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dc.contributor.author Leung, Carson K.
dc.contributor.author Braun, Peter
dc.contributor.author Cuzzocrea, Alfredo
dc.date.accessioned 2020-03-09T20:07:31Z
dc.date.available 2020-03-09T20:07:31Z
dc.date.issued 2019-03
dc.date.submitted 2020-03-02T23:41:19Z en_US
dc.identifier.citation Leung, C.K.; Braun, P.; Cuzzocrea, A. AI-based sensor information fusion for supporting deep supervised learning. Sensors 2019, 19, 1345. en_US
dc.identifier.uri http://hdl.handle.net/1993/34563
dc.description.abstract In recent years, artificial intelligence (AI) and its subarea of deep learning have drawn the attention of many researchers. At the same time, advances in technologies enable the generation or collection of large amounts of valuable data (e.g., sensor data) from various sources in different applications, such as those for the Internet of Things (IoT), which in turn aims towards the development of smart cities. With the availability of sensor data from various sources, sensor information fusion is in demand for effective integration of big data. In this article, we present an AI-based sensor-information fusion system for supporting deep supervised learning of transportation data generated and collected from various types of sensors, including remote sensed imagery for the geographic information system (GIS), accelerometers, as well as sensors for the global navigation satellite system (GNSS) and global positioning system (GPS). The discovered knowledge and information returned from our system provides analysts with a clearer understanding of trajectories or mobility of citizens, which in turn helps to develop better transportation models to achieve the ultimate goal of smarter cities. Evaluation results show the effectiveness and practicality of our AI-based sensor information fusion system for supporting deep supervised learning of big transportation data. en_US
dc.description.sponsorship Natural Sciences and Engineering Research Council of Canada (NSERC); University of Manitoba en_US
dc.language.iso en en_US
dc.publisher MDPI en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject sensor en_US
dc.subject information fusion en_US
dc.subject sensor fusion en_US
dc.subject artificial intelligence (AI) en_US
dc.subject deep learning en_US
dc.subject supervised learning en_US
dc.subject data mining en_US
dc.subject transportation en_US
dc.subject geographic information system (GIS) en_US
dc.subject global navigation satellite system (GNSS) en_US
dc.subject global positioning system (GPS) en_US
dc.title AI-based sensor information fusion for supporting deep supervised learning en_US
dc.type Article en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.3390/s19061345


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