Intelligent environment

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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. [1] "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". [2]

Contents

IEs describe physical environments in which information and communication technologies and sensor systems disappear as they become embedded into physical objects, infrastructures, and the surroundings in which we live, travel and work. The goal here is to allow computers to take part in activities never previously involved and allow people to interact with computers via gesture, voice, movement, and context. [3]

Origins

Conceptual figure of Intelligent Space (by J.-H. Lee and H. Hashimoto) Conceptual figure of Intelligent Space (J.-H. Lee and H. Hashimoto.png
Conceptual figure of Intelligent Space (by J.-H. Lee and H. Hashimoto)

The idea of having an artificial intelligence capable of managing an environment, recollect data, and respond in consequence is older than we would expect. In the novel 2001: A Space Odyssey from 1968, long before the microcomputers revolution, you have the fictional character HAL 9000, a computer capable of controlling the different sensors and systems of the environment and using them as extensions of itself. The character Proteus from the 1973 novel Demon Seed also portrays the same characteristics of an artificial intelligence controlling an embedded environment. By the time these two novels were released, the idea of a computer controlling the environment that surrounds us was not broadly accepted by the community since both characters played the role of evil machines whose only objectives included the control over humans. [4]

The term 'Intelligent environments' is a concept and expression originally created by Peter Droege for his homonymous Elsevier publication of 1997, a project that commenced in 1986: Intelligent environments - Spatial Aspects of the Information Revolution https://www.sciencedirect.com/book/9780444823328/intelligent-environments. The 1986 project was his winning entry into the Campus City Kawasaki competition in Japan, seeking to apply the benefits of information technology and advanced telecommunications to an entire city, its societal empowerment, trans-industrial prosperity and, above all, its environmental redemption.

It is not until 1991 with the introduction of ubiquitous computing by Mark Weiser when we start seeing an inclination from the scientific community to study the area of computing outside of the typical machine with a keyboard and a screen. It became something that could be potentially implemented into anything that surrounds us, proposing casual access to computing to any user. In 1996 Hashimoto Laboratory at the University of Tokyo developed the first research on intelligent spaces. J.-H. Lee and H. Hashimoto designed a room with a homemade three-dimensional tracking sensor and mobile robots, all this connected to a network. The idea was for the robots to support the person in the room with different tasks with the help of vision cameras and computer sets, becoming one of the first intelligent environment. [4]

At first, intelligent spaces were designed with the only objective to help people with physical tasks. Robots included in the room would help people to grab objects as well as support people with disabilities to do certain jobs. This idea started shifting into the concept we have today of intelligent environments, not only an environment to support people but also robots. The intelligent space became a platform that extends the censorial capacity of anything connected to it. If we start designing products, either software or hardware around this intelligent environments, the effort needed to complete all kinds of tasks would be drastically reduced. [4]

Challenges

Practical implementation of intelligent environments implies the solution of many challenges. Pervasive computing systems embedded in IE need to be proactive and to accomplish this, it is crucial that systems can track and determine the users' intent. The challenge here is finding that action that supposedly will help the user rather than hinder him. As of right now, algorithms behind the intelligent environments are constantly being reworked by the simple method of trial and error in artificial environments. It is not until a programmer can see an accurate enough level of prediction for the product to become commercialized. The degree of accuracy of intelligent environments depends on the task they want to accomplish. Some simple actions that do not substantially affect the user can admit more failures in the predictions than other functions that hold more responsibility. Still, there are always actions that cannot be fully predicted by the IE and needs some input from the user to be completed. One of the most significant challenges as of right now is determining which are those actions that are required for user input and how to create algorithms capable of eliminating that input so that the usability of the systems improves. [5]

By the other hand, pro-activity of such environments has to be handled very carefully. Pervasive computing systems are supposed to be minimally intrusive and at the same time be capable of taking decisions that will help users. One way to achieve that is making those systems capable of modifying their behavior based on the user's state and surroundings. Here again, some challenges arise: What are the required data and information that a system needs to be context-aware? How frequently should that information be measured and consulted without hurting system performance? The goal is to create an IE capable of reacting fast and accurate to the needs and inputs of the user so it would be unnecessary for the sensors to record information that will not help the algorithms make the correct action to what is happening. Recognizing important data and filtering the environment to search for the appropriate place to obtain it results in a great challenge. [5]

It is crucial for pervasive computing systems to find the right level of pro-activity and transparency without annoying the user. Systems can infer the user's needs for pro-activity based on his level of expertise on a particular task. Self-tuning can be crucial for accomplishing this goal.

