Relevant bibliographies by topics / Ambient intelligent

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Ambient intelligent'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 March 2023

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Journal articles on the topic "Ambient intelligent"

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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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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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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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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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Dissertations / Theses on the topic "Ambient intelligent"

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Akhlaghinia, M. J. "Occupancy monitoring and prediction in ambient intelligent environment." Thesis, Nottingham Trent University, 2010. http://irep.ntu.ac.uk/id/eprint/281/.

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Occupancy monitoring and prediction as an influential factor in the extraction of occupants' behavioural patterns for the realisation of ambient intelligent environments is addressed in this research. The proposed occupancy monitoring technique uses occupancy detection sensors with unobtrusive features to monitor occupancy in the environment. Initially the occupancy detection is conducted for a purely single-occupant environment. Then, it is extended to the multipleoccupant environment and associated problems are investigated. Along with the occupancy monitoring, it is aimed to supply prediction techniques with a suitable occupancy signal as the input which can enhance efforts in developing ambient intelligent environments. By predicting the occupancy pattern of monitored occupants, safety, security, the convenience of occupants, and energy saving can be improved. Elderly care and supporting people with health problems like dementia and Alzheimer disease are amongst the applications of such an environment. In the research, environments are considered in different scenarios based on the complexity of the problem including single-occupant and multiple-occupant scenarios. Using simple sensory devices instead of visual equipment without any impact on privacy and her/his normal daily activity, an occupant is monitored in a living or working environment in the single-occupant scenario. ZigBee wireless communication technology is used to collect signals from sensory devices such as motion detection sensors and door contact sensors. All these technologies together including sensors, wireless communication, and tagging are integrated as a wireless sensory agent. The occupancy data is then collected from different areas in the monitored environment by installing a wireless sensory agent in each area. In a multiple-occupant scenario, monitored occupants are tagged to support sensory signals in distinguishing them from nonmonitored occupants or visitors. Upon enabling the wireless sensory agents to measure the radio signal strength of received data from tags associated with occupants, wireless localising sensory agents are formed and used for occupancy data collection in the multiple-occupant scenario. After the data collection, suitable occupancy time-series are generated from the collected raw data by applying analysis and suitable occupancy signal representation methods, which make it possible to apply time-series predictors for the prediction of reshaped occupancy signal. In addition, an occupancy signal generator is proposed and implemented to generate sufficient occupancy signal data for choosing the best amongst the prediction techniques. After converting the occupancy of different areas in an environment to an occupancy timeseries, the occupancy prediction problem is solved by time-series analysis and prediction techniques for the single-occupant scenario. The proposed technique has made it possible to predict the occupancy signal for 530 seconds in a real environment and up to 900 seconds for a virtual environment. The occupancy signal generator created based on the proposed statistical model is proved to be able to generate different occupancy signals for different occupant profiles incorporating different environmental layouts. This can give a good understanding of the occupancy pattern in indoor spaces and the effect of the uncertainty factors in the occupancy time-series. In the multiple-occupant scenario, the tagging technology integrated with data acquisition system has made it possible to distinguish monitored occupants and separate their occupancy signals. Separated signals can then be treated as individual time-series for prediction. All the proposed techniques and models are tested and validated by real occupancy data collected from different environments.
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Doctor, Faiyaz. "Adaptive fuzzy embedded agent approaches for ambient intelligent environments." Thesis, University of Essex, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.542367.

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el, Sayed Mewafy Sherif. "Investigation into the creation of an ambient intelligent physiology measurement environment to facilitate modelling of the human wellbeing." Thesis, University of South Wales, 2014. https://pure.southwales.ac.uk/en/studentthesis/investigation-into-the-creation-of-an-ambient-intelligent-physiology-measurement-environment-to-facilitate-modelling-of-the-human-wellbeing(27f3cf96-357d-49fa-a19f-cf60e9ae0347).html.

