Relevant bibliographies by topics / Ambient intelligence: Smart environments

Contents

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

Academic literature on the topic 'Ambient intelligence: Smart environments'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Ambient intelligence: Smart environments"

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Augusto, Juan, and Paul Mccullagh. "Ambient Intelligence: Concepts and applications." Computer Science and Information Systems 4, no. 1 (2007): 1–27. http://dx.doi.org/10.2298/csis0701001a.

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Ambient Intelligence aims to enhance the way people interact with their environment to promote safety and to enrich their lives. A Smart Home is one such system but the idea extends to hospitals, public transport, factories and other environments. The achievement of Ambient Intelligence largely depends on the technology deployed (sensors and devices interconnected through networks) as well as on the intelligence of the software used for decision-making. The aims of this article are to describe the characteristics of systems with Ambient Intelligence, to provide examples of their applications and to highlight the challenges that lie ahead, especially for the Software Engineering and Knowledge Engineering communities. In particular we address system specification and verification for the former and knowledge acquisition from the vast amount of data collected for the latter. .
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SCHERMERHORN, PAUL, and MATTHIAS SCHEUTZ. "NATURAL LANGUAGE INTERACTIONS IN DISTRIBUTED NETWORKS OF SMART DEVICES." International Journal of Semantic Computing 02, no. 04 (2008): 503–24. http://dx.doi.org/10.1142/s1793351x08000579.

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Advances in sensing and networking hardware have made the prospect of ambient intelligence more realistic, but the challenge of creating a software framework suitable for ambient intelligence systems remains. We present ADE, the Agent Development Environment, a distributed agent infrastructure with built-in natural language processing capabilities connected to a sophisticated goal manager that controls access to the world via multiple server interfaces for sensing and actuating devices. Unlike other ambient intelligence infrastructures, ADE includes support for multiple autonomous robots integrated into the system. ADE allows developers of ambient intelligence environments to implement agents of varying complexity to meet the varying requirements of each scenario, and it provides facilities to ensure security and fault tolerance for distributed computing. Natural language processing is conducted incrementally, as utterances are acquired, allowing fast, accurate responses from system agents. We describe ADE and a sample of the many experiments and demonstrations conducted using the infrastructure, then an example architecture for a "smart home" is proposed to demonstrate ADE's utility as an infrastructure for ambient intelligence.
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Muñoz, Andrés, Jaehwa Park, Abdul M. Mouazen, Josenalde Barbosa de Oliveira, and Dimitros Moshou. "Smart environments and ambient intelligence in agricultural and environmental technology." Journal of Ambient Intelligence and Smart Environments 12, no. 5 (2020): 377–78. http://dx.doi.org/10.3233/ais-500576.

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Ribeiro, Fernando Reinaldo, and Rui José. "Smart Content Selection for Public Displays in Ambient Intelligence Environments." International Journal of Ambient Computing and Intelligence 5, no. 2 (2013): 35–55. http://dx.doi.org/10.4018/jaci.2013040103.

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A public display that is able to present the right information at the right time is a very compelling concept. However, realising or even approaching this ability to autonomously select appropriate content based on some interpretation of the surrounding social context represents a major challenge. This article provides an overview of the key challenges involved and an exploration of some of the main alternatives available. It also describes a novel place-based content adaptation system that autonomously selects from web sources the content deemed more relevant according to a dynamic place model. This model is based on a tag cloud that combines content suggestions expressed by multiple place visitors with those expressed by the place owner. Evaluation results have shown that a place tag cloud can provide a valuable approach to this issue and that people recognize and understand the sensitivity of the system to their demands.
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Bacciu, Davide, Maurizio Di Rocco, Mauro Dragone, Claudio Gallicchio, Alessio Micheli, and Alessandro Saffiotti. "An ambient intelligence approach for learning in smart robotic environments." Computational Intelligence 35, no. 4 (2019): 1060–87. http://dx.doi.org/10.1111/coin.12233.

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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 (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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Roy, Patrice C., Bruno Bouchard, Abdenour Bouzouane, and Sylvain Giroux. "Ambient Activity Recognition in Smart Environments for Cognitive Assistance." International Journal of Robotics Applications and Technologies 1, no. 1 (2013): 29–56. http://dx.doi.org/10.4018/ijrat.2013010103.

