The main objective of this project is to develop a surveillance system capable of real-time high-precision recognition of criminal faces, enhancing law enforcement efforts in identifying and tracking individuals of interest for public safety and security
The "Surveillance System for Real-Time High-Precision Recognition of Criminal Faces From Wild Videos" project introduces an innovative approach to enhance public safety by utilizing advanced technologies. This system, built around a Raspberry Pi at its core, leverages high-resolution cameras for capture and integrates GPS for location tracking. It is designed to process detects faces and employs sophisticated facial recognition algorithms for the identification of criminal faces. When unauthorized individuals are detected, the system responds by activating a buzzer to alert nearby personnel and simultaneously sends a notification to the relevant authorities via a GSM module. The collected data is securely uploaded to a server, providing a comprehensive record of incidents. This integrated system represents a crucial step towards improving security and aiding law enforcement agencies in promptly identifying and responding to criminal activities, thereby enhancing public safety and security.
Keywords: Raspberry PI, CAM, GPS, GSM, Motor Driver, Buzzzer
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Hardware Components:
Software Components: