Search results for "Ambient Intelligence"

showing 10 items of 50 documents

Human Activity Recognition Process Using 3-D Posture Data

2015

In this paper, we present a method for recognizing human activities using information sensed by an RGB-D camera, namely the Microsoft Kinect. Our approach is based on the estimation of some relevant joints of the human body by means of the Kinect; three different machine learning techniques, i.e., K-means clustering, support vector machines, and hidden Markov models, are combined to detect the postures involved while performing an activity, to classify them, and to model each activity as a spatiotemporal evolution of known postures. Experiments were performed on Kinect Activity Recognition Dataset, a new dataset, and on CAD-60, a public dataset. Experimental results show that our solution o…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniImage fusionMarkov chainComputer Networks and CommunicationsComputer sciencebusiness.industryMaximum-entropy Markov modelFeature extractionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONHuman Factors and ErgonomicsPattern recognitionComputer Science ApplicationsHuman-Computer InteractionActivity recognitionSupport vector machineHuman activity recognition kinect ambient intelligenceArtificial IntelligenceControl and Systems EngineeringSignal ProcessingComputer visionArtificial intelligenceCluster analysisHidden Markov modelbusinessIEEE Transactions on Human-Machine Systems
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A fog-based hybrid intelligent system for energy saving in smart buildings

2019

In recent years, the widespread diffusion of pervasive sensing devices and the increasing need for reducing energy consumption have encouraged research in the energy-aware management of smart environments. Following this direction, this paper proposes a hybrid intelligent system which exploits a fog-based architecture to achieve energy efficiency in smart buildings. Our proposal combines reactive intelligence, for quick adaptation to the ever-changing environment, and deliberative intelligence, for performing complex learning and optimization. Such hybrid nature allows our system to be adaptive, by reacting in real time to relevant events occurring in the environment and, at the same time, …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniQA75General Computer ScienceAmbient Intelligence Fuzzy Systems Fog Computing Energy Efficiencybusiness.industryComputer scienceDistributed computingComputational intelligence02 engineering and technologyEnergy consumptionHybrid intelligent systemHome automation020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSmart environmentbusinessAdaptation (computer science)Efficient energy useBuilding automationJournal of Ambient Intelligence and Humanized Computing
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A cognitive architecture for ambient intelligence systems

2018

Nowadays, the use of intelligent systems in homes and workplaces is a well-established reality. Research efforts are moving towards increasingly complex Ambient Intelligence (AmI) systems that exploit a wide variety of sensors, software modules and stand-alone systems. Unfortunately, using more data often comes at a cost, both in energy and computational terms. Finding the right trade-off between energy savings, information costs and accuracy of results is a major challenge, especially when trying to integrate many heterogeneous modules. Our approach fits into this scenario by proposing an ontology-based AmI system with a cognitive architecture, able to perceive the state of the surrounding…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSelf-modelingAmbient intelligenceCognitive architecture
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Ambient Intelligence for Energy Efficiency in a Complex of Buildings

2013

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSmart BuildingAmbient IntelligenceEnergy Efficiency
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Gesture Recognition for Improved User Experience in a Smart Environment

2013

Ambient Intelligence (AmI) is a new paradigm that specifically aims at exploiting sensory and context information in order to adapt the environment to the user's preferences; one of its key features is the attempt to consider common devices as an integral part of the system in order to support users in carrying out their everyday life activities without affecting their normal behavior. Our proposal consists in the definition of a gesture recognition module allowing users to interact as naturally as possible with the actuators available in a smart office, by controlling their operation mode and by querying them about their current state. To this end, readings obtained from a state-of-the-art…

Source dataAmbient intelligenceAmbient Intelligencebusiness.industryComputer scienceGesture RecognitionProbabilistic logicUsabilityMachine learningcomputer.software_genreSupport vector machineGesture recognitionArtificial intelligencebusinessClassifier (UML)computerGesture
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Requirement analysis abstractions for AmI system design

2015

Current trends in the AI’s evolution are going towards enriching environments with intelligence in order to support humans in their everyday life. AmI systems are plunged in the real world and humans expect to interact with them in a way that is similar to the one they have with other humans. In this kind of systems, where eliciting requirements involves several documents and stakeholders (mainly users that will be the first consumers of the system), the requirement analysis phase can be affected by incomplete, ambiguous and imprecise information. Hence, the need to find a fruitful way for knowledge management and its representation at design time. In this paper we propose a set of abstract…