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The elderly population worldwide has an increasing expectation of wellbeing and life expectancy. The monitoring of the majority of elderly people on an individual basis, in a medical sense, will not be a viable proposition in the future due to the projected numbers of individuals requiring such activity. The expectation is that the infrastructure available will not be adequate to meet all the anticipated requirements and subsequently people will have to live at home with inadequate care. A new global objective that aims towards enhancing the quality of life of the elderly is being supported by extensive research. This research has been taking place in the field of ambient intelligence (AmI), considering factors including more comfort, improved health, enhanced security for the elderly, and facilitating the living in their homes longer. Prior research has shown a need for accelerated expansion in the ambient intelligence domain. To that end this work presents a novel learning technique for intelligent agents that can be used in Ambient Intelligent Environments (AIEs). The main objective of this work is to add knowledge to the AmI domain and to explore the practical applications within this research field. The added knowledge is accomplished through the development of an ambient intelligent health care environment that allows a practical assessment of the human well-being to take place. This is achieved by transforming the elderly living environment into an intelligent pseudo robot within which they reside to better understand the human wellbeing. The system developed aims to provide evidence that a level of automated care is both possible and practical. This care is for those with chronic physical or mental disabilities who have difficulty in their interactions with standardised living spaces. The novel integrated hardware and software architecture provides personalised environmental monitoring. It also provides control facilities based on the patient‘s physical and emotional wellness in their home. Entitled Health Adaptive Online Emotion Fuzzy Agent (HAOEFA), the system provides a non-invasive, self-learning, intelligent controlling system that constantly adapts to the requirements of an individual. The system has the ability to model and learn the user behaviour in order to control the environment on their behalf. This is achieved with respect to the changing environmental conditions as well as the user‘s health and emotional states being detected. A change of emotion can have a direct impact on the system‘s control taking place in the environment. Thus HAOEFA combines an emotion recognition system within a fuzzy logic learning and adaptation based controller. The emotion recogniser detects the occupant‘s emotions upon the changes of the physiological data being monitored. In addition to acting as an output to the occupant‘s physiological changes, the detected emotion also acts as input to the whole situation being observed by HAOEFA. This allows HAOEFA to control the Glam i-HomeCare on the user‘s behalf with respect to their emotional status. The system developed incorporates real-time, continuous adaptations to facilitate any changes to the occupant‘s behaviour within the environment. It also allows the rules to be adapted and extended online, assisting a life-long learning technique as the environmental conditions change and the user behaviour adjusts with it. HAOEFA uses the fuzzy c-means clustering methodology for extracting membership functions (MFs) before building its set of fuzzy rules. These MFs together with the rules base constitute a major part of the proposed system. It has the ability to learn and model the individual human behaviour with respect to their emotional status. Following the provided literature review and the presentation of Fuzzy logic MFs (see section 3.3). The thesis presents two chosen unobtrusive self-learning techniques that are used in the development of the intelligent fuzzy system. Each approach combines an emotion recogniser with a fuzzy logic learning and adaptation based technique for systems that can be used in AIEs. A comparison of two different MFs designs is contrasted showing the impact they have on the system learning ability. A number of carefully designed experiments were performed by volunteers in the Glam i-HomeCare test-bed at the University of South Wales to examine the system‘s ability to learn the occupant‘s behaviour with respect to their health and emotional states. The experimental procedures were performed twice by each volunteer, while maintaining the same behavioural actions to compare how much the design of fuzzy membership functions can impact the learning process and the number of rules created by the system. Besides evaluating both systems‘ emotion recognition accuracies and comparing them to one another for each occupant, the empirical outcomes show the potential of the approach in assisting the extension of independent living. The results demonstrate how the type-1 fuzzy system both learnt and adapted to each occupant‘s behaviour with respect to their health and emotional state whilst assessing multiple environmental conditions.
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Kunnappilly, Ashalatha. "Formally Assured Intelligent Systems for Enhanced Ambient Assisted Living Support." Licentiate thesis, Mälardalens högskola, Inbyggda system, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-42922.

