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Deep learning–based monitoring sustainable decision support system for energy building to smart cities with remote sensing techniques / Wang Yue in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 9 (September 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 9 (September 2022) . - pp 593 - 601 Titre : Deep learning–based monitoring sustainable decision support system for energy building to smart cities with remote sensing techniques Type de document : Article/Communication Auteurs : Wang Yue, Auteur ; Changgang Yu, Auteur ; A. Antonidoss, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 593 - 601 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage profond [Termes IGN] bâtiment [Termes IGN] capteur (télédétection) [Termes IGN] économie d'énergie [Termes IGN] internet des objets [Termes IGN] performance énergétique [Termes IGN] réseau neuronal artificiel [Termes IGN] système d'aide à la décision [Termes IGN] ville durable [Termes IGN] ville intelligente Résumé : (auteur) In modern society, energy conservation is an important consideration for sustainability. The availability of energy-efficient infrastructures and utilities depend on the sustainability of smart cities. The big streaming data generated and collected by smart building devices and systems contain useful information that needs to be used to make timely action and better decisions. The ultimate objective of these procedures is to enhance the city's sustainability and livability. The replacement of decades-old infrastructures, such as underground wiring, steam pipes, transportation tunnels, and high-speed Internet installation, is already a major problem for major urban regions. There are still certain regions in big cities where broadband wireless service is not available. The decision support system is recently acquiring increasing attention in the smart city context. In this article, a deep learning–based sustainable decision support system (DLSDSS) has been proposed for energy building in smart cities. This study proposes the integration of the Internet of Things into smart buildings for energy management, utilizing deep learning methods for sensor information decision making. Building a socially advanced environment aims to enhance city services and urban administration for residents in smart cities using remote sensing techniques. The proposed deep learning methods classify buildings based on energy efficiency. Data gathered from the sensor network to plan smart cities' development include a deep learning algorithm's structural assembly of data. The deep learning algorithm provides decision makers with a model for the big data stream. The numerical results show that the proposed method reduces energy consumption and enhances sensor data accuracy by 97.67% with better decision making in planning smart infrastructures and services. The experimental outcome of the DLSDSS enhances accuracy (97.67%), time complexity (98.7%), data distribution rate (97.1%), energy consumption rate (98.2%), load shedding ratio (95.8%), and energy efficiency (95.4%). Numéro de notice : A2022-812 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.22-00010R2 Date de publication en ligne : 01/09/2022 En ligne : https://doi.org/10.14358/PERS.22-00010R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101972 [article]

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Smart city data science: Towards data-driven smart cities with open research issues / Iqbal H. Sarker in Internet of Things, vol 19 (August 2022)  

Public [article]  inInternet of Things > vol 19 (August 2022) . - n° 100528 Titre : Smart city data science: Towards data-driven smart cities with open research issues Type de document : Article/Communication Auteurs : Iqbal H. Sarker, Auteur Année de publication : 2022 Article en page(s) : n° 100528 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage profond [Termes IGN] gestion urbaine [Termes IGN] internet des objets [Termes IGN] planification urbaine [Termes IGN] science des données [Termes IGN] sécurité [Termes IGN] télédétection [Termes IGN] ville intelligente Résumé : (auteur) Cities are undergoing huge shifts in technology and operations in recent days, and ‘data science’ is driving the change in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting useful knowledge or actionable insights from city data and building a corresponding data-driven model is the key to making a city system automated and intelligent. Data science is typically the scientific study and analysis of actual happenings with historical data using a variety of scientific methodologies, machine learning techniques, processes, and systems. In this paper, we concentrate on and explore “Smart City Data Science”, where city data collected from various sources such as sensors, Internet-connected devices, or other external sources, is being mined for insights and hidden correlations to enhance decision-making processes and deliver better and more intelligent services to citizens. To achieve this goal, artificial intelligence, particularly, machine learning analytical modeling can be employed to provide deeper knowledge about city data, which makes the computing process more actionable and intelligent in various real-world city services. Finally, we identify and highlight ten open research issues for future development and research in the context of data-driven smart cities. Overall, we aim to provide an insight into smart city data science conceptualization on a broad scale, which can be used as a reference guide for the researchers, industry professionals, as well as policy-makers of a country, particularly, from the technological point of view. Numéro de notice : A2022-383 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1016/j.iot.2022.100528 Date de publication en ligne : 20/04/2022 En ligne : https://doi.org/10.1016/j.iot.2022.100528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100660 [article]

