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http://hdl.handle.net/1942/30833
Title: | UAV-enabled intelligent traffic policing and emergency response handling system for the smart city | Authors: | Beg, Abdurrahman Qureshi, Abdul Rahman Sheltami, Tarek YASAR, Ansar |
Issue Date: | 2020 | Publisher: | SPRINGER LONDON LTD | Source: | PERSONAL AND UBIQUITOUS COMPUTING, | Abstract: | As modern cities expand and develop, the resultant increase in population density gives rise to the need for smart solutions to cope with the demands applied to the infrastructure of the city. In this paper, we investigate the shortcomings of traffic policing and emergency response handling systems; propose an intelligent, autonomous UAV-enabled solution; and describe the system in a simulated environment. Several scenarios of traffic monitoring and policing system are considered in the simulation: traffic light violations and accident detection, mobile speeding traps and automated notification, congestion detection and traffic rerouting, flagged stolen vehicles/pending arrest warrants and vehicle tracking using UAVs, and autonomous emergency response handling systems. Furthermore, smart city infrastructure enable intelligent handling of emergencies by providing traffic light prioritization for ground emergency response units to reduce delay for patient care, automated physical bollard on routes with congested points due to accidents or hazards, first responder support UAV units-medical supplies UAV, fire fighting UAV to combat or control small fires, and numerous other benefits. Lastly, we present the results of the simulated system and discuss our findings. | Notes: | Beg, A (reprint author), King Fahd Univ Petr & Minerals, Dept Comp Engn, Az Zahran, Saudi Arabia. g201703830@kfupm.edu.sa; g201701830@kfupm.edu.sa; tarek@kfupm.edu.sa; ansar.yasar@uhasselt.be |
Other: | Beg, A (reprint author), King Fahd Univ Petr & Minerals, Dept Comp Engn, Az Zahran, Saudi Arabia. g201703830@kfupm.edu.sa; g201701830@kfupm.edu.sa; tarek@kfupm.edu.sa; ansar.yasar@uhasselt.be | Keywords: | Smart city;Traffic monitoring;Traffic policing;UAV;Emergency response;Accident detection | Document URI: | http://hdl.handle.net/1942/30833 | ISSN: | 1617-4909 | e-ISSN: | 1617-4917 | DOI: | 10.1007/s00779-019-01297-y | ISI #: | WOS:000516951500001 | Rights: | Springer-Verlag London Ltd., part of Springer Nature 2020 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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Beg2020_Article_UAV-enabledIntelligentTrafficP.pdf Restricted Access | Published version | 3.91 MB | Adobe PDF | View/Open Request a copy |
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