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In this paper, the authors investigate the challenging key issues that emerge from research in the field of ambient intelligence in smart environments, under the context of activity recognition. The authors clearly describe the specific functional needs inherent in cognitive assistance for effective activity recognition, and then the authors present the fundamental research that addresses this problem in such a context. This paper is more of a survey and an analysis of existing works that have been studied for potential integration into our laboratories, rather than a focused evaluation report. The authors’ objective is to identify gaps in the capabilities of current techniques and to suggest the most productive lines of research to address this complex issue. As such, the contribution is of both theoretical and practical significance.
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Jung, Ralf. "Smart sound environments: merging intentional soundscapes, nonspeech audio cues and ambient intelligence." Journal of the Acoustical Society of America 123, no. 5 (2008): 3935. http://dx.doi.org/10.1121/1.2936002.

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Dunne, Rob, Tim Morris, and Simon Harper. "A Survey of Ambient Intelligence." ACM Computing Surveys 54, no. 4 (2021): 1–27. http://dx.doi.org/10.1145/3447242.

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Ambient Intelligence (AmI) is the application and embedding of artificial intelligence into everyday environments to seamlessly provide assistive and predictive support in a multitude of scenarios via an invisible user interface. These can be as diverse as autonomous vehicles, smart homes, industrial settings, and healthcare facilities—referred to as Ambient Assistive Living. This survey gives an overview of the field; defines key terms; discusses social, cultural, and ethical issues; and outlines the state of the art in AmI technology, and where opportunities for further research exist. We guide the reader through AmI from its inception more than 20 years ago, focussing on the important topics and research achievements of the past 10 years since the last major survey, before finally detailing the most recents research trends and forecasting where this technology is likely to develop. This survey covers domains, use cases, scenarios, and datasets; cultural concerns and usability issues; security, privacy, and ethics; interaction and recognition; prediction and intelligence; and hardware, infrastructure, and mobile devices. This survey serves as an introduction for researchers and the technical layperson into the topic of AmI and identifies notable opportunities for further research.
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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 (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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Dissertations / Theses on the topic "Ambient intelligence: Smart environments"

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Surie, Dipak. "Egocentric interaction for ambient intelligence." Doctoral thesis, Umeå universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-50822.

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Ambient intelligence refers to the vision of computationally augmented everyday environments that are sensitive, adaptive and responsive to humans and intelligently support their daily lives. Ambient ecologies are the infrastructures of ambient intelligence. To enable system developers to frame and manage the dynamic and complex interaction of humans with ambient ecologies consisting of a mixture of physical (real) and virtual (digital) objects, novel interaction paradigms are needed. Traditional interaction paradigms like the WIMP (windows, icon, menus, and pointing devices) paradigm for desktop computing operate in a closed world, unaware of the physical, social and cultural context. They restrict human perception and action to screen, mouse and keyboard with the assumption that human attention will be fully devoted to interaction with the computer. Emerging interaction paradigms for ambient intelligence are typically centered on specific devices, specific computing environments or specific human capabilities. Also, many of them are driven by technological advancements rather than viewing the human agent as their starting point. A principled, theoretical approach centered in the individual human agent, their situation and activities that are comprehensive and integrated while at the same time instrumental in the design of ambient ecologies has been lacking. This thesis introduces egocentric interaction as an approach towards the modeling of ambient ecologies with the distinguishing feature of taking the human agent’s body, situation and activities as center of reference, as opposed to the more common device-centric approaches in facilitating human-environment interaction. Egocentric interaction is encapsulated in a number of assumptions and principles such as situatedness, the proximity principle, the physical-virtual equity principle, perception and action instead of “input” and “output,” and activity-centeredness. A situative space model is proposed based on some of these principles. It is intended to capture what a specific human agent can perceive and not perceive, reach and not reach at any given moment in time. The situative space model is for the egocentric interaction paradigm what the virtual desktop is for the WIMP interaction paradigm: more or less everything of interest to a specific human agent is assumed and supposed to happen here. In addition, the conception and implementation of the easy ADL ecology based on egocentric interaction, comprising of smart objects, a personal activity-centric middleware, ambient intelligence applications aimed at everyday activity support, and a human agent literally in the middle of it all is described. The middleware was developed to address important challenges in ambient intelligence: (1) tracking and managing smart objects; (2) tracking a human agent’s situative spaces; (3) recognizing human activities and actions; (4) managing and facilitating human-environment interaction; and (5) to ease up the development of ambient intelligence applications. The easy ADL ecology was first simulated in immersive virtual reality, and then set up physically as a living laboratory to evaluate: (1) the technological and technical performance of individual middleware components, (2) to perform a user experience evaluation assessing various aspects of user satisfaction in relation to the support offered by the easy ADL ecology, and (3) to use it as a research test bed for addressing challenges in ambient intelligence. While it is problematic to directly compare the “proof-of-concept” easy ADL ecology with related research efforts, it is clear from the user experience evaluation that the subjects were positive with the services it offered.<br>easy ADL project
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Serral, Asensio Estefanía. "Automating Routine Tasks in Smart Environments. A Context-aware Model-driven Approach." Doctoral thesis, Universitat Politècnica de València, 2011. http://hdl.handle.net/10251/11550.

