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Journal articles on the topic 'Ambient intelligent'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 March 2023

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1

Santofimia, María J., Francisco Moya, Félix J. Villanueva, David Villa, and Juan C. López. "How Intelligent Are Ambient Intelligence Systems?" International Journal of Ambient Computing and Intelligence 2, no. 1 (January 2010): 66–72. http://dx.doi.org/10.4018/jaci.2010010106.

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Since the appearance of the Ambient Intelligence paradigm, as an evolution of the Ubiquitous Computing, a great deal of the research efforts in this ?eld have been mainly aimed at anticipating user actions and needs, out of a pre?xed set. However, Ambient Intelligence is not just constrained to user behaviour pattern matching, but to wisely supervise the whole environment, satisfying those unforeseen requirements or needs, by means of rational decisions. This work points at the lack of commonsense reasoning, as the main reason underlying the existance of these idiots savant systems, capable of accomplishing very speci?c and complex tasks, but incapable of making decisions out of the pre?xed behavioral patterns. This work advocates for the integration of the commonsense reasoning and understanding capabilities as the key elements in bridging the gap between idiot savant systems and real Ambient Intelligence systems.

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Djuric, Igor, Vanjica Ratkovic-Zivanovic, Milica Labus, Dragana Groj, and Nikola Milanovic. "Designing an intelligent home media center." Facta universitatis - series: Electronics and Energetics 29, no. 3 (2016): 461–74. http://dx.doi.org/10.2298/fuee1603461d.

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This paper presents design and implementation of a personal intelligent home media center. The primary goal was to increase the quality of life with the use of ambient intelligence in smart homes. The solution presented here uses client-server architecture with network-attached storage for storing all multimedia contents. Sensors are used to identify person?s presence and ambient intelligence techniques to recommend the most suitable multimedia content to end-users. The major advantages of this personal intelligent home media center are speed, intelligence, inexpensive components and scalability. The implementation was done in within one home media center, for the evaluation purposes.

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Yogi, Manas Kumar. "AMBIENT INTELLIGENCE: PRINCIPLES,CURRENT TRENDS, FUTURE DIRECTIONS." International Journal of Advanced Research in Computer Science and Software Engineering 8, no. 2 (March 6, 2018): 43. http://dx.doi.org/10.23956/ijarcsse.v8i2.519.

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In this paper we have presented the involved principles, trends, future directions of ambient intelligence. in the first section we have elucidated concept of ambient intelligence with the prevalent need of intelligent communication with the help of designing knowledgeable entities. We have presented the design process of I-blocks with its inherent merits. we have also discussed the various design concepts of ambient intelligence objects. Finally, we presented the current research directions to motivate societal needs of human beings.

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Bureš, Vladimír, Petr Tučník, Peter Mikulecký, Karel Mls, and Petr Blecha. "Application of Ambient Intelligence in Educational Institutions." International Journal of Ambient Computing and Intelligence 7, no. 1 (January 2016): 94–120. http://dx.doi.org/10.4018/ijaci.2016010105.

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The ambient intelligence concept provides a vision of society of the future, where people will find themselves in an environment of intelligent and intuitively usable interfaces. The manuscript applies this definition to the specific environment of higher education in the context of the Czech Republic. The existence of the so-called Generation Y and characteristics of included individuals represent the main rationale of this paper. In particular sections of this paper, three visions that focus on intelligent assistance for graduation thesis preparation, smart lecture halls, and smart university campuses are described, and related architectures are depicted. Furthermore, results from a survey evaluating three main aspects - feasibility, willingness to use, and accessibility of technologies - of these visions are presented.

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Traynor, Declan, Ermai Xie, and Kevin Curran. "Context-Awareness in Ambient Intelligence." International Journal of Ambient Computing and Intelligence 2, no. 1 (January 2010): 13–23. http://dx.doi.org/10.4018/jaci.2010010102.

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Ambient Intelligence (AmI) deals with the issue of how we can create context-aware, electronic environments which foster seamless human-computer interaction. Ambient Intelligence encompasses the fields of ubiquitous computing, artificially intelligent systems, and context awareness among others. This paper discusses context-awareness and examines how discoveries in this area will be key in propelling the development of true AmI environments. This will be done by examining the background and reasoning behind this particular strand of AmI research along with an overview of the technologies being explored alongside possible applications of context awareness in computing as well as technological and socio- ethical challenges in this field.

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Crutzen, C. K. M. "Invisibility and the Meaning of Ambient Intelligence." International Review of Information Ethics 6 (December 1, 2006): 52–62. http://dx.doi.org/10.29173/irie140.

