Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1810
Title: i-Police-An Intelligent Policing System Through Public Area Surveillance
Authors: Jayakody, A
Lokuliyana, S
Dasanayaka, K
Iddamalgoda, A
Ganepola, I
Dissanayake, A
Keywords: i-Police
Intelligent Policing
Policing System
Public Area
Surveillance
Issue Date: 27-Oct-2021
Publisher: IEEE
Citation: A. Jayakody, S. Lokuliyana, K. Dasanayaka, A. Iddamalgoda, I. Ganepola and A. Dissanayake, "i-Police - An Intelligent Policing System Through Public Area Surveillance," 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2021, pp. 0148-0154, doi: 10.1109/IEMCON53756.2021.9623145.
Series/Report no.: 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON);Pages 0148-0154
Abstract: Technology and law enforcement are now commonly used hand in hand to improve public safety. Most police departments only use CCTV cameras at a few major intersections for remote surveillance. The public is waiting too long for emergency response lines, therefore using new technologies to improve the current policing system has become one of the police's main goals. The paper presents a coordinated framework that could identify the subtleties of violations via an automated public area surveillance system, specifically the weapon-related crimes and vehicle accidents, which are then disassembled, analyzed, and stored for future inspections. The trained models are aimed to reduce the false positives of incident detection. The weapon detection system had the best average precision (93.8%) by using YOLOv5 while the vehicle accident detection system resulted in the best average precision (94.9%) by using YOLOv4. The system is tested against the collected set of CCTV footage and tested how long it takes to create a notification which is the main goal of this system. Notification is generated in less than 5 seconds after an incident is detected. The evidence collection engine developed with MATLAB delivered the expected with an accuracy of 97% making the extracted evidence reliable to both vehicle accidents and crime scenes. Additionally, the framework provides an effective and efficient communication channel through which the residents can report crimes to regular parties.
URI: http://rda.sliit.lk/handle/123456789/1810
ISSN: 2644-3163
Appears in Collections:Department of Computer systems Engineering-Scopes
Research Papers - Dept of Computer Systems Engineering
Research Papers - IEEE
Research Papers - SLIIT Staff Publications

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