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Detecting spatiotemporal traffic events using geosocial media data / Shishuo Xu in Computers, Environment and Urban Systems, vol 94 (June 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 94 (June 2022) . - n° 101797 Titre : Detecting spatiotemporal traffic events using geosocial media data Type de document : Article/Communication Auteurs : Shishuo Xu, Auteur ; Songnian Li, Auteur ; Wei Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101797 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de groupement [Termes IGN] base de données d'objets mobiles [Termes IGN] base de données spatiotemporelles [Termes IGN] détection d'événement [Termes IGN] données issues des réseaux sociaux [Termes IGN] données spatiotemporelles [Termes IGN] planification urbaine [Termes IGN] sécurité routière [Termes IGN] Toronto [Termes IGN] trafic routier [Termes IGN] Twitter Résumé : (auteur) Social media platforms enable efficient traffic event detection by allowing users to produce geo-tagged content (e.g., tweets) known as geosocial media data. Geosocial media data improve road safety by providing timely updates for traffic flow and traffic control. Recent studies on traffic event detection with geosocial media data have been focused around keyword-based query approaches, where the event content was inferred by predetermined categories, to retrieve relevant traffic events. Spatiotemporal features associated with traffic-related posts have not been fully investigated. In this study, we filtered irrelevant posts with association rules. A spatiotemporal clustering-based method was then used to retrieve traffic events from these filtered posts, where the content of detected events was automatically inferred with a set of representative terms. For comparison, a typical text classification-based method was also used by classifying the posts filtered from association rules into different categories. By validating the detection results with vehicle travel speed data, we demonstrate that the former outperforms the latter in terms of the number of correctly detected traffic events from one-year of Twitter data in Toronto, Canada. Our proposed approach helps organizations and governments to be aware of when and where traffic events occur by identifying event hotspots and peak periods, which improves both traffic management and urban planning. Numéro de notice : A2022-264 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101797 Date de publication en ligne : 26/03/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100261 [article]

The point-descriptor-precedence representation for point configurations and movements / Amna Qayyum in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1374 - 1391 Titre : The point-descriptor-precedence representation for point configurations and movements Type de document : Article/Communication Auteurs : Amna Qayyum, Auteur ; Bernard De Baets, Auteur ; Muhammad Sulman Baig, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1374 - 1391 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] courbe [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] mesurage de distances [Termes IGN] objet mobile [Termes IGN] reconnaissance de formes [Termes IGN] relation topologique [Termes IGN] trafic routier [Termes IGN] véhicule automobile Résumé : (auteur) In this paper, we represent (moving) point configurations along a curved directed line qualitatively by means of a system of relational symbols based on two distance descriptors: one representing distance along the curved directed line and the other representing signed orthogonal distance to the curved directed line. The curved directed line represents the direction of the movement of interest. For instance, it could be straight as in the case of driving along a highway or could be curved as in the case of an intersection or a roundabout. Inspired by the Point Calculus, the order between the points on the curved directed line is described by means of a small set of binary relations () acting upon the distance descriptors. We call this representation the Point-Descriptor-Precedence-Static (PDPS) representation at a time point and Point-Descriptor-Precedence-Dynamic (PDPD) representation during a time interval. To illustrate how the proposed approach can be used to represent and analyse curved movements, some basic micro-analysis traffic examples are studied. Finally, we discuss some extensions of our work to highlight the practical benefits of PDP in identifying motion patterns that could be useful in GIS, autonomous vehicles, sports analytics, and gait analysis. Numéro de notice : A2021-453 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1864378 Date de publication en ligne : 11/01/2021 En ligne : https://doi.org/10.1080/13658816.2020.1864378 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97882 [article]

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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]

Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica [en ligne], vol 24 n° 2 (April 2020)  