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A vision of future daily life is explored in Ambient Intelligence (AmI). It contains the assumption that intelligent technology should disappear into our environment to bring humans an easy and entertaining life. The mental, physical, methodical invisibility of AmI will have an effect on the relation between design and use activities of both users and designers. Especially the ethics discussions of AmI, privacy, identity and security are moved into the foreground. However in the process of using AmI, it will go beyond these themes. The infiltration of AmI will cause the construction of new meanings of privacy, identity and security because the "visible" acting of people will be preceded, accompanied and followed by the invisible and visible acting of the AmI technology and their producers. A question in this paper is: How is it possible to create critical transformative rooms in which doubting will be possible under the circumstances that autonomous 'intelligent agents' surround humans? Are humans in danger to become just objects of artificial intelligent conversations? Probably the relation between mental, physical, methodical invisibility and visibility of AmI could give answers.

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7

Leonidis, Korozi, Kouroumalis, Poutouris, Stefanidi, Arampatzis, Sykianaki, et al. "Ambient Intelligence in the Living Room." Sensors 19, no. 22 (November 16, 2019): 5011. http://dx.doi.org/10.3390/s19225011.

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The emergence of the Ambient Intelligence (AmI) paradigm and the proliferation of Internet of Things (IoT) devices and services unveiled new potentials for the domain of domestic living, where the line between “the computer” and the (intelligent) environment becomes altogether invisible. Particularly, the residents of a house can use the living room not only as a traditional social and individual space where many activities take place, but also as a smart ecosystem that (a) enhances leisure activities by providing a rich suite of entertainment applications, (b) implements a home control middleware, (c) acts as an intervention host that is able to display appropriate content when the users need help or support, (d) behaves as an intelligent agent that communicates with the users in a natural manner and assists them throughout their daily activities, (e) presents a notification hub that provides personalized alerts according to contextual information, and (f) becomes an intermediary communication center for the family. This paper (i) describes how the “Intelligent Living Room” realizes these newly emerged roles, (ii) presents the process that was followed in order to design the living room environment, (iii) introduces the hardware and software facilities that were developed in order to improve quality of life, and (iv) reports the findings of various evaluation experiments conducted to assess the overall User Experience (UX).

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8

de Ruyter, Boris. "Social interactions in Ambient Intelligent environments." Journal of Ambient Intelligence and Smart Environments 3, no. 2 (2011): 175–77. http://dx.doi.org/10.3233/ais-2011-0104.

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9

Sarikaya, Ruhi. "Intelligent Conversational Agents for Ambient Computing." ACM SIGIR Forum 56, no. 2 (December 2022): 1–10. http://dx.doi.org/10.1145/3582900.3582907.

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We are in the midst of an AI revolution. Three primary disruptive changes set off this revolution: 1) increase in compute power, mobile internet, and advances in deep learning. The next decade is expected to be about the proliferation of Internet-of-Things (IoT) devices and sensors, which will generate exponentially larger amounts of data to reason over and pave the way for ambient computing. This will also give rise to new forms of interaction patterns with these systems. Users will have to interact with these systems under increasingly richer context and in real-time. Conversational AI has a critical role to play in this revolution, but only if it delivers on its promise of enabling natural, frictionless, and personalized interactions in any context the user is in, while hiding the complexity of these systems through ambient intelligence. However, current commercial conversational AI systems are trained primarily with a supervised learning paradigm, which is difficult, if not impossible, to scale by manually annotating data for increasingly complex sets of contextual conditions. Inherent ambiguity in natural language further complicates the problem. We need to devise new forms of learning paradigms and frameworks that will scale to this complexity. In this talk, we present some early steps we are taking with Alexa, Amazon's Conversational AI system, to move from supervised learning to self-learning methods, where the AI relies on customer interactions for supervision in our journey to ambient intelligence. Date: 14 July 2022.

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Mustaquim, Moyen Mohammad. "Designing Ambient Media." International Journal of Ambient Computing and Intelligence 5, no. 1 (January 2013): 19–33. http://dx.doi.org/10.4018/jaci.2013010102.

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The philosophy of information is the area of research that studies conceptual issues arising at the intersection of computer science, information technology and philosophy. Universal design is a concept that emphasizes the importance of non-specialized features in things and environments. As ambient media is becoming more intelligent and the users are already across a larger part of the population, the path towards achieving universal design and change of attitude in the authors’ minds is clear but requires that they think globally and frame the issues a little differently. This article aims to see universal design concept; its principles, uses, design processes, from a philosophical perspective in terms of ambient media design. Principles for designing intelligent user interface are derived from the universal design principles and a framework is proposed. The framework is then verified to see how optimally these intelligent user interface design principles can work to enhance ambient media experience. The paper concludes by arguing that the concept of universal design for ambient media development is not a style but an attitude of accepting the difference and responsibility of ours by proposing what needs to be done further for upholding the universal design concept of ambient media design.

