Smart and Sustainable Surveillance System

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Abstract

Safety and security are major concerns in the modern day. People and organizations can employ security mechanisms to safeguard their property for their homes or commercial enterprises. Present security systems involve the utilization of Assorted Sensors in cameras for video surveillance. This paper aims at providing one such idea to ensure the protection and security of one's property. This technique performs Face Recognition as an authentication procedure when a new face is detected by a snapshot. We propose to present a sensible, smart and sustainable Closed - Circuit Television (CCTV) camera with intrusion detection using the LBPH-Local binary pattern histogram algorithm, SIM-Structural Similarity Index Measure, Haar Cascade Classifier, and TKinter. By utilizing intrusion detection, CCTV cameras record real-time videos and process the video at the time of recording to search out the unwanted people arriving within the surveillance area. Our GUI has different buttons supported with features. Adding DL support would create broad scope in this paper such as with DL we would be able to add up much more functionality. We can have future enhancements on this paper such as creating Portable CCTV, Deadly weapon detection, Accident Detection, Fire Detection.

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APA

Karuna, G., Reddy, A. S., Vishal, K., Pavan, E., & Negi, G. S. (2023). Smart and Sustainable Surveillance System. In E3S Web of Conferences (Vol. 430). EDP Sciences. https://doi.org/10.1051/e3sconf/202343001030

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