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Ubiquitous and Pervasive computing put forth a vision where environments are enriched with devices that provide users with services to serve them in their everyday lives. The building of such environments has the final objective of automating tedious routine tasks that users must perform every day. This automation is a very desirable challenge because it can considerably reduce resource consumption and improve users' quality of life by 1) making users' lives more comfortable, eficient, and productive, and 2) helping them to stop worrying and wasting time in performing tasks that need to be done and that they do not enjoy. However, the automation of user tasks is a complicated and delicate matter because it may bother users, interfere in their goals, or even be dangerous. To avoid this, tasks must be automated in a non-intrusive way by attending to users' desires and demands. This is the main goal of this thesis, that is, to automate the routine tasks that users want the way they want them. To achieve this, we propose two models of a high level of abstraction to specify the routines to be automated. These models provide abstract concepts that facilitate the participation of end-users in the model specification. In addition, these models are designed to be machine-processable and precise-enough to be executable models. Thus, we provide a software infrastructure that is capable of automating the specified routines by directly interpreting the models at runtime. Therefore, the routines to be automated are only represented in the models. This makes the models the primary means to understand, interact with, and modify the automated routines. This considerably facilitates the evolution of the routines over time to adapt them to changes in user behaviour. Without this adaptation, the automation of the routines may not only become useless for end-users but may also become a burden on them instead of being a help in their daily life.<br>Serral Asensio, E. (2011). Automating Routine Tasks in Smart Environments. A Context-aware Model-driven Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11550<br>Palancia
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Ramoly, Nathan. "Contextual integration of heterogeneous data in an open and opportunistic smart environment : application to humanoid robots." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLL003/document.

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L'association de robots personnels et d’intelligences ambiantes est une nouvelle voie pour l’aide à domicile. Grâce aux appareils intelligents de l'environnement, les robots pourraient fournir un service de haute qualité. Cependant, des verrous existent pour la perception, la cognition et l’action.En effet, une telle association cause des problèmes de variétés, qualités et conflits, engendrant des données hétérogènes et incertaines. Cela complique la perception du contexte et la cognition, i.e. le raisonnement et la prise de décision. La connaissance du contexte est utilisée par le robot pour effectuer des actions. Cependant, il se peut qu’il échoue, à cause de changements de contexte ou par manque de connaissance. Ce qui annule ou retarde son plan. La littérature aborde ces sujets, mais n’offre aucune solution viable et complète. Face à ces verrous, nous avons proposé des contributions, autour à la fois du raisonnement et de l’apprentissage. Nous avons d’abord conçu un outil d'acquisition de contexte qui gère et modélise l’incertitude. Puis, nous avons proposé une technique de détection de situations anormales à partir de données incertaines. Ensuite, un planificateur dynamique, qui considère les changements de contexte, a été proposé. Enfin, nous avons développé une méthode d'apprentissage par renforcement et expérience pour éviter proactivement les échecs.Toutes nos contributions ont été implémentées et validées via simulation ou à l’aide d’un robot dans une plateforme d’espaces intelligents<br>Personal robots associated with ambient intelligence are an upcoming solution for domestic care. In fact, helped with devices dispatched in the environment, robots could provide a better care to users. However, such robots are encountering challenges of perception, cognition and action.In fact, such an association brings issues of variety, data quality and conflicts, leading to the heterogeneity and uncertainty of data. These are challenges for both perception, i.e. context acquisition, and cognition, i.e. reasoning and decision making. With the knowledge of the context, the robot can intervene through actions. However, it may encounter task failures due to a lack of knowledge or context changes. This causes the robot to cancel or delay its agenda. While the literature addresses those topics, it fails to provide complete solutions. In this thesis, we proposed contributions, exploring both reasoning and learning approaches, to cover the whole spectrum of problems. First, we designed novel context acquisition tool that supports and models uncertainty of data. Secondly, we proposed a cognition technique that detects anomalous situation over uncertain data and takes a decision in accordance. Then, we proposed a dynamic planner that takes into consideration the last context changes. Finally, we designed an experience-based reinforcement learning approach to proactively avoid failures.All our contributions were implemented and validated through simulations and/or with a small robot in a smart home platform
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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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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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Al-Ashraf, Samir Daniel, and Zeeshan Hussain Bhatti. "A proposal of a smart home platform for better home entertainment experience." Thesis, Malmö högskola, Fakulteten för teknik och samhälle (TS), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20839.