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Ambient Assisted Living (AAL) solutions are aimed to assist the elderly in their independent and safe living. During the last decade, the AAL field has witnessed a significant development due to advancements in Information and Communication Technologies, Ubiquitous Computing and Internet of Things. However, a closer look at the existing AAL solutions shows that these improvements are used mostly to deliver one or a few functions mainly of the same type (e.g. health monitoring functions). There are comparatively fewer initiatives that integrate different kinds of AAL functionalities, such as fall detection, reminders, fire alarms, etc., besides health monitoring, into a common framework, with intelligent decision-making that can thereby offer enhanced reasoning by combining multiple events.    To address this shortage, in this thesis, we propose two different categories of AAL architecture frameworks onto which different functionalities, chosen based on user preferences, can be integrated. One of them follows a centralized approach, using an intelligent Decision Support System (DSS), and the other, follows a truly distributed approach, involving multiple intelligent agents. The centralized architecture is our initial choice, due to its ease of development by combining multiple functionalities with a centralized DSS that can assess the dependency between multiple events in real time. While easy to develop, our centralized solution suffers from the well-known single point of failure, which we remove by adding a redundant DSS. Nevertheless, the scalability, flexibility, multiple user accesses, and potential self-healing capability of the centralized solution are hard to achieve, therefore we also propose a distributed, agent-based architecture as a second solution, to provide the community with two different AAL solutions that can be applied depending on needs and available resources. Both solutions are to be used in safety-critical applications, therefore their design-time assurance, that is, providing a guarantee that they meet functional requirements and deliver the needed quality-of-service, is beneficial.    Our first solution is a generic architecture that follows the design of many commercial AAL solutions with sensors, a data collector, DSS, security and privacy, database (DB) systems, user interfaces (UI), and cloud computing support. We represent this architecture in the Architecture Analysis and Design Language (AADL) via a set of component patterns that we propose. The advantage of using patterns is that they are easily re-usable when building specific AAL architectures. Our patterns describe the behavior of the components in the Behavioral Annex of AADL, and the error behavior in AADL's Error Annex. We also show various instantiations of our generic model that can be developed based on user requirements. To formally assure these solutions against functional, timing and reliability requirements, we show how we can employ exhaustive model checking using the state-of-art model checker, UPPAAL, and also statistical model-checking techniques with UPPAAL SMC, an extension of the UPPAAL model checker for stochastic systems, which can be employed in cases when exhaustive verification does not scale. The second proposed architecture is an agent-based architecture for AAL systems, where agents are intelligent entities capable of communicating with each other in order to decide on an action to take. Therefore, the decision support is now distributed among agents and can be used by multiple users distributed across multiple locations. Due to the fact that this solution requires describing agents and their interaction, the existing core AADL does not suffice as an architectural framework. Hence, we propose an extension to the core AADL language - The Agent Annex, with formal semantics as Stochastic Transition Systems, which allows us to specify probabilistic, non-deterministic and real-time AAL system behaviors. In order to formally assure our multi-agent system, we employ the state-of-art probabilistic model checker PRISM, which allows us to perform probabilistic yet exhaustive verification.   As a final contribution, we also present a small-scale validation of an architecture of the first category, with end users from three countries (Romania, Poland, Denmark). This work has been carried out with partners from the mentioned countries.    Our work in this thesis paves the way towards the development of user-centered, intelligent ambient assisted living solutions with ensured quality of service.
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Lidan, Hu. "An Intelligent Presentation System." Thesis, KTH, Kommunikationssystem, CoS, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-91852.

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The master thesis project - Personal video: An Intelligent Presentation System (IPS) - was conducted at the Department of Communication Systems, Royal Institute of Technology (KTH), Stockholm, Sweden. The focus of this thesis is designing, building, and evaluating an intelligent environment for giving presentations which makes all the technologies of the existing devices invisible to the presenter, i.e., to remove difficulties of configuration, compatibility, etc. from hindering the user from being able to give their presentation. IPS is an application in a hot research field - Ambient Intelligence (AmI) which is influenced by user – centered design. Therefore, the goal of IPS is to improve the user’s experience. As compared to a traditional presentation system, IPS integrating several independent applications hence improving the user’s efficiency and offering greater user friendliness. In this thesis, a prototype of IPS was designed which combines an online presentation room booking system (running on a context server), a CGI presentation control module (running on a presentation server), and a cross platform control panel (which could be running on a PC, laptop, PDA, cellular phone, etc.). This prototype realized our goals of providing an intelligent and comfortable environment for both the presenters and the system a dministrators.
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Gallissot, Mathieu. "Modéliser le concept de confort dans un habitat intelligent : du multisensoriel au comportement." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00738342.

