Intelligent Surveillance System with Mask Detection and Temperature Monitoring

Abstract

An efficient and adroit surveillance system is im-perative in the fast-paced digital world, with a monumental rise in video-based surveillance systems for security and monitoring. The pandemic has created the need for effective surveillance and made it more relevant than ever before. The AI-based surveillance system proposed in this paper is capable of performing the traditional functions of a surveillance system and checking if a person is wearing a mask and if his temperature is below a certain threshold. The proposed surveillance system is a video-based surveillance system capable of logging people who are not wearing a mask or whose temperature is not below a specified value. This system is implemented with Raspberry Pi as the central hub for processing, extracting, and analyzing the video stream from a camera. The proposed system aims to identify the mask on people by using a cascade classifier generated by Machine learning techniques, thus mulling down the effects of external factors (lighting condition, position, etc.) that affect the performance of a traditional video surveillance system.