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Gomes, Luis, Carlos Ramos, Aria Jozi, Bruno Serra, Lucas Paiva, and Zita Vale. "IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach." Future Internet 11, no. 3 (March 2, 2019): 58. http://dx.doi.org/10.3390/fi11030058.

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This paper presents IoH (Intelligence of Home), a platform developed to test some basic intelligent behaviors in Home context. Internet of Things, ambient intelligence and context awareness approaches motivated the development of IoH. The platform involves six layers, responsible by connectivity, persistency, unification, Internet of Things integration, subsystems integration and user interface. The integrated subsystems involve intelligent systems for light control, television brightness control, desk light control, persons counting and air conditioner control. The IoH platform is then tested for a real building, and results and conclusions are obtained. Different intelligent methods and technologies are used, form the use of a diversity of sensors, actuators, and controllers and processing units to a set of artificial intelligence approaches varying from machine learning and optimization algorithms to the use of sensor fusion and computer vision. The use of IoH day-by-day demonstrated an intelligent performance for the real building occupants.

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Ander, Veronika, Petr Cihelka, Jan Tyrychtr, and David Novák. "Towards Compromise User Experience Design in Ambient Intelligent Environment." Agris on-line Papers in Economics and Informatics 14, no. 2 (June 30, 2022): 3–13. http://dx.doi.org/10.7160/aol.2022.140201.

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Building, testing and evaluating UX for applications for Agricultural Ambient Intelligence Environments can be a difficult and time-consuming job. It can be an even longer and more challenging process due to their complexity and area of scope for complex intelligent systems. Many studies address the issue of UX design and evaluation of website user interface, mobiles, tangible equipment, wearable equipment and other, but it is necessary to look for UX deficiencies in all possible functions, every possible task. Depending on the structure of expert teams, experts’ opinions can vary broadly vary or may even contradict. This paper presents possibilities of use the Best-Compromise-Mean (BeCoMe) method for evaluation UX design. BeCoMe was not used for UX evaluation yet. Verification of whether the BeCoMe method is suitable for UX evaluation is carried out on a tablet using two prototypes of control panels of an intelligent environment.

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13

de Andrade, Norberto Nuno Gomes. "The “A.I.vatar”: Artificial Intelligent agents in the context of Ambient Intelligence." Journal of Ambient Intelligence and Smart Environments 3, no. 4 (2011): 363–70. http://dx.doi.org/10.3233/ais-2011-0123.

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14

Feng, Ling, Yuanping Li, and Lin Qiao. "Towards a Mission-Critical Ambient Intelligent Fire Victims Assistance System." International Journal of Ambient Computing and Intelligence 3, no. 4 (October 2011): 41–61. http://dx.doi.org/10.4018/jaci.2011100104.

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While various ambient computing and intelligence techniques have been used to assist human beings in different aspects of their daily lives and work, this paper investigates potential ambient intelligence support in mission-critical scenarios such as firefighting. The paper reviews state-of-the-art ubiquitous techniques and tools assisting firefighting. Based upon these great research results, the authors then report the design and implementation of an ambient intelligent fire victims assistance application. By sensing the physical environment and occupants in a fire building, the system suggests the safest and fastest route along which the building occupants could evacuate; and when escaping from the building is not possible, the system tries to calm down and inform the trapped ones an action list. The channels to convey the guide assistance include traditional lights, speakers, and occupants’ mobile phones (if existing). The empirical experiments show that ambient intelligence in such a fire response guide can help improve the egress time performance of building occupants. The presented ambient smart fire victims’ assistance system is supposed to work at an early stage of fire in a building. As a complement of existing firefighting techniques, it still faces a number of open questions to be resolved in the future.

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Callaghan, Vic, Achilles Kameas, Dolors Royo, Angelica Reyes, and Leandro Navarro. "The Fifth International Conference on Intelligent Environments (IE 09): A Report." AI Magazine 30, no. 4 (January 2, 2010): 117. http://dx.doi.org/10.1609/aimag.v30i4.2277.