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Smart home is a topic that emerged in the 90s to improve the quality of human life. The evolutions of ambient intelligence, recent technology advancements, internet, and smart devices have had a large impact in smart home environment. In the traditional smart home environment, devices are connected physically in the environment and there are interoperability issues between the devices, because the environment is heterogeneous and the devices do not allow to communicate with the outside world such as the internet.In this master thesis we propose a conceptual design of a platform for better home entertainment experience. Smart phone, smart TV and a personal computer are the most important devices in this platform design. The platform provides a high degree of interaction and integration among devices within the environment. The proposed platform model helps software architects and engineers to have an early involvement in the design process. We proposed the platform to be implemented with the help of hybrid cloud computing model. Our suggested platform design is able to overcome the deficiencies of the previous models and approaches in this domain. We conducted direct interviews with seven computer science teachers at Malmö University for the evaluation of our platform design. The results show that the platform design can be physically implemented with the specified devices, the clouds are better than the traditional approaches and hybrid cloud model is more acceptable in terms of security and economy. We encourage software architects, developers and project supervisors to adopt this proposed platform model in physical smart home environment.
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Hellenschmidt, Michael. "Realisierung der ambient intelligence Software-Infrastruktur und Entwicklungsumgebung für selbstorganisierende multimediale Ensembles in Ambient-intelligence-Umgebungen." Saarbrücken VDM Verlag Dr. Müller, 2007. http://d-nb.info/988827433/04.

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Zugl.: Darmstadt, Techn. Univ., Diss., 2007 u.d.T.: Hellenschmidt, Michael: Software-Infrastruktur und Entwicklungsumgebung für selbstorganisierende multimediale Ensembles in Ambient-Intelligence-Umgebungen<br>Hergestellt on demand
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Milosevic, Bojan <1983&gt. "Technologies for Ambient intelligence: from Smart Objects to Sensor Networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5838/.

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n the last few years, the vision of our connected and intelligent information society has evolved to embrace novel technological and research trends. The diffusion of ubiquitous mobile connectivity and advanced handheld portable devices, amplified the importance of the Internet as the communication backbone for the fruition of services and data. The diffusion of mobile and pervasive computing devices, featuring advanced sensing technologies and processing capabilities, triggered the adoption of innovative interaction paradigms: touch responsive surfaces, tangible interfaces and gesture or voice recognition are finally entering our homes and workplaces. We are experiencing the proliferation of smart objects and sensor networks, embedded in our daily living and interconnected through the Internet. This ubiquitous network of always available interconnected devices is enabling new applications and services, ranging from enhancements to home and office environments, to remote healthcare assistance and the birth of a smart environment. This work will present some evolutions in the hardware and software development of embedded systems and sensor networks. Different hardware solutions will be introduced, ranging from smart objects for interaction to advanced inertial sensor nodes for motion tracking, focusing on system-level design. They will be accompanied by the study of innovative data processing algorithms developed and optimized to run on-board of the embedded devices. Gesture recognition, orientation estimation and data reconstruction techniques for sensor networks will be introduced and implemented, with the goal to maximize the tradeoff between performance and energy efficiency. Experimental results will provide an evaluation of the accuracy of the presented methods and validate the efficiency of the proposed embedded systems.
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Dobrucki, Mikołaj. "Applications of Artificial Intelligence in Lighting Systems for Home Environments." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23548.

