• Anuja Wakchaure
• Soham Nagane
• Prathamesh Salunkhe
• Riyaj Tamboli
• N.K. Patil

With the rapid urbanization and increasing need for public safety, traditional surveillance systems have become inadequate in addressing the challenges of modern crime detection. Conventional CCTV systems depend heavily on human monitoring, which is prone to fatigue, delayed responses, and oversight. The integration of Artificial Intelligence (AI) into surveillance infrastructure offers a transformative solution by enabling automated, intelligent, and real-time crime detection capabilities. This research explores the design and application of AI-powered smart surveillance systems aimed at enhancing situational awareness, detecting criminal activities, and responding proactively to potential threats. Leveraging computer vision, machine learning, and deep learning techniques, these systems can automatically identify suspicious behaviour, detect weapons, recognize faces, and track individuals across multiple camera feeds. Key models used include Convolutional Neural Networks (CNNs) for object detection and classification, and Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units for behaviour prediction and anomaly detection in video sequences. The study evaluates the performance of AI algorithms on benchmark surveillance datasets such as UCF-Crime and AI City Challenge, focusing on accuracy, precision, recall, and processing speed. Results demonstrate that AI-enhanced surveillance significantly improves the ability to detect crimes such as theft, assault, and vandalism in real-time compared to manual monitoring. Furthermore, the system reduces false alarms by learning contextual patterns of normal versus suspicious activity. Despite its advantages, the deployment of AI in surveillance raises ethical, legal, and social concerns. Issues such as data privacy, algorithmic bias, mass surveillance, and lack of transparency must be addressed to ensure responsible use. This paper discusses these challenges and emphasizes the importance of developing ethical guidelines, transparent policies, and fair machine learning practices.

Artificial Intelligence, Smart Surveillance, Crime Detection, Machine Learning, Deep Learning, Facial Recognition.

"Smart Surveillance And Crime Detection Using AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 6, page no.a934-a939, June-2025, Available :http://www.jetir.org/papers/JETIR2506100.pdf

"Smart Surveillance And Crime Detection Using AI", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 6, page no. ppa934-a939, June-2025, Available at : http://www.jetir.org/papers/JETIR2506100.pdf