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The development of intelligent environments is considered an important step towards the realization of the ambient intelligence vision. Intelligent environments are technologically augmented everyday spaces, which intuitively support human activity. The IE conferences traditionally provide a leading edge forum for researchers and engineers to present their latest research and to discuss future directions in the area of intelligent environments. This article briefly presents the content of the Fifth International Conference on Intelligent Environments (IE09), which was held July 20–21 at the Castelldefels campus, of the Technical University of Catalonia, near Barcelona, Spain.

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Falomir, Zoe. "Qualitative descriptors applied to ambient intelligent systems." Journal of Ambient Intelligence and Smart Environments 9, no. 1 (January 16, 2017): 21–39. http://dx.doi.org/10.3233/ais-160418.

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17

Hynes, Gearoid, Fergal Monaghan, Vinhtuan Thai, Thomas Strang, and David O'Sullivan. "SAGE: An Ambient Intelligent Framework for Manufacturing." IFAC Proceedings Volumes 39, no. 4 (2006): 339–43. http://dx.doi.org/10.3182/20060522-3-fr-2904.00054.

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18

Freitas, Carlos Filipe, António Meireles, Lino Figueiredo, Joao Barroso, Antonio Silva, and Carlos Ramos. "Context aware middleware in ambient intelligent environments." International Journal of Computational Science and Engineering 10, no. 4 (2015): 347. http://dx.doi.org/10.1504/ijcse.2015.070995.

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Op het Veld, Bert, Dennis Hohlfeld, and Valer Pop. "Harvesting mechanical energy for ambient intelligent devices." Information Systems Frontiers 11, no. 1 (February 26, 2009): 7–18. http://dx.doi.org/10.1007/s10796-009-9160-5.

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20

Boukharrou, Radja Radja, Jean-Michel Ilié, and Djamel Eddine Saidouni. "Time and Space Reasoning for Ambient Systems." International Journal of Ambient Computing and Intelligence 8, no. 3 (July 2017): 38–57. http://dx.doi.org/10.4018/ijaci.2017070103.

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This paper presents an algebraic language, called Time-AgLOTOS, to describe time-dependent behavior of intelligent agent for the design of Ambient Intelligence systems. This specification model provides a theoretical foundation for performing planning under timing constraints. Based on a true-concurrency semantics, a contextual model, called Spatio-Temporal Planning System (STPS), is developed to capture all possible evolutions of an agent plan including context changes. The STPS provides formal description of possible actions to perform supporting timing constraints, action duration and spatial information. This structure offers new possibilities and strategies for taking agent real-time decisions in context-awareness manner.

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Sanchez-Pi, Nayat, Luiz Andre Paes Leme, and Ana Cristina Bicharra Garcia. "Intelligent agents for alarm management in petroleum ambient." Journal of Intelligent & Fuzzy Systems 28, no. 1 (2015): 43–53. http://dx.doi.org/10.3233/ifs-141198.

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Curran, Kevin, Denis McFadden, and Ryan Devlin. "The Role of Augmented Reality within Ambient Intelligence." International Journal of Ambient Computing and Intelligence 3, no. 2 (April 2011): 16–34. http://dx.doi.org/10.4018/jaci.2011040102.

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An Augmented Reality (AR) is a technology which provides the user with a real time 3D enhanced perception of a physical environment with addition virtual elements—either virtual scenery, information regarding surroundings, other contextual information—and is also capable of hiding or replacing real structures. With Augmented Reality applications becoming more advanced, the ways the technology can be viably used is increasing. Augmented Reality has been used for gaming several times with varying results. AR systems are seen by some as an important part of the ambient intelligence landscape. Therefore, the authors present several types of augmentation applications of AR in the domestic, industrial, scientific, medicinal, and military sectors which may benefit future ambient intelligent systems.

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Naimavičiene, Jurga, Artūras Kaklauskas, and Andrius Gulbinas. "MULTI-VARIANT DECISION SUPPORT E‐SYSTEM FOR DEVICE AND KNOWLEDGE BASED INTELLIGENT RESIDENTIAL ENVIRONMENT." Technological and Economic Development of Economy 13, no. 4 (December 31, 2007): 303–13. http://dx.doi.org/10.3846/13928619.2007.9637816.

