Abstract
Computer vision and IoT-based systems play a significant role in the field of home security. In this paper, we present the design and implementation of IoT-based home security with integrated intrusion detection to minimize the damages caused by the burglary. Also, the proposed system combines a web server with the web application to remotely access and control their status. This system is cost-effective and efficient enough for monitoring home automatically. It includes a real-time identification system that can process images faster. The aim of this paper is to ensure home security by identifying the face. A single-board computer called the Raspberry Pi will capture the images, and from that, the system will detect and identify the face. This project uses the Haar-cascades algorithm for face detection and uses LBPH algorithm for face recognition and uses SQLite which is a lite version of SQL for the Raspberry Pi, along with MYSQL to update the database to the web server. Finally, using an IoT application called Twillo, the images and notifications will be sent to the user by SMS. According to the experimental results, the system can be used as a real-time system. This system can be used without any human intervention. The system includes instant approachability, efficient usage of power and fits user service.
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Acknowledgements
The scientific research foundation NUPTSF sponsored this work (Grant No. NY-214144) and NSFC (Grant no. 61701260). Special thanks to our team members Hasan Salman, Md Arifur Rahman Nayeem, Asif Mohammad who contributed to the experiment of face recognition(Fig. 3, right side) and successfully got the results.
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Salman, H. et al. (2020). A Low-Cost Internet of Things-Based Home Security System Using Computer Vision. In: Satapathy, S., Bhateja, V., Nguyen, B., Nguyen, N., Le, DN. (eds) Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 1014. Springer, Singapore. https://doi.org/10.1007/978-981-13-9920-6_17
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DOI: https://doi.org/10.1007/978-981-13-9920-6_17
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