Traffic accident monitoring system using radio frequency identification tools
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Authors
Pardo, Eduardo Martin EstelaChero, Jhonatan Axel Yataco
Aguirre, Jimmy Armas
Acosta, Alvaro Chavarri
Issue Date
2022-01-01
Metadata
Show full item recordJournal
Proceedings of the 2022 IEEE 2nd International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2022DOI
10.1109/ICALTER57193.2022.9964798Additional Links
https://ieeexplore.ieee.org/document/9964798Abstract
This article proposes a system that allows monitoring car accidents with the use of NFC technology. The solution is comprised of low-cost Radio Frequency Identification (RFID) tools integrated into a mobile and web application that interact with the Google Maps API for efficient monitoring. The car accident reporting process collects and sends data manually through different service channels, which generates delays and, in some cases, the receipt of erroneous data. The proposed solution automates the accident reporting process by storing data from the users involved in the RFID tags and displaying them in the mobile and web applications, when generating a new report. Also, our application interacts with the Google Maps API to show the exact location from where accidents are reported, in order to speed up the process of attention by the PNP. The validation was carried out in the city of Lima, Peru. Preliminary results yielded data showing a 94% reduction in the accident reporting process and a 94% reduction in the average data capture time by the National Police of Peru (PNP).Rights
info:eu-repo/semantics/embargoedAccessAttribution-NonCommercial-ShareAlike 4.0 International
Language
engae974a485f413a2113503eed53cd6c53
10.1109/ICALTER57193.2022.9964798
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- Creative Commons
Except where otherwise noted, this item's license is described as info:eu-repo/semantics/embargoedAccess