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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]

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)  

Public Titre : Applications of Internet of Things Type de document : Monographie Auteurs : Chi-Hua Chen, Éditeur scientifique ; Kuen-Rong Lo, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 162 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-0365-1193-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] analyse de groupement [Termes IGN] apprentissage automatique [Termes IGN] géopositionnement [Termes IGN] informatique en nuage [Termes IGN] internet des objets [Termes IGN] service fondé sur la position [Termes IGN] système de transport intelligent [Termes IGN] téléphonie mobile [Termes IGN] trafic routier [Termes IGN] vitesse Résumé : (auteur) This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al. Note de contenu : 1- Vehicle positioning and speed estimation based on cellular network signals for urban roads 2- A method for traffic congestion clustering judgment based on grey relational analysis 3- Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection 4- A high-efficiency method of mobile positioning based on commercial vehicle operation data 5- Efficient location privacy-preserving k-anonymity method based on the credible chain 6- Proximity-based asynchronous messaging platform for location-based Internet of Things service 7- Detection of electronic anklet wearers’ groupings throughout telematics monitoring 8- Camera coverage estimation based on multistage grid subdivision Numéro de notice : 28650 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/SOCIETE NUMERIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1193-1 En ligne : https://doi.org/10.3390/books978-3-0365-1193-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99766

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

Public Titre : Intelligent sensors for positioning, tracking, monitoring, navigation and smart sensing in smart cities Type de document : Monographie Auteurs : Li Tiancheng, Éditeur scientifique ; Jan Junkun, Éditeur scientifique ; Cao Yue, Éditeur scientifique ; et al., Auteur Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 266 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-0365-0123-9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage automatique [Termes IGN] capteur (télédétection) [Termes IGN] cartographie et localisation simultanées [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] détection de cible [Termes IGN] exploration de données [Termes IGN] Extreme Gradient Machine [Termes IGN] fusion de données [Termes IGN] Inférence floue [Termes IGN] internet des objets [Termes IGN] logique floue [Termes IGN] navigation autonome [Termes IGN] odomètre [Termes IGN] positionnement en intérieur [Termes IGN] réseau de capteurs [Termes IGN] simulation de signal [Termes IGN] ville intelligente Résumé : (éditeur) The rapid development of advanced, arguably, intelligent sensors and their massive deployment provide a foundation for new paradigms to combat the challenges that arise in significant tasks such as positioning, tracking, navigation, and smart sensing in various environments. Relevant advances in artificial intelligence (AI) and machine learning (ML) are also finding rapid adoption by industry and fan the fire. Consequently, research on intelligent sensing systems and technologies has attracted considerable attention during the past decade, leading to a variety of effective applications related to intelligent transportation, autonomous vehicles, wearable computing, wireless sensor networks (WSN), and the internet of things (IoT). In particular, the sensors community has a great interest in novel, intelligent information fusion, and data mining methods coupling AI and ML for substantial performance enhancement, especially for the challenging scenarios that make traditional approaches inappropriate. This reprint book has collected 14 excellent papers that represent state-of-the-art achievements in the relevant topics and provides cutting-edge coverage of recent advances in sensor signal and data mining techniques, algorithms, and approaches, particularly applied for positioning, tracking, navigation, and smart sensing. Note de contenu : 1- MIMU/odometer fusion with state constraints for vehicle positioning during BeiDou signal outage: Testing and results 2- Autonomous road roundabout detection and navigation system for smart vehicles and cities using laser simulator–fuzzy logic algorithms and sensor fusion 3- An elaborated signal model for simultaneous range and vector velocity estimation in FMCW radar 4- Hybrid solution combining Kalman filtering with Takagi–Sugeno fuzzy inference system for online car-following model calibration 5- Computationally efficient cooperative dynamic range-only SLAM based on sum of Gaussian filter 6- LoRaWAN geo-tracking using map matching and compass sensor fusion 7- A robust multi-sensor data fusion clustering algorithm based on density peaks 8- Extended target marginal distribution Poisson multi-Bernoulli mixture filter 9- A multi-core object detection coprocessor for multi-scale/type classification applicable to IoT devices 10- Leveraging uncertainties in softmax decision-making models for low-power IoT devices 11- Implementing deep learning techniques in 5G IoT networks for 3D indoor positioning: DELTA (DeEp Learning-Based Co-operaTive Architecture) 12- A novel hybrid algorithm based on Grey Wolf optimizer and fireworks algorithm 13- Passenger flow forecasting in metro transfer station based on the combination of singular spectrum analysis and AdaBoost-weighted extreme learning machine 14- A unified fourth-order tensor-based smart community system Numéro de notice : 28609 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/POSITIONNEMENT Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0123-9 En ligne : https://doi.org/10.3390/books978-3-0365-0123-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99453

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 [en ligne], 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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Conception et évaluation de techniques d'interaction non-visuelle basées sur un dispositif personnel / Sandra Bardot (2019)  

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GéoIoT : au carrefour des SIG et de l'IoT / Anonyme in Géomatique expert, n° 126 (janvier - février 2019)

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Trends in geomatics / Rifaat Abdalla (2019)  

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