Prevention of School Shooting using Neural Networks and Computer Vision

The main goal of the project is to focus on resolving the major threat or problem of school shootings by developing a system that provides the best security within schools and avoid any threat that may arise. The project is planned such a way that it uses advanced concepts such as Deep Neural Networks which would allow facial recognition of the students and teachers and therefore permit them into the school campuses based on certain conditions where the person should not carry harmful weapons or anything that would cause a threat to the children. Deep Neural Networks using algorithms like YOLOv3 can be used to identify the person that could carry harmful weapons, and other color detection algorithms to distinguish dress color. Computer Vision plays a major role in weapon detection and thus, ensures the safety within the school premises. Further, features like buzzers and alert notifications can be used to alert the students and the higher authorities and also the nearest police department. the images of the suspects can be taken and directed to the commissioners for further actions.