IoT Based Real-Time Face Recognition and Weapon Detection Door Lock System Using Raspberry Pi
Author(s):
Ishwari Thakur, Ruchika Chaudhari, Jagruti Pawar, Punam Khairnar, P. R. Kulkarni
Keywords:
Artificial Intelligence, Face Recognition, IoT, Open CV, Raspberry Pi, Security, Weapon detection
Abstract
Nowadays the number of thefts and identity fraud has become a very serious problem & A weapon is any object that can do harm to another individual or group of individuals. In order to avoid these problems of thefts and identity fraud, a face recognition & weapon detection system must be established. Smart door lock security systems has become a necessity in daily life. Security systems prevent robbery in highly secure areas such as home environments with lesser power consumption and also more reliable standalone security devices for door lock systems as well as Intruder detection. Also nowadays, privacy and security has become an important issue in our day to day life. Burglary and global attacks continue to escalate,so it is exigent to find Different solutions to ensure the safety of individuals. And, to ensure safety our daily life, a lot of research is going on in the field. Security matters to this day and that’s why we are up with this project of Face recognition and weapon detection systems. We are developing this project using Raspberry-pi, where a person is allowed to enter the house only if his/her face is recognized by the proposed system and he does not carry any weapons with him. This system is more reliable and effective through the point of view of security. The scope of the proposed system is to develop a security access control application based on face recognition. The haar-like features is used for face detection and face recognition. In order to achieve a system with higher accuracy and effectiveness,we use Open CV libraries and python computer language. The Training and identification by the proposed system is done in embedded device known as Raspberry Pi.
Article Details
Unique Paper ID: 151742

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 812 - 815
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