Exploring digital twin adaptation to the urban environment: comparison with CIM to avoid silo-based approaches / Adeline Deprêtre in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-4-2022 (2022 edition) . - pp 337 - 344 Titre : Exploring digital twin adaptation to the urban environment: comparison with CIM to avoid silo-based approaches Type de document : Article/Communication Auteurs : Adeline Deprêtre, Auteur ; Florence Jacquinod , Auteur ; Alexandre Mielniczek, Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : pp 337 - 344 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse comparative [Termes IGN] internet des objets [Termes IGN] jumeau numérique [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] système d'information géographique [Termes IGN] zone urbaine Résumé : (auteur) The use of digital models and tools to support a more sober, sustainable and human-centred spatial planning is constantly expanding. Among those, digital models of buildings and territories are considered useful by scientists and practitioners and used for a wide range of purposes. Several labels are currently used to characterise those digital tools and models, partly reflecting on technological developments: 3D city models, Planning support systems, Smart Cities, urbanism 3.0., City Information Model (CIM), Digital Twins (DT), etc. First used in industry, the label DT is now both used by practitioners and researchers, in relation to the development of innovative city models. Nevertheless, this label remains fuzzily defined and designates heterogeneous models from a technical standpoint. In this paper, we propose an exploration of the definitions and technical contents of DT at the city scale and a comparison with CIM approaches, as CIM is also used to label similar city models. Our analysis is based on a literature review of both DT and CIM definitions and applications to the urban context, an exploratory survey conducted with 13 practitioners about their views on DT and its potential regarding urban planning and management and a comparison of a few real-world projects either labelled CIM or DT by practitioners. Our analysis leads us to pinpoint several of the remaining challenges for a DT approach to be developed at the city scale. We also shed light on potential shortcomings of future research, if based on too narrow DT definitions. Numéro de notice : A2022-421 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-4-2022-337-2022 Date de publication en ligne : 18/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2022-337-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100725 [article]

From artificial intelligence to artificial human interaction : understand consumer acceptance of smart objects via mental representations of future interactions / Mohamed Hakimi (2022)  

Public Titre : From artificial intelligence to artificial human interaction : understand consumer acceptance of smart objects via mental representations of future interactions Type de document : Thèse/HDR Auteurs : Mohamed Hakimi, Auteur ; Pierre Valette-Florence, Directeur de thèse Editeur : Grenoble [France] : Université Grenoble Alpes Année de publication : 2022 Importance : 397 p. Format : 21 x 30 cm Note générale : bibliographie Thèse pour obtenir le grade de Docteur de l'Université Grenoble Alpes, spécialité Science de gestion Langues : Français (fre) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] comportement [Termes IGN] consommation [Termes IGN] interaction homme-machine [Termes IGN] internet des objets [Termes IGN] ontologie [Termes IGN] représentation mentale Index. décimale : THESE Thèses et HDR Résumé : (auteur) While we are promised a booming for IoT markets and artificial intelligence, consumers still seem affected by ambivalence and concern regarding their acceptance (Ardelet et al. 2017). These negative attitudes toward smart objects represent a real barrier to adoption (Mani and Chouk 2018). Prior studies have tried to investigate the mechanisms of acceptance and resistance toward smart objects. Yet, they often relied upon a human-oriented perspective to assess this complex phenomenon and didn’t consider the interpersonal nature of consumer-smart object interactions (Novak and Hoffman 2019, Monsurro et al. 2020). The aim of this research is to assess the consumer-smart object anticipated interaction from an object-oriented ontology. The main goal is to explore the mental representations that smart object’s capacities can trigger. We posit that consumers can mentally simulate future interpersonal interactions with the smart object, based on its perceived capacities to affect and to be affected (Hoffman and Novak 2015). To do so, this research has adopted a mixed-method approach. First, we relied upon a projective qualitative technique called Album-OnLine (AOL) to explore the mental representations elicited by a smart object before purchase. Then, two quantitative studies examine the potential influence of smart object’s perceived capacities (Agency) over the emergence of negative attitudes and anxiety toward it, prior to any real-life interaction. Our results suggest that passive resistance toward smart objects and anxiety toward them emerge due to the innovative and agentic capacities expressed by the smart object. A detailed explanation of the phenomenon and avenues for future research are provided for researchers and managers to reduce this state of anticipated anxiety and to promote smart objects’ adoption. Note de contenu : Introduction 1- A theoretical approach of consumer-smart object interaction 2- Studying the simulated relational outcomes of consumer-smart objects anticipated relationships: Conceptual framework and methodology General discussion Numéro de notice : 24070 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/SOCIETE NUMERIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Science de gestion : Grenoble : 2022 Organisme de stage : CERAG DOI : sans En ligne : https://tel.archives-ouvertes.fr/tel-03790489 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102125

