Abstract
Security and safety are top concerns in our digital age, whether it is the safety of our own home or the security of the data. Doors serve as barriers that keep intruders out. In order to improve home security, a door security system is absolutely necessary. Face recognition-based door unlock system is used to protect guarded areas. The ability to identify visitors entering the house is a crucial part of any home security system. In this project, face recognition module is incorporated. Here, the images of authorized people are captured and stored in the database. Once the person arrives at the door, his/her image is compared with images stored in database. The door opens only when the person’s image matches with the database. When an unauthorized person arrives, due to mismatch of image the door remains locked and gives signal by glowing red LED. Alternately, in case of emergency, the visitor can open the door by entering the manual pin provided by the admin. The developed project offers double factor authentication that is leading to high secure door locking contributing a smart home concept. These features are obtained by integrating Arduino UNO, ESP32 CAM, L298N motor driver, GSM sms900a and 4 × 4 matrix keypad. This module can be implemented in apartments, commercial buildings and security required places like bank and corporate sectors, etc., to keep unauthorized persons like thieves and other sort of dangers at bay.
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Acknowledgements
The authors acknowledge Mr. Sridhar Head, center of design and Mr. Mettupelly Kumaraswamy, center of design, S R Engineering college for their support in preparing the model of the project. The authors also extend their gratitude to Principal and Management of S R Engineering college for helping us in carrying out this project work in the campus.
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Ahmed, S.M., Aditi, J., Afreen, A., Tharun, G., Gunjan, V.K. (2023). Face Recognition Based Home Security System to Detect Usual/Unusual person Using IoT. In: Kumar, A., Gunjan, V.K., Hu, YC., Senatore, S. (eds) Proceedings of the 4th International Conference on Data Science, Machine Learning and Applications. ICDSMLA 2022. Lecture Notes in Electrical Engineering, vol 1038. Springer, Singapore. https://doi.org/10.1007/978-981-99-2058-7_19
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