As the Intelligent Environments Conference (2007) points out: "Types of Intelligent Environments range from private to public and from fixed to mobile; some are ephemeral while others are permanent; some change type during their lifespan. The realization of Intelligent Environments requires the convergence of different disciplines: Information and Computer Science, Architecture, Material Engineering, Artificial Intelligence, Sociology, and Design. Besides, technical breakthroughs are required in key enabling technology fields, such as microelectronics (e.g., miniaturization, power consumption), communication and networking technologies (e.g., broadband and wireless networks), smart materials (e.g., bio-implants) and intelligent agents (e.g., context awareness)". The correct integration of all of these components is crucial to developing a useful IE. [6]

Applications

Business

One of the main areas that will experience a significant impact on the emergence of IE is business relations. The way companies interact with each other and with people will suffer the most significant impact. Their relationships will become more dynamic and should emphasize a more flexible approach to businesses, trying to adapt to the continually changing commercial environment. Such flexibility should also be reflected also on their employees and their work environment. Even today, companies that have shown significant levels of flexibility on their working environments and with their employees (as at Microsoft or Google) have increasing levels of productivity and employees retention. [7]

Another critical issue that companies must take into account in the IE era is the way they approach the privacy of their clients. The success of these future companies will depend significantly on how people feel more confident in the use they give to their personal information. Another essential key to the success of these prospective businesses will be to allow the end user to have control over the way in which the IE systems make the decisions. Friendly user configurations should enable them to be in control of these systems but at the time is one of the biggest challenges for systems engineers.

Leisure Activities

New ways of entertainment have emerged since the creation of IE. There have been several experiments in museums where this technology is used to create a more interactive experience that makes the visitors not only experience history with their eyes but also feel in all of their senses. From the use of sounds and lights that adapt according to the expositions presented to the incorporation of smells that define unique environments, there are endless opportunities to the application of IE into this sort of entertainment. [8]

The same concept can be used to not only improve existent leisure experiences but also to create new ones. Artistic expression has had a significant influence on this since we have seen new forms of art using Artificial Intelligence and IE. Take for example the work of the artist Chris Milk where you can see the implementation of immersive installations that make the user not only appreciate a work of art but also be part of it. One of his most important work of arts, "The Treachery of Sanctuary" uses projections of the users' bodies in different screens to explore the creative process by using generated digital birds. These type of art requires the user's interaction to exist. [9] [8]

Health Care

One of the most critical applications of Intelligent Environments is in the Healthcare Industry. You can use IE in the hospital's rooms to monitor the state of the patients without the patient even noticing, which results in less disturbance to those patients who need extraordinary amounts of rest and fewer efforts for nurses that are no longer required to check on patients regularly. This technology could substantially change the way in which hospitals and clinics are designed since nurses can be more efficient with their time attending patients in critical needs without leaving other patients under the care of intelligent rooms. This unique installations will no longer monitor the patient's health and notify the nurses, but it could also be programmed to interact with them with preventative purposes by administering specific drugs or directly delivering food when needed. [8]

Caring of frail, elderly patients could dramatically change in the future with the use of IE. By introducing this technology into their own homes, we will be able to monitor a patient from anywhere we are without having the need to transporting them to hospitals or clinics to have proper care. This could transform nearly any house into an intelligent nursing home care, allowing families to save lots of money by dramatically reducing the cost of care. [8]

Emergency Response

Preventing is the best way to fighting a possible problem and there is no better way to do so that gathering information prior to a problematic event that helps us know when it would happen. IE would provide the perfect way to gather the data necessary to predict hazards and possible problems in the future. If we implement IE in our houses, it could notify, for example, the fire department if a fire is about to happen without us even noticing, or the police department if suspicious activity is detected in the proximity of our homes. In the best scenario, the event would not happen since the IE will help us create a diagnosis of the environment where it is implemented so that we could attack possible issues long before it happens. This will substantially improve live conditions in the cities, and a substantial economic impact since less hazardous events would happen, preventing material loss. [8]