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La notion de confort dans les habitats est une problématique majeure pour résoudre des problèmes écologiques (consommation et émissions des bâtiments), économiques (réduction de coûts d'exploitation) et sociaux (maintien et assistance à domicile) qui définissent le développement durable. Cependant, cette notion de confort est complexe, par le nombre de paramètres qu'elle intègre, paramètres à la fois humains (perception) et physiques (mesure). Notre étude vise à modéliser cette notion de confort dans un contexte d'habitat intelligent. L'habitat intelligent émerge depuis le début des années 2000, et se positionne en héritier de la domotique, bénéficiant des progrès technologiques illustrés par l'informatique ubiquitaire et l'intelligence artificielle, concepts formants l'intelligence ambiante. La première partie de notre étude consiste à définir l'habitat intelligent, en formalisant les acquis (domotique) et les problématiques de recherche, sous l'angle de la représentation de connaissances par les modèles. Notre approche du bâtiment intelligent nous à permis de définir un cadre d'interopérabilité : un intergiciel capable de concentrer les paramètres et commandes d'un environnement. Cette interopérabilité est nécessaire de par l'hétérogénéité des objets communicants qui composent un habitat : hétérogénéité des applications, des protocoles de communication, de savoir-faire et d'usages. Les travaux réalisés dans cette première partie de l'étude nous ont permis d'instrumenter une plate-forme d'expérimentation : la plateforme Domus. Ainsi, en reconstituant un appartement, et en le dotant d'objets communicants, nous avons pu mettre en œuvre, par le biais de l'interopérabilité, un environnement intelligent, environnement qui se caractérise par une forte densité d'information et une capacité de réaction. La réalisation de cette plate-forme est nécessaire pour aborder des thématiques diverses liées à l'habitat, comme le confort. En effet, l'intelligence ambiante apporte une nouvelle dimension dans ce cadre de recherche : l'ubiquité. La densité croissante de capteurs nous permet de collecter plus d'informations, non seulement sur l'environnement mais également sur l'utilisateur et son comportement, définissant ainsi une nouvelle approche du confort : le confort adaptatif. Les travaux sur l'étude du confort dans les bâtiments se focalisent sur le confort thermique. Dans nos travaux, nous avons voulu nous intéresser au confort multi-sensoriel. Celui-ci permet d'une part de prendre en compte l'ensemble des paramètres qui agrémentent un environnement (l'air, le son, la vue) mais permet également de nous intéresser aux effets sensoriels croisés que peuvent induire ces modalités sur l'occupant. Par exemple, on soupçonne la température d'éclairage (éclairage rouge/chaud, éclairage bleu/froid) d'avoir une incidence sur la perception thermique. Des expérimentations ont en effet démontré l'approche pratique et l'approche théorique de ces effets multi-sensoriels. La mise en place de notre cadre d'interopérabilité, en première partie, dans la plateforme Domus et les résultats de nos évaluations expérimentales, en seconde partie, sur le confort réalisés dans cette même plateforme, nous permettent de participer à la définition d'un " confort-mètre ", qui s'appuie à la fois sur les capteurs, les objets de l'habitat et la perception des habitants.
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Rivera-Illingworth, Fernando. "An embedded-agent approach to activity recognition in domestic ambient intelligent environments." Thesis, University of Essex, 2009. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.502218.

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Hu, Yunkai. "Ambient Backscatter and Reconfigurable Intelligent Surface Empowered Wireless Communications in Future 6G Networks." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/26679.

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In future wireless communication systems, a substantial proportion of devices will be connected to the Internet of Things (IoT) networks for data communications, which poses three critical challenges for designing IoT networks: cost efficiency, spectrum efficiency, and energy efficiency. Ambient backscatter communication (AmBC), a novel communication scheme that offers low-cost, spectrum-efficient, and energy-efficient data communications, has found itself a competitive solution for developing and deploying future IoT networks. In AmBC systems, the main design challenge is to decode the tag signals from the composite received signals. In this thesis, the author focuses on the transceiver design and performance analysis of the AmBC system by making the following contributions. Firstly, we design a machine learning-based detector to decode the tag signals for an AmBC system. The second focus of this thesis is to study the BER performance of the AmBC systems that utilize the RF source signals with error control coding. The ongoing developments of 5G wireless networks are continuously exposing some inherent limitations. Reconfigurable intelligent surface (RIS), a promising solution to overcome the limitations in current 5G wireless networks and enable the beyond 5G and future sixth-generation (6G) networks, has attracted increasing attention recently. In the third research focus, we investigate the performance of the RIS-assisted wireless system where the signal transmitted from the transmitter is protected by error control codes. We focus on deriving the analytical upper and lower bounds on the bit error probability of the RIS-assisted wireless system with LDPC-coded source signals. We further investigate the performance of the RIS-assisted wireless system with polar codes through simulations. In addition, we show that the deployment of RIS can enhance the system BER performance significantly by increasing the number of RIS reflecting elements.
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Gheisari, Masoud. "An ambient intelligent environment for accessing building information in facility management operations; A healthcare facility scenario." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/52967.