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Artificial Intelligence, being recently one of the most popular topics in technology, has been in a spotlight of Interaction Design for a long time. Despite its success in software and business-oriented cases, the adoption of Artificial Intelligence solutions in home environments still remains relatively low. This study reflects on the key reasons for the low penetration of AI-based solutions in private households and formulates design considerations for possible further developments in this area with a focus on artificial light sources. The design considerations are based on literature review and studies of multiple home environments gathered through qualitative interviews and context mapping exercises. Health influence of lighting, multi-user interactions, and privacy-related and ethical concerns are taken into account as the key factors. The considerations have been validated with participants of the study through user testing sessions of a digital prototype that virtualises a home environment and explores some of the common light usage scenarios. The study argues that despite multiple efforts in this direction during the past three decades, the future of Artificial Intelligence in connected, intelligent homes does not lie in smart, autonomous systems. Instead, Artificial Intelligence can be arguably used to simplify and contextualise interactions between humans and their home environments as well as foster the development of parametric solutions for private households.
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Durango, Melisa de Jesus Barrera. "SIRAH : sistema de reconhecimento de atividades humanas e avaliação do equilibrio postural /." Ilha Solteira, 2017. http://hdl.handle.net/11449/151317.

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Orientador: Alexandre César Rodrigues da Silva<br>Resumo: O reconhecimento de atividades humanas abrange diversas técnicas de classificação que permitem identificar padrões específicos do comportamento humano no momento da ocorrência. A identificação é realizada analisando dados gerados por diversos sensores corporais, entre os quais destaca-se o acelerômetro, pois responde tanto à frequência como à intensidade dos movimentos. A identificação de atividades é uma área bastante explorada. Porém, existem desafios que necessitam ser superados, podendo-se mencionar a necessidade de sistemas leves, de fácil uso e aceitação por parte dos usuários e que cumpram com requerimentos de consumo de energia e de processamento de grandes quantidades de dados. Neste trabalho apresenta-se o desenvolvimento do Sistema de Reconhecimento de atividades Humanas e Avaliação do Equilíbrio Postural, denominado SIRAH. O sistema está baseado no uso de um acelerômetro localizado na cintura do usuário. As duas fases do reconhecimento de atividades são apresentadas, fase Offline e fase Online. A fase Offline trata do treinamento de uma rede neural artificial do tipo perceptron de três camadas. No treinamento foram avaliados três estudos de caso com conjuntos de atributos diferentes, visando medir o desempenho do classificador na diferenciação de 3 posturas e 4 atividades. No primeiro caso o treinamento foi realizado com 15 atributos, gerados no domínio do tempo, com os que a rede neural artificial alcançou uma precisão de 94,40%. No segundo caso foram gerados 34 ... (Resumo completo, clicar acesso eletrônico abaixo)<br>Doutor
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Books on the topic "Ambient intelligence: Smart environments"

1

Handbook of ambient intelligence and smart environments. Springer, 2010.

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Nakashima, Hideyuki, Hamid Aghajan, and Juan Carlos Augusto, eds. Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0.

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Handbook of research on ambient intelligence and smart environments: Trends and perspective. Information Science Reference, 2011.

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Stephanidis, Constantine, and Michael Pieper, eds. Universal Access in Ambient Intelligence Environments. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-71025-7.

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Cook, Diane. Smart Environments. John Wiley & Sons, Ltd., 2004.

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Curran, Kevin. Innovative appllications of ambient intelligence: Advances in smart systems. Information Science Reference, 2012.

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

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

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Curran, Kevin. Pervasive and ubiquitous technology innovations for ambient intelligence environments. Information Science Reference, 2013.

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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. IOS Press, 2009.

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Book chapters on the topic "Ambient intelligence: Smart environments"

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Moreno, Francisco-Angel, Cipriano Galindo, and Javier Gonzalez-Jimenez. "Enhancing Smart Environments with Mobile Robots." In Ubiquitous Computing and Ambient Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48799-1_17.

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Gottfried, Björn. "Locomotion Activities in Smart Environments." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_4.

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Leistikow, René. "Multi-Agent Strategy Synthesis in Smart Meeting Environments." In Ambient Intelligence - Software and Applications. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19937-0_19.

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García-Gómez, Joaquín, Marta Bautista-Durán, Roberto Gil-Pita, Inma Mohino-Herranz, and Manuel Rosa-Zurera. "Violence Detection in Real Environments for Smart Cities." In Ubiquitous Computing and Ambient Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48799-1_52.

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Härmä, Aki. "Ambient Human-to-Human Communication." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_30.

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Corno, Fulvio, Alastair Gale, Päivi Majaranta, and Kari-Jouko Räihä. "Eye-based Direct Interaction for Environmental Control in Heterogeneous Smart Environments." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_41.

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Chin, Jeannette, Victor Callaghan, and Graham Clarke. "End-user Customisation of Intelligent Environments." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_14.

