SafeRoute: An AI-Powered Solution for School Bus Safety

The Project

SafeRoute solves a simple yet serious problem: uncertainty and safety during students’ daily bus commutes. Many students wait alone at bus stops, unsure if the bus is minutes away or has already passed. In extreme weather—freezing cold, heavy rain, or snow—standing outside for too long can be dangerous. This stress affects both students and parents. Parents often have no way to monitor their children, and schools frequently lack the tools to ensure safety along bus routes. Inspired by these challenges, I built SafeRoute, an AI-powered school bus app for students from elementary to high school. The platform provides accurate, real-time bus arrival predictions using a Python machine learning model that considers GPS coordinates, traffic, stop durations, weather, and time of day. Parents can track multiple children and buses in one account, receive customizable notifications, and confirm when students board or arrive home safely. Drivers benefit from hands-free safety alerts. Throughout the development process, I gathered feedback from students and parents, which helped me refine the user interface and functionality. Listening to their experiences allowed me to make the app more intuitive, informative, and tailored to real user needs, ensuring that it truly improves the daily commute. The most challenging part of building SafeRoute was assembling and configuring all the components together. Integrating Firebase, Flutter code, live GPS data, and AI predictions into a seamless, real-time system required careful design, testing, and iteration. Ensuring all parts worked reliably under real-world conditions was difficult but crucial for delivering accurate predictions and consistent safety alerts.

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