The emergence of edge computing allows the processing of data at the source of data. By combining edge computing with the cloud and the Internet of Things (IoT), data collection, processing, and storage can be managed effectively. This combined architecture has given hope for an automated surveillance system. This paper presents an edge–cloud – IoT-based Surveillance System that uses computer vision algorithms in the edge devices to process the video feed captured by cameras and store the required video backup in the cloud through IoT. This paper discusses the protocols used, task scheduling methods, metrics used to analyze the quality of service, and security and privacy issues. The dataset is collected from the SRMIST, Kattankulathur campus. The architecture is tested on the students’ activities and is found efficient.
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