Environmental Monitoring

Intelligent Environments will help us monitor different natural environments at a much higher precision and granularity than the currently used techniques. By having access to a richer and more significant data, it will not only help us to control the environment for possible hazards, but it will also change the way in which we understand it, making us improve the current theories and models of environmental processes. As of today, this technology is being used to study phenomena such as coastal erosion, flooding and the movement of glacial. We know very little about the why of many natural processes that are currently affecting us and having more accurate and precise data will significantly improve the way in which we attack those issues so that we not only make humans more environmentally friendly but also improve the health of our planet. [8]

See also

Related Research Articles

Ubiquitous computing is a concept in software engineering, hardware engineering and computer science where computing is made to appear seamlessly anytime and everywhere. In contrast to desktop computing, ubiquitous computing implies use on 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 the Internet, advanced middleware, kernels, operating systems, mobile codes, sensors, microprocessors, new I/Os and user interfaces, computer networks, mobile protocols, global navigational systems, and new materials.

<span class="mw-page-title-main">Telerobotics</span> Controlling robots from a distance

Telerobotics is the area of robotics concerned with the control of semi-autonomous robots from a distance, chiefly using television, wireless networks or tethered connections. It is a combination of two major subfields, which are teleoperation and telepresence.

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.

Autonomic computing (AC) is distributed computing resources with self-managing characteristics, adapting to unpredictable changes while hiding intrinsic complexity to operators and users. Initiated by IBM in 2001, this initiative ultimately aimed to develop computer systems capable of self-management, to overcome the rapidly growing complexity of computing systems management, and to reduce the barrier that complexity poses to further growth.

Human-centered computing (HCC) studies the design, development, and deployment of mixed-initiative human-computer systems. It is emerged from the convergence of multiple disciplines that are concerned both with understanding human beings and with the design of computational artifacts. Human-centered computing is closely related to human-computer interaction and information science. Human-centered computing is usually concerned with systems and practices of technology use while human-computer interaction is more focused on ergonomics and the usability of computing artifacts and information science is focused on practices surrounding the collection, manipulation, and use of information.

Multimodal interaction provides the user with multiple modes of interacting with a system. A multimodal interface provides several distinct tools for input and output of data.

<span class="mw-page-title-main">Ambient intelligence</span>

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

<span class="mw-page-title-main">Smart environment</span> Computing environment involving multiple devices

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

<span class="mw-page-title-main">Systems architecture</span> Conceptual model of a system

A system architecture is the conceptual model that defines the structure, behavior, and more views of a system. An architecture description is a formal description and representation of a system, organized in a way that supports reasoning about the structures and behaviors of the system.

<span class="mw-page-title-main">Mobile robot</span> Type of robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering.

Adaptable Robotics refers to a field of robotics with a focus on creating robotic systems capable of adjusting their hardware and software components to perform a wide range of tasks while adapting to varying environments. The 1960s introduced robotics into the industrial field. Since then, the need to make robots with new forms of actuation, adaptability, sensing and perception, and even the ability to learn stemmed the field of adaptable robotics. Significant developments such as the PUMA robot, manipulation research, soft robotics, swarm robotics, AI, cobots, bio-inspired approaches, and more ongoing research have advanced the adaptable robotics field tremendously. Adaptable robots are usually associated with their development kit, typically used to create autonomous mobile robots. In some cases, an adaptable kit will still be functional even when certain components break.

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 communication 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.

A pervasive game is one where the gaming experience is extended out into the real world, or where the fictional world in which the game takes place blends with the physical world. The "It's Alive" mobile games company described pervasive games as "games that surround you," while Montola, Stenros, and Waern's book Pervasive Games defines them as having "one or more salient features that expand the contractual magic circle of play spatially, temporally, or socially." The concept of a "magic circle" draws from the work of Johan Huizinga, who describes the boundaries of play.

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".

Activity recognition aims to recognize the actions and goals of one or more agents from a series of observations on the agents' actions and the environmental conditions. Since the 1980s, this research field has captured the attention of several computer science communities due to its strength in providing personalized support for many different applications and its connection to many different fields of study such as medicine, human-computer interaction, or sociology.

Urban computing is an interdisciplinary field which pertains to the study and application of computing technology in urban areas. This involves the application of wireless networks, sensors, computational power, and data to improve the quality of densely populated areas. Urban computing is the technological framework for smart cities.

