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Automated Vigilance Assistance System with Crime Detection for Upcoming Smart Cities
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
In an unavoidable event of a suspect being chased by police, there is high probability for the criminal to evade the police while driving his vehicle. At many instances, criminal escapes without leaving a trail behind and becomes untraceable. A new concept of Vigilance Assistance System Network (VASN) has been developed, which is spread across the city and helps in catching the escaping criminals. At every junction, the traffic-signals are installed with a microcontroller chip and these connected traffic signals form a network with distinct city areas demarcated on the map. The vehicle is installed with GPS and a RFID module on their ECU when it approaches any intersection or junction; they receive wireless signals from traffic-signals and transmit another registering signal to the traffic-light wirelessly through RFID. They register their basic information such as Vehicle Number, Driver Information, GPS coordinates and other Vehicle information such as vehicle speed, fuel level etc. The traffic surveillance team at the control room gets information about the running criminal and tracks the vehicle effectively through maps and initiates vigilance operations. If the GPS of car is disabled or if it fails, this vigilance system still works on RFID module chip which sends wireless signal to traffic-light microcontroller. This system can also be used to secretly track the location of any vehicle in smart cities by searching for a particular vehicle number. Also the details of the car type can be further enhanced by using the particular or the next upcoming traffic CCTV cameras so that a visual interpretation can be obtained.
CitationShah, S., Sharma, A., Angra, R., Singh, N. et al., "Automated Vigilance Assistance System with Crime Detection for Upcoming Smart Cities," SAE Technical Paper 2017-01-1726, 2017, https://doi.org/10.4271/2017-01-1726.
Data Sets - Support Documents
|Unnamed Dataset 1|
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