TechGuard: Violence Detection Technology for Schools
This project targets the design and implementation of an automated violence detection system called “TechGuard” that harnesses the power of machine learning technology. Machine learning has emerged as a dominant trend, widely adopted by industry leaders like Facebook, Google, and Uber. Our project leverages machine learning algorithms to create a violence-minimal environment in schools. Four algorithms are employed: fight detection, weapon detection, verbal abuse detection, and facial recognition. The system incorporates a mobile application for communicating notifications and recommendations to parents and school staff, as well as enabling access to a student`s violence record. Additionally, a wrist-worn device is provided for students to request additional protection against verbal abuse. Through this integration of machine learning and automation, TechGuard aims to enhance safety and security within school environments.
Project Details
- Student(s): Nivine Arabi, Randa El Rifai, Jana Loubani, and Lea Mansour
- Advisor(s): Dr. Chadi Abou Rjeily
- Year: 2022-2023