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An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data

1
Department of Information Engineering, Infrastructure and Sustainable Energy (DIIES), University Mediterranea of Reggio Calabria, 89124 Reggio Calabria, Italy
2
HWA srl-Spin Off dell’Università Mediterranea di Reggio Calabria, Via Reggio Campi II tr. 135, 89126 Reggio Calabria, Italy
*
Author to whom correspondence should be addressed.
Algorithms 2020, 13(10), 254; https://doi.org/10.3390/a13100254
Received: 11 August 2020 / Revised: 29 September 2020 / Accepted: 3 October 2020 / Published: 7 October 2020
(This article belongs to the Special Issue Algorithms for Smart Cities)
Smart cities need technologies that can be really applied to raise the quality of life and environment. Among all the possible solutions, Internet of Things (IoT)-based Wireless Sensor Networks (WSNs) have the potentialities to satisfy multiple needs, such as offering real-time plans for emergency management (due to accidental events or inadequate asset maintenance) and managing crowds and their spatiotemporal distribution in highly populated areas (e.g., cities or parks) to face biological risks (e.g., from a virus) by using strategies such as social distancing and movement restrictions. Consequently, the objective of this study is to present an IoT system, based on an IoT-WSN and on algorithms (Neural Network, NN, and Shortest Path Finding) that are able to recognize alarms, available exits, assembly points, safest and shortest paths, and overcrowding from real-time data gathered by sensors and cameras exploiting computer vision. Subsequently, this information is sent to mobile devices using a web platform and the Near Field Communication (NFC) technology. The results refer to two different case studies (i.e., emergency and monitoring) and show that the system is able to provide customized strategies and to face different situations, and that this is also applies in the case of a connectivity shutdown. View Full-Text
Keywords: smart city; emergency management; monitoring; social distancing; neural network; internet of things; wireless sensors network; near field communication technology; computer vision smart city; emergency management; monitoring; social distancing; neural network; internet of things; wireless sensors network; near field communication technology; computer vision
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Fedele, R.; Merenda, M. An IoT System for Social Distancing and Emergency Management in Smart Cities Using Multi-Sensor Data. Algorithms 2020, 13, 254.

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