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Intelligent housing is a novelty in Lithuania yet. Such housing is not popular in our country. Specialists of automation claim that such situation occurred not only because people lack knowledge but also because the concept of intelligent housing is interpreted erroneously (most people think that remotely controlled door of garage, for instance, makes their housing intelligent). Intelligent helpers started to emerge in households only recently. Intelligent ambient assisted environment model, created by authors, helps to evaluate intelligent ambient assisted environment by social, cultural, political, legal, economical, technological and environmental factors analysis. Basing on this model also ambient assisted environment supply and demand as well as various criteria evaluation, the system able to select the best intelligent devices alternatives accordingly to each family needs was created. Through analysis of separate parts of an existing household, it is possible to distinguish intelligent devices that I study, ie intelligent lock, intelligent robot‐cleaner, intelligent infant respiratory monitor, intelligent sentinel and intelligent keyboard. Users of intelligent devices are families of young people, who want to save time and who appreciate convenience and innovations. Advantages and benefits of devices used by families of young people are being analysed. In order to provide the best guarantee for rational selection of variants of intelligent devices, decisions must be based on the system of criteria which describes variants of intelligent devices, the decision Support system must reflect consumer requirements to the best possible extent, and the data provided in the system must be real and updated easily. Computer and internet technologies, multi‐variant evaluation methods as well as principles and requirements applicable to favourable residential environment are combined to achieve this goal.

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Duman, Hakan, Hani Hagras, and Victor Callaghan. "A multi-society-based intelligent association discovery and selection for ambient intelligence environments." ACM Transactions on Autonomous and Adaptive Systems 5, no. 2 (May 2010): 1–34. http://dx.doi.org/10.1145/1740600.1740603.

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Camacho, David, and Paulo Novais. "Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing." Journal of Ambient Intelligence and Humanized Computing 8, no. 2 (February 4, 2017): 155–56. http://dx.doi.org/10.1007/s12652-017-0454-z.

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Cinque, Marcello, Antonio Coronato, and Alessandro Testa. "On Dependability Issues in Ambient Intelligence Systems." International Journal of Ambient Computing and Intelligence 3, no. 3 (July 2011): 18–27. http://dx.doi.org/10.4018/jaci.2011070103.

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Ambient Intelligence (AmI) is the emerging computing paradigm used to build next-generation smart environments. It provides services in a flexible, transparent, and anticipative manner, requiring minimal skills for human-computer interaction. Recently, AmI is being adapted to build smart systems to guide human activities in critical domains, such as, healthcare, ambient assisted living, and disaster recovery. However, the practical application to such domains generally calls for stringent dependability requirements, since the failure of even a single component may cause dangerous loss or hazard to people and machineries. Despite these concerns, there is still little understanding on dependability issues in Ambient Intelligent systems and on possible solutions. This paper provides an analysis of the AmI literature dealing with dependability issues and to propose an innovative architectural solution to such issues, based on the use of runtime verification techniques.

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Korzun, Dmitry G., Ilya Nikolaevskiy, and Andrei Gurtov. "Service Intelligence and Communication Security for Ambient Assisted Living." International Journal of Embedded and Real-Time Communication Systems 6, no. 1 (January 2015): 76–100. http://dx.doi.org/10.4018/ijertcs.2015010104.

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Mobile health (m-Health) scenarios and Internet of Things (IoT) technologies form an important direction for enhancing medical systems for Ambient Assisted Living (AAL). Yet current development meets with two challenges: 1) use of patient's health data with strong security guarantees in mobile network and resource-constrained assumptions and in emergency situations, 2) inclusion of personal data to the entire system for “smart” service construction and delivery. This paper presents a smart space based architectural model that adopts emerging IoT technologies to enable security of personal mobile data and their intelligent utilization in health services. To support the service intelligence, the authors employ the smart spaces approach with its prominent technologies adopted from IoT and Semantic Web. The intelligence and security solutions are considered symbiotic to present better user-experience, security level, and utility of a system.

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Søraker, Johnny Hartz, and Phillip Brey. "Ambient Intelligence and Problems with Inferring Desires from Behaviour." International Review of Information Ethics 8 (December 1, 2007): 7–12. http://dx.doi.org/10.29173/irie91.

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In this paper we will argue that many of the ethical problems raised by Ambient Intelligence stems from presupposing a behaviourist conception of the relation between human desires and behaviour. Insofar as Ambient Intelligence systems take overt, natural behaviour as input, they are likely to suffer from many of the same problems that have fuelled the widespread criticism of behaviourist explanations of human behav-iour. If these limitations of the technology are not sufficiently recognized, the technology is likely to be insuf-ficiently successful in supporting the needs and desires of human users. We will focus on four distinct chal-lenges that result from this behaviourist presupposition, all of which ought to be taken into consideration at the design stage: reciprocal adaptation, bias towards isolated use, culture-specific behaviour, and inability to manually configure the system. By considering these issues, our purpose is to raise awareness of the ethical problems that can arise because of intelligent user interfaces that rely on natural, overt behaviour.

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Lekova, Anna. "Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/262936.

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Ambient Intelligence (AmI) joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs) for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF) to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.