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López-Cózar, Ramón, and Zoraida Callejas. "Multimodal Dialogue for Ambient Intelligence and Smart Environments." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_21.

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Ramos, Carlos, Goreti Marreiros, Ricardo Santos, and Carlos Filipe Freitas. "Smart Offices and Intelligent Decision Rooms." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_32.

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Fuchs, Florian, Michael Berger, and Claudia Linnhoff-Popien. "Smart Monitoring for Physical Infrastructures." In Handbook of Ambient Intelligence and Smart Environments. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-93808-0_22.

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Conference papers on the topic "Ambient intelligence: Smart environments"

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Mikulecky, P. "Ambient intelligence and smart spaces for managerial work support." In 3rd IET International Conference on Intelligent Environments (IE 07). IEE, 2007. http://dx.doi.org/10.1049/cp:20070426.

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Najjar, Amro, and Patrick Reignier. "Constructivist ambient intelligent agent for smart environments." In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2013). IEEE, 2013. http://dx.doi.org/10.1109/percomw.2013.6529515.

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Streitz, N. A. "Designing interaction for smart environments: ambient intelligence and the disappearing computer." In 2nd IET International Conference on Intelligent Environments (IE 06). IEE, 2006. http://dx.doi.org/10.1049/cp:20060618.

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Anwar Hossain, M., P. K. Atrey, and A. El Saddik. "Smart mirror for ambient home environment." In 3rd IET International Conference on Intelligent Environments (IE 07). IEE, 2007. http://dx.doi.org/10.1049/cp:20070431.

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"SENAmI 2013: 5th international workshop on smart environments and ambient intelligence 2013 - Program." In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 2013. http://dx.doi.org/10.1109/percomw.2013.6529444.

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"SENAmI 2013: 5th international workshop on smart environments and ambient intelligence 2013 - Committees and welcome." In 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops). IEEE, 2013. http://dx.doi.org/10.1109/percomw.2013.6529445.

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Lim, Yuto, Sin Yee Lim, Minh Dat Nguyen, Cheng Li, and Yasuo Tan. "Bridging between universAAL and ECHONET for smart home environment." In 2017 14th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2017. http://dx.doi.org/10.1109/urai.2017.7992884.

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Sadovenko, Maryna, Iryna Vasylchuk, and Kateryna Slyusarenko. "Environmental Taxation and Its Impact on Stimulating the Development of Smart Industry." In III International Scientific Congress Society of Ambient Intelligence 2020 (ISC-SAI 2020). Atlantis Press, 2020. http://dx.doi.org/10.2991/aebmr.k.200318.024.

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Amirjavid, Farzad, Abdenour Bouzouane, and Bruno Bouchard. "Intelligent temporal data driven world actuation in ambient environments: Case study: Anomaly recognition and assistance provision in smart home." In 2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS). IEEE, 2013. http://dx.doi.org/10.1109/icis.2013.6607856.

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Lei, Hong, Wen Li, Guoming Zhu, and Xiaobo Tan. "Evaluation of Encapsulated IPMC Sensor Based on Thick Parylene Coating." In ASME 2012 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/smasis2012-7975.

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Ionic polymer-metal composites (IPMCs) have intrinsic sensing and actuation capabilities. However, IPMCs require ionic hydration to operate. As the most commonly used solvent, water content contained in the polymer changes with the humidity level of the ambient environment, which affects the sensing behavior of an IPMC in air. Motivated by the need to ensure consistent sensing performance of IPMCs under different ambient environments, in this paper we propose thick (up to 10 micrometers) parylene C coating for IPMC sensors, develop effective coating processes, and evaluate the stability of the encapsulated sensors in air. During the process of parylene coating, water molecules would evaporate inside the deposition chamber, resulting in the encapsulated IPMCs’ losing sensing capability. To address this challenge and control the hydration level of an encapsulated IPMC, the proposed fabrication process comprises major steps of parylene deposition, water absorption, and SU-8 seal. The influence of hydration level controlled by the water absorption step is studied to improve the sensitivity of the IPMC sensor. The water impermeability of the proposed encapsulation technique is tested in different media. Experiments have also been conducted to evaluate the performance of the encapsulated IPMC sensor. The sensing consistency and the lifetime of an encapsulated sensor in air are studied in an environment with changing humidity, along with the comparison with an uncoated IPMC sensor. Experimental results show that the proposed thick parylene coating can effectively maintain the water content inside the IPMC and reduce the interference due to the ambient humidity change, which allows IPMC sensors to be used in many practical applications.
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