Activity recognition in residential spaces with Internet of things devices and thermal imaging / Kshirasagar Naik in Sensors, vol 21 n° 3 (February 2021)  

Public [article]  inSensors > vol 21 n° 3 (February 2021) . - n° 988 Titre : Activity recognition in residential spaces with Internet of things devices and thermal imaging Type de document : Article/Communication Auteurs : Kshirasagar Naik, Auteur ; Tejas Pandit, Auteur ; Nitin Naik, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 988 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] compréhension de l'image [Termes IGN] contrôle par télédétection [Termes IGN] détection d'événement [Termes IGN] espace intérieur [Termes IGN] image RVB [Termes IGN] image thermique [Termes IGN] intelligence artificielle [Termes IGN] internet des objets [Termes IGN] itération [Termes IGN] modèle stéréoscopique [Termes IGN] objet mobile [Termes IGN] reconnaissance automatique [Termes IGN] reconnaissance d'objets [Termes IGN] scène 3D Résumé : (auteur) In this paper, we design algorithms for indoor activity recognition and 3D thermal model generation using thermal images, RGB images, captured from external sensors, and the internet of things setup. Indoor activity recognition deals with two sub-problems: Human activity and household activity recognition. Household activity recognition includes the recognition of electrical appliances and their heat radiation with the help of thermal images. A FLIR ONE PRO camera is used to capture RGB-thermal image pairs for a scene. Duration and pattern of activities are also determined using an iterative algorithm, to explore kitchen safety situations. For more accurate monitoring of hazardous events such as stove gas leakage, a 3D reconstruction approach is proposed to determine the temperature of all points in the 3D space of a scene. The 3D thermal model is obtained using the stereo RGB and thermal images for a particular scene. Accurate results are observed for activity detection, and a significant improvement in the temperature estimation is recorded in the 3D thermal model compared to the 2D thermal image. Results from this research can find applications in home automation, heat automation in smart homes, and energy management in residential spaces. Numéro de notice : A2021-159 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s21030988 Date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.3390/s21030988 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97075 [article]

Applications of Internet of Things / Chi-Hua Chen (2021)  

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Intelligent sensors for positioning, tracking, monitoring, navigation and smart sensing in smart cities / Li Tiancheng (2021)  

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Knowledge graph management and streaming in the context of edge computing / Weiqin Xu (2021)  

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SIoT: a new strategy to improve the network lifetime with an efficient search process / Abderrahim Zannou in Future internet, vol 13 n° 1 (January 2021)  

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Smart cities / Anuar Mohamed Kassim (2021)  

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Objets connectés et mobilité urbaine : visualiser les déplacements des usagers de Twitter avec des graphes dynamiques / Françoise Lucchini in Mappemonde, n° 128 (juillet 2020)  

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A proposal for modeling indoor–outdoor spaces through indoorGML, open location code and OpenStreetMap / Ruben Cantarero Navarro in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

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Demystifying Internet of Things security / Sunil Cheruvu (2020)  

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Développement d’une méthode d’intégration systématique des capteurs dans le BIM pour les constructions durables / Yasmine El Khadraoui (2020)  

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Security risk management for the Internet of things: Technologies and techniques for IoT security, privacy and data protection / John Soldatos (2020)  

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