Intelligent school bus monitoring using Ai for real-time parent alerts and child safety
In recent times, safeguarding the well-being of school children during their daily travel has turned into a major priority for parents and educational organizations. Conventional monitoring systems do not offer real-time tracking or smart alert features, which hinders quick responses to emergencies and maintaining steady communication with parents. This initiative introduces a Smart School Bus Tracking System that utilizes Artificial Intelligence (AI) and Global Positioning System (GPS) technology to improve child safety and offer parents real-time notifications. The system incorporates a camera module placed inside the bus that employs Haar Cascade-based facial recognition to identify and document every student as they enter and leave the vehicle. This guarantees precise recording of student attendance and movement. When a child's face is recognized and verified, an automatic notification is dispatched to the parent through email or a mobile alert, confirming the child's existence on the bus. Furthermore, the system utilizes GPS tracking, allowing parents to track the real-time location of the school bus via a mobile app or web portal, providing transparency and reassurance. The suggested system greatly enhances the safety, efficiency, and reliability of school transportation by merging computer vision methods with real-time tracking and automated communication. It decreases human mistakes, lowers the chance of students being misplaced, and guarantees that parents are regularly updated. This clever solution embodies a progressive strategy for ensuring child safety in school transport systems and corresponds with the increasing demand for intelligent monitoring in public infrastructure.
Institutions
- Vels University (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-03
- DOI
- https://doi.org/10.5281/zenodo.15586782
- Primary Topic
- IoT and GPS-based Vehicle Safety Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00