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Chen, Yunfei. "Performance of Ambient Backscatter Systems Using Reconfigurable Intelligent Surface." IEEE Communications Letters 25, no. 8 (August 2021): 2536–39. http://dx.doi.org/10.1109/lcomm.2021.3083110.

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Yayilgan, Sule Yildirim, Bernd Blobel, Françoise Petersen, Asbjørn Hovstø, Peter Pharow, Dag Waaler, and Younis Hijazi. "An Architectural Approach to Building Ambient Intelligent Travel Companions." International Journal of E-Health and Medical Communications 3, no. 3 (July 2012): 86–95. http://dx.doi.org/10.4018/jehmc.2012070107.

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In theory, persons with impairments including elderly have the same rights of taking part in everyday life activities and society. However in practice, they are at risk of being excluded because of the great number of ICT solutions not addressing the needs of people with impairments. This paper describes a system which provides personalized services supporting people with impairments and patients travelling for medical reasons, work, social contacts, daily outdoor life activities, etc. In this paper, the authors focus on the scenarios, requirements, architecture, integration, requirements fulfillment, and conclusions of building an ambient intelligent travel companions.

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Heinroth, T., A. Kameas, G. Pruvost, L. Seremeti, Y. Bellik, and W. Minker. "Human-computer interaction in next generation ambient intelligent environments." Intelligent Decision Technologies 5, no. 1 (January 5, 2011): 31–46. http://dx.doi.org/10.3233/idt-2011-0096.

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Tiwari, Shailesh, Munesh Trivedi, and Mohan L. Kohle. "Special issue on ambient advancements in intelligent computational sciences." Journal of Intelligent & Fuzzy Systems 35, no. 2 (August 26, 2018): 1207–8. http://dx.doi.org/10.3233/jifs-169665.

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Alam, Md Golam Rabiul, Rim Haw, Sung Soo Kim, Md Abul Kalam Azad, Sarder Fakhrul Abedin, and Choong Seon Hong. "EM-Psychiatry: An Ambient Intelligent System for Psychiatric Emergency." IEEE Transactions on Industrial Informatics 12, no. 6 (December 2016): 2321–30. http://dx.doi.org/10.1109/tii.2016.2610191.

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Sheng, Quan Z., Wei Emma Zhang, and Elhadi Shakshuki. "Practices and applications in ambient and intelligent information systems." Personal and Ubiquitous Computing 21, no. 6 (July 5, 2017): 1039–40. http://dx.doi.org/10.1007/s00779-017-1037-x.

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Doctor, F., H. Hagras, and V. Callaghan. "A Fuzzy Embedded Agent-Based Approach for Realizing Ambient Intelligence in Intelligent Inhabited Environments." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 35, no. 1 (January 2005): 55–65. http://dx.doi.org/10.1109/tsmca.2004.838488.

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OLARU, ANDREI, and CRISTIAN GRATIE. "AGENT-BASED, CONTEXT-AWARE INFORMATION SHARING FOR AMBIENT INTELLIGENCE." International Journal on Artificial Intelligence Tools 20, no. 06 (December 2011): 985–1000. http://dx.doi.org/10.1142/s0218213011000498.

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In a future vision of Ambient Intelligence — or AmI — our surrounding environment will integrate a pervasive, interconnected network of sensors, intelligent appliances and computer-like devices. This implies, on the one hand, hardware and interface related issues, and, on the other hand, a layer of context-aware services that manages the large quantities of information generated throughout a system formed mostly of devices with limited capabilities. This paper presents the first steps toward the realization of the AmIciTy framework: a multi-agent system that relies on local interaction and the self-organization of agents, having as purpose the context-aware sharing of pieces of information. The paper presents the structure of the system, the design of the agents, the manner of building scenarios, experiments and the evaluation of a prototype.

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Amador-Domínguez, Elvira, Emilio Serrano, Daniel Manrique, and Juan F. De Paz. "Prediction and Decision-Making in Intelligent Environments Supported by Knowledge Graphs, A Systematic Review." Sensors 19, no. 8 (April 13, 2019): 1774. http://dx.doi.org/10.3390/s19081774.

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Ambient Intelligence is currently a lively application domain of Artificial Intelligence and has become the central subject of multiple initiatives worldwide. Several approaches inside this domain make use of knowledge bases or knowledge graphs, both previously existing and ad hoc. This form of representation allows heterogeneous data gathered from diverse sources to be contextualized and combined to create relevant information for intelligent systems, usually following higher level constraints defined by an ontology. In this work, we conduct a systematic review of the existing usages of knowledge bases in intelligent environments, as well as an in-depth study of the predictive and decision-making models employed. Finally, we present a use case for smart homes and illustrate the use and advantages of Knowledge Graph Embeddings in this context.

