible user interface. He is a professor at Ludwig Maximilian University of Munich where he joined the faculty in 2017.

Nearables are a type of smart object. They are everyday items that have small, wireless computing devices attached to them. These devices can be equipped with a variety of sensors and work as transmitters to broadcast digital data through a variety of methods, but they usually use the Bluetooth Smart protocol. Due to this, these objects are able to provide mobile devices in range with information about their location, state and immediate surroundings. The word 'nearables' is a reference to wearable technology – electronic devices worn as part of clothing or jewellery.

Crowdsensing, sometimes referred to as mobile crowdsensing, is a technique where a large group of individuals having mobile devices capable of sensing and computing collectively share data and extract information to measure, map, analyze, estimate or infer (predict) any processes of common interest. In short, this means crowdsourcing of sensor data from mobile devices.

<span class="mw-page-title-main">Eli Zelkha</span> American entrepreneur, venture capitalist and professor

Elias "Eli" Zelkha was an Iranian-American entrepreneur, venture capitalist and professor. He was the inventor of ambient intelligence.

References

  1. "Ambient Intelligence within a Home Environment". www.ercim.eu. Retrieved December 14, 2017.
  2. Arribas-Ayllon, Michael. "Ambient Intelligence: an innovation narrative". Lancs.ac.uk.
  3. Aarts, Emile H. L.; Encarnação, José Luis (December 13, 2006). True Visions: The Emergence of Ambient Intelligence. Springer. ISBN   9783540289746 via Google Books.
  4. Nolin, Jan; Olson, Nasrine (2016). "The Internet of Things and Convenience (PDF Download Available)". Internet Research. 26 (2): 360–376. doi:10.1108/IntR-03-2014-0082.
  5. "Ambient Intelligence Knowledge Center .: SemiEngineering.com".
  6. Brian Epstein, Digital Living Room Conference Keynote 1998, (17 June 1998: revised script) https://epstein.org/ambient-intelligence/ accessed 14/12/17
  7. Cook, Diane J.; Augusto, Juan C.; Jakkula, Vikramaditya R. (August 1, 2009). "Ambient intelligence: Technologies, applications, and opportunities". Pervasive and Mobile Computing. 5 (4): 277–298. doi:10.1016/j.pmcj.2009.04.001. ISSN   1574-1192. S2CID   2751401.
  8. Olson, Nasrine; Nolin, Jan; Nelhans, Gustaf (2015). "Semantic web, ubiquitous computing, or internet of things? A macro-analysis of scholarly publications". Journal of Documentation. 71 (5): 884–916. doi:10.1108/JD-03-2013-0033.
  9. Aarts, Emile H. L.; Encarnação, José Luis (December 13, 2006). True Visions: The Emergence of Ambient Intelligence. Springer. ISBN   9783540289746 via Google Books.
  10. "MIT Project Oxygen". Computer Science and Artificial Intelligence Laboratory. Retrieved June 27, 2012.
  11. "Fluid Interfaces Group". MIT Media Lab. Archived from the original on May 10, 2012. Retrieved June 27, 2012.
  12. Gasson & Warwick 2013.
  13. Hildebrandt, Mireille; Koops, Bert-Jaap (2010). "The Challenges of Ambient Law and Legal Protection in the Profiling Era" (PDF). The Modern Law Review. 73 (3): 428–460. doi:10.1111/j.1468-2230.2010.00806.x. ISSN   0026-7961. JSTOR   40660735. S2CID   55400364.
  14. Lopez, Mar; Pedraza, Juanita; Carbó, Javier; Molina, José (June 4, 2014). "Ambient Intelligence: Applications and Privacy Policies". Highlights of Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. Communications in Computer and Information Science. Vol. 430. pp. 191–201. doi:10.1007/978-3-319-07767-3_18. hdl:10016/27593. ISBN   978-3-319-07766-6.
  15. Streitz, Norbert; Charitos, Dimitris; Kaptein, Maurits; Böhlen, Marc (January 1, 2019). "Grand challenges for ambient intelligence and implications for design contexts and innovative societies". Journal of Ambient Intelligence and Smart Environments. 11 (1): 87–107. doi: 10.3233/AIS-180507 . ISSN   1876-1364.
  16. "No Ads on Orkut, but Come". ClickZ. October 8, 2007. Retrieved December 14, 2017.
  17. Parker 2002.

Bibliography