Smart Monitoring System for Housing Societies based on Deep Learning and IoT
by Neha Koppikar* 
, Nidhi Koppikar
Department of Data Science MPSTME, SVKMs NMIMS University, Mumbai, India
* Author to whom correspondence should be addressed.
Journal of Engineering Research and Sciences, Volume 2, Issue 12, Page # 15-22, 2023; DOI: 10.55708/js0212003
Keywords: Face Recognition, Raspberry Pi, Edge Vision, Body Temperature
Received: 19 September 2023, Accepted: 16 December 2023, Published Online: 30 December 2023
APA Style
Chicago/Turabian Style
IEEE Style
Since 2020, people have been getting their body temperatures checked at every public location, social distancing has become a norm, and it has become essential to know who has been in contact with whom. Therefore, we needed a system that helped us solve these challenges, especially in housing societies, as most of the general public stayed home more than ever. Therefore, it has become essential to safeguard housing societies. There has been a lot of research in building a security system, but there needs to be more research that targets housing societies as the end users. We have devised a possible solution, including a facial recognition system with body temperature sensing on a Raspberry Pi. The best part of our application is the automated data collection page on aweb application, which makes collecting facial images more straightforward and faster. Code for this project can be found at: https://github.com/NehaKoppikar/Monitoring-System-for-Housing-Societies-using-Deep-Learning-and-IoT
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