Pervasive informatics is the study of how information affects interactions with the built environments they occupy. The term and concept were initially introduced by Professor Kecheng Liu during a keynote speech at the SOLI 2008 international conference.

<span class="mw-page-title-main">Body area network</span> Small-scale computer network to connect devices around a human body, typically wearables

A body area network (BAN), also referred to as a wireless body area network (WBAN), a body sensor network (BSN) or a medical body area network (MBAN), is a wireless network of wearable computing devices. BAN devices may be embedded inside the body as implants or pills, may be surface-mounted on the body in a fixed position, or may be accompanied devices which humans can carry in different positions, such as in clothes pockets, by hand, or in various bags. Devices are becoming smaller, especially in body area networks. These networks include multiple small body sensor units (BSUs) and a single central unit (BCU). Despite this trend, decimeter sized smart devices still play an important role. They act as data hubs or gateways and provide a user interface for viewing and managing BAN applications on the spot. The development of WBAN technology started around 1995 around the idea of using wireless personal area network (WPAN) technologies to implement communications on, near, and around the human body. About six years later, the term "BAN" came to refer to systems where communication is entirely within, on, and in the immediate proximity of a human body. A WBAN system can use WPAN wireless technologies as gateways to reach longer ranges. Through gateway devices, it is possible to connect the wearable devices on the human body to the internet. This way, medical professionals can access patient data online using the internet independent of the patient location.

Cloud robotics is a field of robotics that attempts to invoke cloud technologies such as cloud computing, cloud storage, and other Internet technologies centered on the benefits of converged infrastructure and shared services for robotics. When connected to the cloud, robots can benefit from the powerful computation, storage, and communication resources of modern data center in the cloud, which can process and share information from various robots or agent. Humans can also delegate tasks to robots remotely through networks. Cloud computing technologies enable robot systems to be endowed with powerful capability whilst reducing costs through cloud technologies. Thus, it is possible to build lightweight, low-cost, smarter robots with an intelligent "brain" in the cloud. The "brain" consists of data center, knowledge base, task planners, deep learning, information processing, environment models, communication support, etc.

Joëlle Coutaz is a French computer scientist, specializing in human-computer interaction (HCI). Her career includes research in the fields of operating systems and HCI, as well as being a professor at the University of Grenoble. Coutaz is considered a pioneer in HCI in France, and in 2007, she was awarded membership to SIGCHI. She was also involved in organizing CHI conferences and was a member on the editorial board of ACM Transactions on Computer-Human Interaction.

References

  1. ↑ Augusto, Juan C; Callaghan, Vic (2013). "Intelligent Environments: a manifesto" (PDF). Human-centric Computing and Information Sciences. 3: 12. doi: 10.1186/2192-1962-3-12 . S2CID   4221143.
  2. ↑ Steventon, A., and Wright, S. (eds) (2006) Intelligent Spaces: The Application of Pervasive ICT, Springer-Verlag.
  3. ↑ "Intelligent Environments Conference".
  4. 1 2 3 Lee, Joo-Ho; Hashimoto, Hideki (2002). "Intelligent Space — concept and contents". Advanced Robotics. 16 (3): 265–280. doi:10.1163/156855302760121936. ISSN   0169-1864. S2CID   207629201.
  5. 1 2 Satyanarayanan, M. (2001). "Pervasive Computing: Vision and Challenges". IEEE Personal Communications. 8 (4): 10–17. doi:10.1109/98.943998.
  6. ↑ "Intelligent Environments Conference (2007)". Archived from the original on 2013-09-29. Retrieved 2021-06-25.
  7. ↑ Steventon, Alan; Wright, Steve (2010-05-30). Intelligent Spaces: The Application of Pervasive ICT. Springer Science & Business Media. ISBN   9781846284298.
  8. 1 2 3 4 5 6 Wright, S; Steventon, A (2004). "Intelligent Spaces — The Vision, the Opportunities and the Barriers". BT Technology Journal. 22 (3): 15–26. doi:10.1023/b:bttj.0000047116.13540.e0. ISSN   1358-3948. S2CID   62538246.
  9. ↑ "Art in the Age of AI: How Tech Is Redefining Our Creativity". Singularity Hub. 2017-02-06. Retrieved 2018-11-28.

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