Safe-Campus: Leveraging AI for Advanced Surveillance and Security Enhancement
Hamna Farooq, Dr Najeed Ahmed Khan · 2024
The primary concern faced by any institution frequented by the public daily is the breach of safety, security and compliance standards upheld by the institution. While nearly all organizations implement security systems on premises, it is often highly dependent on manual surveillance, an inadequate approach, the outcomes of which are limited by delayed response times, inconsistent monitoring and lack of real-time analysis. Conventional surveillance systems need to be redesigned to integrate a more intelligent security systems infrastructure, upgrading to accommodate for the evolving requirements of contemporary institutions. In this paper we propose an AI based solution; “Safe-Campus”. We have developed a framework for real-time data analysis of the CCTV footage, that takes into account safety concerns and attempts to mitigate them by leveraging artificial intelligence models, utilizing object detection, anomaly detection and generate an alert on time to provide an automated solution. By use of this cutting-edge technology, we can ensure enhanced safety, security and compliance regulations taking the realm of surveillance architecture beyond the limitations of response delays, inconsistent monitoring issues and insufficient real-time analysis. The successful implementation of this system could serve as a benchmark for other in-house systems.