Public [article]  inGeoinformatica [en ligne] > vol 24 n° 2 (April 2020) . - pp 269 – 299 Titre : Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network Type de document : Article/Communication Auteurs : Adil Alim, Auteur ; Aparna Joshi, Auteur ; Feng Chen, Auteur ; Catherine T. Lawson, Auteur Année de publication : 2020 Article en page(s) : pp 269 – 299 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] corrélation [Termes IGN] détection d'événement [Termes IGN] détection de changement [Termes IGN] données spatiotemporelles [Termes IGN] entretien du réseau [Termes IGN] hiver [Termes IGN] météorologie [Termes IGN] prévision météorologique [Termes IGN] réseau routier [Termes IGN] sécurité routière [Termes IGN] trafic routier Résumé : (auteur) Adverse weather conditions have a significant impact on the safety, mobility, and efficiency of highway networks. Weather contributed to 23 percent of all non-reoccurring delay and approximately 544 million vehicle hours of delay each year (2014). Nearly 2.3 billion dollars each year are spent by transportation agencies for winter maintenance that contribute to close to 20 percent of most DOT’s yearly budgets (2014). These safety and mobility factors make it important to develop new and more effective methods to address road conditions during adverse weather conditions. Given weather and traffic sensors installed along side of the highway networks, how can we automatically detect weather and traffic change events and prevent from the traffic delay or harsh weather accidents? To this end, we propose a novel framework to address this problem. This paper develops techniques for efficiently detecting rapid weather change events and analyzing their impacts on the traffic flow characteristics of a highway network. It is composed of three components, including 1) detection of rapid weather change events in a highway network using the streaming weather information from a sensor network of weather stations; 2) detection of rapid traffic change events on the traffic flow characteristics (e.g., travel time) of the highway network; and 3) analysis of correlations between the detected weather and traffic change events in space and time. The proposed approach was applied to a weather dataset provided by New York State Mesonet and a traffic flow dataset the National Performance Management Research Data Set (NPMRDS) provided by NYSDOT. The empirical results provide potential evidence about the significant impacts of rapid weather change events on traffic flow characteristics of the Interstate 90 (I-90) Highway in the state of New York. We show the quantitative performance evaluation of our change event detection algorithm and three baseline methods on manually labeled the weather dataset and our method outperforms baselines in terms of precision, recall and F-score. We present the analysis of Top K detected change events as case studies and also provide the spatio-temporal correlation statistics of top k weather and traffic change events. The limitations of the proposed approach and the empirical study are also discussed. Numéro de notice : A2020-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00395-x Date de publication en ligne : 12/02/2020 En ligne : https://doi.org/10.1007/s10707-020-00395-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95263 [article]

Placial analysis of events: a case study on criminological places / Sunghwan Cho in Cartography and Geographic Information Science, Vol 46 n° 6 (November 2019)  

Public [article]  inCartography and Geographic Information Science > Vol 46 n° 6 (November 2019) . - pp 547-566 Titre : Placial analysis of events: a case study on criminological places Type de document : Article/Communication Auteurs : Sunghwan Cho, Auteur ; May Yuan, Auteur Année de publication : 2019 Article en page(s) : pp 547-566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cartographie statistique [Termes IGN] criminalité [Termes IGN] Dallas (Texas) [Termes IGN] détection d'événement [Termes IGN] données spatiotemporelles [Termes IGN] géolocalisation [Termes IGN] interaction humain-espace [Termes IGN] système d'information géographique [Termes IGN] zone à risque Résumé : (auteur) The contrast of space and place has long been an active topic of scholarly discussions in many disciplines. While spatial analysis enjoys a multitude of quantitative methods, the study of place remains mostly conceptual and descriptive. This paper expands upon the rich concepts of place in the literature to propose a quantitative framework for placial analysis based on events. Central to the proposed framework are three assumptions: (1) human experiences transform space to place; (2) events build human experiences in space; and (3) places emerge organically and may change characters, spatial extent and location over time through the shifts in occurrences and types of events in space and time. The proposed framework consists of three elements: clustering events, decomposing event distributions, and identifying the similarity of event clusters. We applied the framework to identify criminological places in the City of Dallas in the United States and the changes of these places from 1 June 2014 to 30 May 2018. Numéro de notice : A2019-417 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1578265 Date de publication en ligne : 01/03/2019 En ligne : https://doi.org/10.1080/15230406.2019.1578265 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93544 [article]

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Challenges in grassland mowing event detection with multimodal Sentinel images / Anatol Garioud (2019)  

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Joint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)

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Unsupervised detection of ruptures in spatial relationships in video sequences based on log‑likelihood ratio / Abdalbassir Abou-Elailah in Pattern Analysis and Applications, vol 21 n° 3 (August 2018)  

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