PUBLIC SAFETY AND UNUSUAL BEHAVIOUR MONITORING IN PUBLIC AREAS

Abstract

Unusual Behavior Real-time in-demand research is being done on recognition from surveillance images. Quick abnormal event detection meets the growing demand for processing a vast amount of surveillance footage. Video surveillance represents a burgeoning field where artificial intelligence (AI), machine learning (ML), and deep learning technologies are actively employed. Computers possess the ability to emulate human thought processes, thanks to artificial intelligence. Machine learning, a crucial facet of this, involves acquiring knowledge based on training of information and making estimations determined by forthcoming information. Utilization of deep learning has become feasible because the accessibility of substantial datasets and powerful GPU processors (Graphics Processing Units).

Unusual Behavior Real-time in-demand research is being done on recognition from surveillance images.

To prevent theft instances, Detecting potentially suspicious human activity through video monitoring is of paramount importance, terrorists from using abandoned goods as explosives, Vandalism, altercations, and personal attacks, and fire in many extremely sensitive places like as well as airports, refineries, nuclear power plants, bus and train terminals, shopping centres, banks, hospitals, universities, borders, and so on. Campuses of universities and other academic institutions can utilise video surveillance to keep an eye on students' activities to protect property from theft and destruction. Additionally, it will assist in reducing student fights and improper behaviour. For the protection of the faculty and students, it will keep an eye on the outside of the university campus and other academic buildings. When exams are being given, video surveillance may be utilised to keep an eye on any suspicious behaviour among the students in the exam room.