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The Architecture, Engineering, Construction, and Operations (AECO) industry is constantly searching for new methods for increasing efficiency and productivity. Facility managers, as a part of the owner/operator role, work in complex and dynamic environments where critical decisions are constantly made. This decision-making process and its consequent performance can be improved by enhancing Situation Awareness (SA) of the facility managers through new digital technologies. SA, as a user-centered approach for understanding facility managers’ information requirement, together with Mobile Augmented Reality (MAR) was used for developing an Ambient Intelligent (AmI) environment for accessing building information in facilities. Augmented Reality has been considered as a viable option to reduce inefficiencies of data overload by providing facility managers with an SA-based tool for visualizing their “real-world” environment with added interactive data. Moreover, Building Information Modeling (BIM) was used as the data repository of the required building information. A pilot study was done to study the integration between SA, MAR, and BIM. InfoSPOT (Information Surveyed Point for Observation and Tracking) was developed as a low-cost solution that leverage current AR technology, showing that it is possible to take an idealized BIM model and integrate its data and 3D information in an MAR environment. A within-subjects user participation experiment and analysis was also conducted to evaluate the usability of the InfoSPOT in facility management related practices. The outcome of statistical analysis (a one-way repeated measure ANOVA) revealed that on average the mobile AR-based environment was relatively seamless and efficient for all participants in the study. Building on the InfoSPOT pilot study, an in-depth research was conducted in the area of healthcare facility management, integrating SA, MAR, and BIM to develop an AmI environment where facility mangers’ information requirement would be superimposed on their real-word view of the facility they maintain and would be interactively accessible through current mobile handheld technology. This AmI environment was compared to the traditional approach of conducting preventive and corrective maintenance using paper-based forms. The purpose of this part of the research was to investigate the hypothesis of “bringing 3D BIM models of building components in an AR environment and making it accessible through handheld mobile devices would help the facility managers to locate those components easier and faster compared to facility managers’ paper-based approach”. The result of this study shows that this innovative application of AR and integrating it with BIM to enhance the SA has the potential to improve construction practices, and in this case, facility management.
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Chahuara, Quispe Pedro. "Contrôle intelligent de la domotique à partir d'informations temporelles multi sources imprécises et incertaines." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00957941.

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La Maison Intelligente est une résidence équipée de technologie informatique qui assiste ses habitant dans les situations diverses de la vie domestique en essayant de gérer de manière optimale leur confort et leur sécurité par action sur la maison. La détection des situations anormales est un des points essentiels d'un système de surveillance à domicile. Ces situations peuvent être détectées en analysant les primitives générées par les étages de traitement audio et par les capteurs de l'appartement. Par exemple, la détection de cris et de bruits sourds (chute d'un objet lourd) dans un intervalle de temps réduit permet d'inférer l'occurrence d'une chute. Le but des travaux de cette thèse est la réalisation d'un contrôleur intelligent relié à tous les périphériques de la maison capable de réagir aux demandes de l'habitant (par commande vocale) et de reconnaître des situations à risque ou détresse. Pour accomplir cet objectif, il est nécessaire de représenter formellement et raisonner sur des informations, le plus souvent temporelles, à des niveaux d'abstraction différents. Le principale défi est le traitement de l'incertitude, l'imprécision, et incomplétude, qui caractérisent les informations dans ce domaine d'application. Par ailleurs, les décisions prises par le contrôleur doivent tenir compte du contexte dans lequel une ordre est donné, ce qui nous place dans l'informatique sensible au contexte. Le contexte est composé des informations de haut niveau tels que la localisation, l'activité en cours de réalisation, la période de la journée. Les recherches présentées dans ce manuscrit peuvent être divisés principalement en trois axes: la réalisation des méthodes d'inférence pour acquérir les informations du contexte(notamment, la localisation de l'habitant y l'activité en cours) à partir des informations incertains, la représentation des connaissances sur l'environnement et les situations à risque, et finalement la prise de décision à partir des informations contextuelles. La dernière partie du manuscrit expose les résultats de la validation des méthodes proposées par des évaluations amenées à la plateforme expérimental Domus.
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Books on the topic "Ambient intelligent"

1

Montebello, Matthew. The Ambient Intelligent Classroom. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21882-9.

