Vehicle Anti-Theft Face Recognition System Based on IoT using Raspberry Pi4
Volume 16 Issue 2 2022
Download| Author(s): | Zamin Ali Khan*, Sajida Karim, Darakhshan Syed |
|---|---|
| Abstract | Security for automobiles provides the protection of living lifestyle in this era where the vehicle is an essential need to adopt in modern society around the whole world. The major problem these days is to secure the vehicles, because the owner always has fear about their vehicles would have stolen from parking areas either at home or office. In this paper, we present a system, vehicle anti-theft face recognition system (VATFRS) that can be detected access through Internet of things (IoT), allow authorized identification or unauthorized protection. The proposed VATFRS provides the security infrastructure on a low-cost extendable security system. This will work with a structure, with combination of three systems, i.e. face detection subsystem (FDS), a global positioning system (GPS), and an android management platform. Moreover, the system captures images of the driver and compares their face to the database to determine whether or not he is an accredited driver. We use a Raspberry Pi circuit to handle all of the events and construct a face detection module based on an advanced local binary pattern (LBPH) algorithm. Although different modules transmit necessary information to users to help and provide security. Therefore, our results show that the thief identification system and vehicle location system are much smarter and cost-effective than the traditional system. |
| Keywords | "Face Recognition and Detection, Vehicle Theft, Raspberry Pi4 MODEL B+" |
| Year | 2022 |
| Volume | 16 |
| Issue | 2 |
| Type | Research paper, manuscript, article |
| Journal Name | Journal of Information & Communication Technology | Publisher Name | ILMA University | Jel Classification | - | DOI | - | ISSN no (E, Electronic) | 2075-7239 | ISSN no (P, Print) | 2415-0169 | Country | Pakistan | City | Karachi | Institution Type | University | Journal Type | Open Access | Manuscript Processing | Blind Peer Reviewed | Format | Paper Link | https://jict.ilmauniversity.edu.pk/journal/jict/16.2/5.pdf | Page | 66-72 |