Person Identification and Movement Analysis for Surveillance using Machine Learning and Web Scraping

Face recognition is a biometrically based technique that creates a face print by mathematically mapping a person's facial characteristics. The image is subjected to machine learning, and a feature vector is produced that links a set of numbers to each object in the image. The idea behind this program is to use this technology to track down wanted criminals based on their past behavior. Suspects will be detected using machine learning based on their behaviors and unidentifiable facial matching records. The photo or video frame was captured by one of the cameras placed at various locations, and it can be utilized with Prohibited Activities (Physical) and face recognition to identify the stranger. With the use of web scraping, this initiative provides more information about strangers. The suggested method can accurately identify many faces due to the incredibly low computing time, which is useful for speedy suspect search. By lowering crime, this technology will make our society safer.