Search results for "missing information"

showing 3 items of 3 documents

Estimating Missing Information by Cluster Analysis and Normalized Convolution

2018

International audience; Smart city deals with the improvement of their citizens' quality of life. Numerous ad-hoc sensors need to be deployed to know humans' activities as well as the conditions in which these actions take place. Even if these sensors are cheaper and cheaper, their installation and maintenance cost increases rapidly with their number. We propose a methodology to limit the number of sensors to deploy by using a standard clustering technique and the normalized convolution to estimate environmental information whereas sensors are actually missing. In spite of its simplicity, our methodology lets us provide accurate assesses.

010504 meteorology & atmospheric sciencesComputer sciencemedia_common.quotation_subjectReal-time computingEnergy Engineering and Power Technology02 engineering and technologyIterative reconstructionsmart city dealsCluster (spacecraft)01 natural sciencesIndustrial and Manufacturing Engineeringnormalized convolutionstandard clustering technique[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ConvolutionArtificial IntelligenceSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringLimit (mathematics)SimplicityCluster analysisInstrumentationad-hoc sensors0105 earth and related environmental sciencesmedia_commonSettore INF/01 - InformaticaRenewable Energy Sustainability and the EnvironmentComputer Science Applications1707 Computer Vision and Pattern Recognitionenvironmental informationmissing informationComputer Networks and CommunicationKernel (image processing)020201 artificial intelligence & image processingcluster analysis2018 IEEE 4th International Forum on Research and Technology for Society and Industry (RTSI)
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Multi-agent Systems for Estimating Missing Information in Smart Cities

2019

International audience; Smart cities aim at improving the quality of life of citizens. To do this, numerous ad-hoc sensors need to be deployed in a smart city to monitor the environmental state. Even if nowadays sensors are becoming more and more cheap their installation and maintenance costs increase rapidly with their number. This paper makes an inventory of the dimensions required for designing an intelligent system to support smart city initiatives. Then we propose a multi-agent based solution that uses a limited number of sensors to estimate at runtime missing information in smart cities using a limited number of sensors.

Computer scienceMulti-agent system020206 networking & telecommunications02 engineering and technologyComputer securitycomputer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Missing Information EstimationSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringSmart City020201 artificial intelligence & image processingState (computer science)Cooperative Multi-agent Systemscomputer
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A Cooperative Multi-Agent System for Crowd Sensing Based Estimation in Smart Cities

2020

The concept of Smart City has spread as a solution to ensure better access to information and services to citizens, but also as a means to reduce the environmental footprint of cities. To this end, a continuous and wide observation of the environment is necessary to analyze information that enables government bodies to act on the environment appropriately. Moreover, a diffused acquisition of information requires adequate infrastructure and proper devices, which results in relevant installation and maintenance costs. Our proposal enables reducing the number of necessary sensors to be deployed while ensuring that information is available at any time and anywhere. We present the HybridIoT syst…

cooperative multi-agent systemsGeneral Computer ScienceComputer scienceContext (language use)02 engineering and technologycomputer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]missing information estimationIntelligent sensorSmart city11. Sustainability0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceComputingMilieux_MISCELLANEOUSGovernmentSmart cityEcological footprintMulti-agent systemGeneral Engineering020206 networking & telecommunicationsRisk analysis (engineering)13. Climate actionheterogeneous data integration020201 artificial intelligence & image processinglcsh:Electrical engineering. Electronics. Nuclear engineeringcomputerlcsh:TK1-9971Data integrationIEEE Access
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