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Noor, Ahmed K. "Preparing for the Intelligence Era." Mechanical Engineering 132, no. 11 (November 1, 2010): 24–29. http://dx.doi.org/10.1115/1.2010-nov-1.

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This article provides an overview of various technologies meant for developing intelligent digital engineering ecosystems. The article also highlights the need to develop new methods for combining visual and haptic impressions to provide a high degree of immersion, and enable touching and moving virtual objects. Some current activities are devoted to studying and improving the relation between humans and computing devices. One of these activities is the Human–Computer Confluence, an interdisciplinary initiative funded by the European Commission, as part of its Future and Emerging Technologies program. Intelligent digital engineering ecosystems will closely link research and academic institutions with industry and policymakers, and will facilitate the networking of innovation knowledge. They will enable the widespread adoption of augmented reality; the seamless integration of virtual and physical worlds; establishing a new baseline for human functionality; and experimentation with novel modalities of expression. They will accelerate advances in neurocomputation, artificial general intelligence, and other novel technologies, as well as the synergistic union of the human brain, intelligent computing devices, and the ambient intelligence environment to usher in the Intelligence Era.

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Agrawal, Vikas, Christopher Archibald, Mehul Bhatt, Hung Bui, Diane J. Cook, Juan Cortés, Christopher Geib, et al. "The AAAI-13 Conference Workshops." AI Magazine 34, no. 4 (September 9, 2013): 108–15. http://dx.doi.org/10.1609/aimag.v34i4.2511.

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The AAAI-13 Workshop Program, a part of the 27th AAAI Conference on Artificial Intelligence, was held Sunday and Monday, July 14‚Äì15, 2013 at the Hyatt Regency Bellevue Hotel in Bellevue, Washington, USA. The program included 12 workshops covering a wide range of topics in artificial intelligence, including Activity Context-Aware System Architectures (WS-13-05); Artificial Intelligence and Robotics Methods in Computational Biology (WS-13-06); Combining Constraint Solving with Mining and Learning (WS-13-07); Computer Poker and Imperfect Information (WS-13-08); Expanding the Boundaries of Health Informatics Using Artificial Intelligence (WS-13-09); Intelligent Robotic Systems (WS-13-10); Intelligent Techniques for Web Personalization and Recommendation (WS-13-11); Learning Rich Representations from Low-Level Sensors (WS-13-12); Plan, Activity, and Intent Recognition (WS-13-13); Space, Time, and Ambient Intelligence (WS-13-14); Trading Agent Design and Analysis (WS-13-15); and Statistical Relational Artificial Intelligence (WS-13-16).

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Sengupta, Diganta. "Taxonomy on Ambient Computing." International Journal of Ambient Computing and Intelligence 11, no. 1 (January 2020): 1–33. http://dx.doi.org/10.4018/ijaci.2020010101.

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The rise of Internet-of-Things, Cloud infrastructure, and intelligent home solutions has resulted in the growth of Ambient Computing over the past decade. This article is an attempt to cluster the multi-dimensional research in ambient computing into relevant nodes. The author proposes a taxonomy in ambient computing, creating a logical arrangement of such nodes. An algorithm based on the cosine similarity function for calculating the distance between two ‘author keywords' has been used to spawn the inter-nodal relationships. The vocabulary for the research has been generated from IEEE Xplore taking into consideration the relevant journal publications. The taxonomy will guide researchers to the relevant published literature about a certain area of interest instead of exhaustive search into a plethora of published research in ambient computing. The taxonomy exhibits exponential growth of research in ambient computing over the last three years.

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Sernani, Paolo, Andrea Claudi, and Aldo Franco Dragoni. "Combining Artificial Intelligence and NetMedicine for Ambient Assisted Living." International Journal of E-Health and Medical Communications 6, no. 4 (October 2015): 62–76. http://dx.doi.org/10.4018/ijehmc.2015100105.

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World population is shifting towards older ages: according to recent estimates there will be 1.5 billion people over 65 years old in 2050. Local governments, international institutions, care organizations and industry are fostering the research community to find solutions to face the unprecedented challenges raised by population ageing. A combination of Artificial Intelligence and NetMedicine could be ideal to face these challenges: they provide the means to develop an intelligent system and simultaneously to distribute it over a network, allowing the communication over the internet, if needed. Hence, the authors present a Multi-Agent Architecture for Ambient Assisted Living (AAL): it is the model for a system to manage a distributed sensor network composed by ambient and biometric sensors. The system should analyse data and pro-actively decide to trigger alarms if anomalies are detected. The authors tested the architecture implementing a prototypical Multi-Agent System (MAS), based on Belief-Desire-Intention (BDI) paradigm: the Virtual Carer.