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Ravulakollu, Kiran Kumar, Mohammad Ayoub Khan, and Ajith Abraham, eds. Trends in Ambient Intelligent Systems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30184-6.

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Agents and ambient intelligence: Achievements and challenges in the intersection of agent technology and ambient intelligence. Amsterdam: IOS Press, 2012.

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Minker, Wolfgang. Advanced intelligent environments. Edited by SpringerLink (Online service). Dordrecht: Springer, 2009.

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Verhaegh, Wim, Emile Aarts, and Jan Korst, eds. Intelligent Algorithms in Ambient and Biomedical Computing. Dordrecht: Springer Netherlands, 2006. http://dx.doi.org/10.1007/1-4020-4995-1.

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Tobias, Heinroth, and SpringerLink (Online service), eds. Next Generation Intelligent Environments: Ambient Adaptive Systems. New York, NY: Springer Science+Business Media, LLC, 2011.

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Jacko, Julie A., ed. Human-Computer Interaction. Ambient, Ubiquitous and Intelligent Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02580-8.

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Spain) IET International Conference on Intelligent Environments (5th 2009 Barcelona. Intelligent environments 2009: Proceedings of the 5th International Conference on Intelligent Environments, Barcelona 2009. Amsterdam: IOS Press, 2009.

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Dorothy, Monekosso, Remagnino Paolo 1963-, and Kuno Yoshinori, eds. Intelligent environments: Methods, algorithms and applications. London: Springer, 2009.

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Athens, Greece) International Conference on Intelligent Environments (9th 2013. Workshop proceedings of the 9th International Conference on Intelligent Environments. Amsterdam: IOS Press, 2013.

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Book chapters on the topic "Ambient intelligent"

1

Vallverdú, Jordi. "Ambient Stupidity." In Trends in Ambient Intelligent Systems, 173–86. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30184-6_7.

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Montebello, Matthew. "The Ambient Intelligent Classroom." In Studies in Computational Intelligence, 93–121. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21882-9_6.

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Acampora, Giovanni, Vincenzo Loia, Michele Nappi, and Stefano Ricciardi. "Hybrid Computational Intelligence for Ambient Intelligent Environments." In Advances in Web Intelligence, 26–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11495772_5.

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Desertot, Mikael, Sylvain Lecomte, Christophe Gransart, and Thierry Delot. "Intelligent Transportation Systems." In Computer Science and Ambient Intelligence, 285–306. Hoboken, NJ USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118580974.ch13.

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Costa, Ângelo, José Carlos Castillo Montotya, Paulo Novais, Antonio Fernández-Caballero, and María Teresa López Bonal. "Sensor-Driven Intelligent Ambient Agenda." In Ambient Intelligence - Software and Applications, 19–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28783-1_3.

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Akashi, Osamu, Atsushi Terauchi, Kensuke Fukuda, Toshio Hirotsu, Mitsuru Maruyama, and Toshiharu Sugawara. "Detection and Diagnosis of Inter-AS Routing Anomalies by Cooperative Intelligent Agents." In Ambient Networks, 181–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11568285_16.

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Hagras, H., and C. Wagner. "Artefact Adaptation in Ambient Intelligent Environments." In Next Generation Intelligent Environments, 127–51. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-1299-1_4.

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Ivanecký, Jozef, Stephan Mehlhase, and Margot Mieskes. "An Intelligent House Control Using Speech Recognition with Integrated Localization." In Ambient Assisted Living, 51–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18167-2_4.

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Naticchia, Berardo, and Alberto Giretti. "On the Design of Intelligent Buildings for Ambient Assisted Living." In Ambient Assisted Living, 381–88. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01119-6_38.

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Fernández, Javier Martínez, Juan Carlos Augusto, Ralf Seepold, and Natividad Martínez Madrid. "Why Traders Need Ambient Intelligence." In Advances in Intelligent and Soft Computing, 229–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13268-1_32.

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Conference papers on the topic "Ambient intelligent"

1

van Doorn, Mark, Evert van Loenen, and Arjen P. de Vries. "Deconstructing Ambient Intelligence into Ambient Narratives: The Intelligent Shop Window." In 1st International ICST Conference on Ambient Media and Systems. ICST, 2008. http://dx.doi.org/10.4108/icst.ambisys2008.2872.

