Authors - Vinodkumar Bhutnal, Prajwal Vijay Sonawane, Om Vinod Chaudhari, Avinash Golande, Mohit Ashok Tajane, Sujal Kishor Papdeja Abstract - There is no more pressing issue in modern cities, industries, and public venues than nighttime security, as the conventional approach of patrolling in-person only works well until fatigue and coverage become challenges, when humanity and human error become a finite issue that requires short delay interruptions. Urbanization, increased crime rates, and the inadequacy of current traditional patrolling to provide a sufficient security posture have led to the proposal of an Intelligent Night Patrolling System that uses edge-cloud frameworks, IoT-enabled CCTV camera technology, and artificial intelligence video analytics to significantly reduce the presence gap. This system will provide continuous, real-time proactive surveillance of locations and even be equipped with advanced deep learning models like Cummings Neural Networks (CNNs) and Long Short term Memory (LSTM) to detect suspicious activity, anomalies, intrusions, and violent types of activities. This research introduces the concept of Night Patrolling System designed to assist security personnel during night surveillance.The proposed system achieves an estimated accuraxy of over 90% with a reduced latency , demonstarting it’s effectiveness for a real time survillence applications.
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