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Homola, Martin, Theodore Patkos, Giorgos Flouris, Ján Šefránek, Alexander Šimko, Jozef Frtús, Dimitra Zografistou, and Martin Baláž. "Resolving conflicts in knowledge for ambient intelligence." Knowledge Engineering Review 30, no. 5 (October 30, 2015): 455–513. http://dx.doi.org/10.1017/s0269888915000132.

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AbstractAmbient intelligence (AmI) proposes pervasive information systems composed of autonomous agents embedded within the environment who, in orchestration, complement human activity in an intelligent manner. As such, it is an interesting and challenging application area for many computer science fields and approaches. A critical issue in such application scenarios is that the agents must be able to acquire, exchange, and evaluate knowledge about the environment, its users, and their activities. Knowledge populated between the agents in such systems may be contextually dependent, ambiguous, and incomplete. Conflicts may thus naturally arise, that need to be dealt with by the agents in an autonomous way. In this survey, we relate AmI to the area of knowledge representation and reasoning (KR), where conflict resolution has been studied for a long time. We take a look at a number of KR approaches that may be applied: context modelling, multi-context systems, belief revision, ontology evolution and debugging, argumentation, preferences, and paraconsistent reasoning. Our main goal is to describe the state of the art in these fields, and to draw attention of researchers to important theoretical issues and practical challenges that still need to be resolved, in order to reuse the results from KR in AmI systems or similar complex and demanding applications.

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Liu, Suying, Chenfei Jiao, and Chong Zhu. "Tunnel Lighting Intelligent Control System Based on Ambient Light Ratio." Journal of Physics: Conference Series 1865, no. 2 (April 1, 2021): 022019. http://dx.doi.org/10.1088/1742-6596/1865/2/022019.

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Idrees, Sahar, Xiaolun Jia, Salman Durrani, and Xiangyun Zhou. "Design of Intelligent Reflecting Surface (IRS)-Boosted Ambient Backscatter Systems." IEEE Access 10 (2022): 65000–65010. http://dx.doi.org/10.1109/access.2022.3184017.

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Xiang Li, Ling Feng, Lizhu Zhou, and Yuanchun Shi. "Learning in an Ambient Intelligent World: Enabling Technologies and Practices." IEEE Transactions on Knowledge and Data Engineering 21, no. 6 (June 2009): 910–24. http://dx.doi.org/10.1109/tkde.2008.143.

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Becerra, Gabriel, and Rob Kremer. "Ambient intelligent environments and environmental decisions via agent-based systems." Journal of Ambient Intelligence and Humanized Computing 2, no. 3 (June 12, 2011): 185–200. http://dx.doi.org/10.1007/s12652-011-0056-0.

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Hakim, Amira, Abdelkrim Amirat, and Mourad Chabane Oussalah. "Non-intrusive contextual dynamic reconfiguration of ambient intelligent IoT systems." Journal of Ambient Intelligence and Humanized Computing 11, no. 4 (November 14, 2018): 1365–76. http://dx.doi.org/10.1007/s12652-018-1127-2.

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Costa, Angelo, Jaime A. Rincon, Carlos Carrascosa, Vicente Julian, and Paulo Novais. "Emotions detection on an ambient intelligent system using wearable devices." Future Generation Computer Systems 92 (March 2019): 479–89. http://dx.doi.org/10.1016/j.future.2018.03.038.

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Palacín, Jordi, Eduard Clotet, Dani Martínez, Javier Moreno, and Marcel Tresanchez. "Automatic Supervision of Temperature, Humidity, and Luminance with an Assistant Personal Robot." Journal of Sensors 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/1480401.

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Smart environments and Ambient Intelligence (AmI) technologies are defining the future society where energy optimization and intelligent management are essential for a sustainable advance. Mobile robotics is also making an important contribution to this advance with the integration of sensors and intelligent processing algorithms. This paper presents the application of an Assistant Personal Robot (APR) as an autonomous agent for temperature, humidity, and luminance supervision in human-frequented areas. The robot multiagent capabilities allow gathering sensor information while exploring or performing specific tasks and then verifying human comfortability levels. The proposed methodology creates information maps with the distribution of temperature, humidity, and luminance and interprets such information in terms of comfort and warns about corrective actuations if required.

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