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Kynsilehto, Minna, and Thomas Olsson. "Intelligent ambient technology." In the 15th International Academic MindTrek Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2181037.2181055.

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Puteh, Saifullizam, Caroline Langensiepen, and Ahmad Lotfi. "Fuzzy ambient intelligence for intelligent office environments." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6250771.

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Cesta, A. "Intelligent supervision for ambient intelligence: customizing scheduling technology." In IEE Seminar on Intelligent Building Environments. IEE, 2005. http://dx.doi.org/10.1049/ic:20050241.

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Ramadan, Rabie A., Hani Hagras, Moustafa Nawito, Amr El Faham, and Bahaa Eldesouky. "The Intelligent Classroom: Towards an Educational Ambient Intelligence Testbed." In 2010 6th International Conference on Intelligent Environments (IE). IEEE, 2010. http://dx.doi.org/10.1109/ie.2010.70.

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De Silva, Varuna, Jamie Roche, Xiyu Shi, and Ahmet Kondoz. "IoT Driven Ambient Intelligence Architecture for Indoor Intelligent Mobility." In 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). IEEE, 2018. http://dx.doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00090.

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Ballestas, Caseysimone, Euiyoung Kim, Jesuël Lanoy, and Jules Janssens. "Design-Engineers’ Selection of Agency: Harm Mitigation in Ambient Intelligent Environments." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-91063.

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Abstract The computing paradigm where sensor and actuator technology work in tandem to track and act on events in real Euclidean space, known as ambient intelligence (AmI), is likely to become increasingly common due to the rapid maturation of computing technology. Installing AmI in the built environment creates ambient intelligent environments (AmIE), which strive to make the places we inhabit (invisibly) sensitive and responsive to our presence, needs, wants, and preferences. Given that built environments and the goings-on therein are complicated in an of them selves, implementing AmI for (increasingly) complicated tasks in (increasingly) complicated scenarios, increases the difficulty of managing the outcomes in AmIEs. Our previous research indicates that industry practitioners attribute the agency of AmI artifacts as responsible for these outcomes; especially when harm perpetuation is (one of) the outcome(s), which we codified as the Agency/Intelligence Axis [1]. Due to the nascence of AmI, research on best practices for the design-engineering of AmI is still emerging. This research seeks to add to this literature by evaluating our formerly identified Agency/Intelligence Axis in the context of AmIE through a case study of VyZee, a retail company working on transitioning their retail stores to “smart” stores. Our findings highlight that while VyZee seems largely unaware of any relationship between agency and perpetuating un-anticipated/-desired outcomes, they do implement an array of levels of AmI agency in their retail stores, and their justifications for their choices are presented in the discussion. Finally, coding the data revealed more nuance then previously documented in the Agency/Intelligence Axis, and a new Ambient Intelligent Agent Model, which suggests that AmI agents have six properties, is proposed.
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Chandrasekaran, K., I. R. Ramya, and R. Syama. "Ambi Graph: Modeling Ambient Intelligent System." In 2009 International Conference on Computer Engineering and Technology (ICCET). IEEE, 2009. http://dx.doi.org/10.1109/iccet.2009.203.

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van den Hoven, Elise, and Berry Eggen. "Personal souvenirs as ambient intelligent objects." In the 2005 joint conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1107548.1107583.

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Luyten, Kris, Chris Vandervelpen, and Karin Coninx. "Task modeling for ambient intelligent environments." In the 4th international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1122935.1122953.

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Reports on the topic "Ambient intelligent"

1

Sadeh, Norman M., Fabien L. Gandon, and Oh B. Kwon. Ambient Intelligence: The MyCampus Experience. Fort Belvoir, VA: Defense Technical Information Center, July 2005. http://dx.doi.org/10.21236/ada481799.

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Hushko, Serhii, Victoria Solovieva, Andrii Shaikan, lnesa Khvostina, and Serhii Semerikov, eds. IV International Scientific Congress “Society of Ambient Intelligence – 2021” (ISCSAI 2021). Kryvyi Rih, Ukraine, April 12-16, 2021. EDP Sciences, March 2021. http://dx.doi.org/10.31812/123456789/4354.

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