• Mr. Omkar Sutar
• Prof .Kaveri Kari
• Mr. Rohan Bankar
• Mr. Ashish Bhatkal
• Mr .Namdev Jedgule

The system aims to give CCTV cameras the ability to detect suspicious activity, without human intervention. This paper aims to identify suspicious activity for surveillance and alert shop owners when suspicious activity is detected. Electronic article surveillance (eas) systems are widely used in today’s retail stores, but this system is not capable enough as the shoplifters can easily remove the tag or label from the product. Hence, this system aims to take real-time videos from CCTV as input and pass it to the cnn model created with the help of transfer learning and detect ‘shoplifting’, ‘robbery’ or ’break-in’ in the store and notify the owners as soon as it occurs. Finally, the main motive is to provide a system that detects suspicious activities without human intervention and generates an alert, thus making a huge revolution in today’s surveillance system.

Alert Generation, Suspicious Activity, Shoplifting, Robbery, Break-In

"Suspicious Activity Detection Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.e585-e592, May-2023, Available :http://www.jetir.org/papers/JETIR2305482.pdf

"Suspicious Activity Detection Using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppe585-e592, May-2023, Available at : http://www.jetir.org/papers/JETIR2305482.pdf