Statistics and ProbabilityAmbient intelligenceKnowledge representation and reasoningRequirement analysisComputer scienceMulti-agent systemsmart environmentGeneral EngineeringOntology (information science)software designData scienceWorld Wide WebAmI modelArtificial Intelligencemulti-agent systemAmbient intelligenceSystems designSoftware designSmart environmentontologyRequirement analysiRequirements analysisontology AmI modelJournal of Intelligent & Fuzzy Systems
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Autonomic behaviors in an Ambient Intelligence system

2014

Ambient Intelligence (AmI) systems are constantly evolving and becoming ever more complex, so it is increasingly difficult to design and develop them successfully. Moreover, because of the complexity of an AmI system as a whole, it is not always easy for developers to predict its behavior in the event of unforeseen circumstances. A possible solution to this problem might lie in delegating certain decisions to the machines themselves, making them more autonomous and able to self-configure and self-manage, in line with the paradigm of Autonomic Computing. In this regard, many researchers have emphasized the importance of adaptability in building agents that are suitable to operate in real-wor…

Structure (mathematical logic)Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniEngineeringAmbient intelligenceExploitbusiness.industryEvent (computing)media_common.quotation_subjectOntology (information science)AdaptabilityAutonomic computingHuman-Computer InteractionRisk analysis (engineering)Artificial IntelligenceArtificial intelligenceArchitecturebusinessmedia_common
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Enforcing role based access control model with multimedia signatures.

2009

International audience; Recently ubiquitous technology has invaded almost every aspect of the modern life. Several application domains, have integrated ubiquitous technology to make the management of resources a dynamic task. However, the need for adequate and enforced authentication and access control models to provide safe access to sensitive information remains a critical matter to address in such environments. Many security models were proposed in the literature thus few were able to provide adaptive access decisions based on the environmental changes. In this paper, we propose an approach based on our previous work [B.A. Bouna, R. Chbeir, S. Marrara, A multimedia access control languag…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-WB] Computer Science [cs]/WebComputer access controlComputer science[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceXACMLAccess control02 engineering and technologycomputer.software_genreWorld Wide Web[SCCO.COMP] Cognitive science/Computer science020204 information systems0202 electrical engineering electronic engineering information engineeringRole-based access control[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Intelligent environmentcomputer.programming_language[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Ambient intelligenceMultimediabusiness.industry[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]Computer security model[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ SCCO.COMP ] Cognitive science/Computer science020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]Web servicebusinesscomputerSoftware
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Bridging Sensing and Decision Making in Ambient Intelligence Environments

2009

Context-aware and Ambient Intelligence environments represent one of the emerging issues in the last decade. In such intelligent environments, information is gathered to provide, on one hand, autonomic and easy to manage applications, and, on the other, secured access controlled environments. Several approaches have been defined in the literature to describe context-aware application with techniques to capture and represent information related to a specified domain. However and to the best of our knowledge, none has questioned the reliability of the techniques used to extract meaningful knowledge needed for decision making especially if the information captured is of multimedia types (image…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Ambient intelligenceComputer science02 engineering and technologycomputer.software_genreBridging (programming)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]uncertainty resolver modelHuman–computer interaction020204 information systemsResolver0202 electrical engineering electronic engineering information engineeringcontext-aware applicationsemantic-based020201 artificial intelligence & image processingData mining[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]computer
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Introduction to the 5th International Workshop on Intelligent Environments Supporting Healthcare and Well-Being (WISHWell13)

2013

This workshop is designed to bring together researchers from both industry and academia from the various disciplines to discuss how innovation in the use of technologies to support healthier lifestyles can be moved forward. There has been a growing interest around the world and especially in Europe, on investigating the potential consequences of introducing technology to deliver social and health care to citizens (see for example [1]). This implies an important shift on how social and health care are delivered and it has positive as well as negative consequences which must be investigated carefully. On the other hand there is an urgency provided by the changes in demographics which is putti…

education.field_of_studyKnowledge managementAmbient intelligenceDemographicsbusiness.industryComputer sciencePopulationPublic relationsHealth careWell-beingBody area networkIntelligent environmentbusinesseducation
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