Bus Buddy

Solving the Biggest Transit Challenge: Real-Time AI-Powered Bus Crowd Monitoring The Problem One of the biggest challenges for public transit users during rush hours is overcrowded buses. Existing solutions rely on user feedback to estimate crowd levels, which is inaccurate, inconsistent, and fails to provide real-time insights. Moreover, these solutions do not inform users whether a bus is at full capacity or has space available, leading to frustration, delays, and a poor transit experience for Durham Region Transit (DRT) users.

🚨 Current limitations:

Inaccurate, user-reported data No real-time monitoring of bus occupancy Lack of transparency on whether a bus can accommodate more passengers Our Solution: AI-Driven Real-Time Bus Crowd Monitoring We have developed an AI-powered transit mapping application that accurately tracks bus occupancy in real time. Unlike existing solutions, our application monitors and reports the number of passengers onboard, alerts users if a bus is full, and allows drivers to update bus status dynamically.

🚀 Key Features: ✅ Live crowd tracking – AI-powered sensors count passengers in real-time ✅ Bus availability notifications – Users are informed if a bus is full or has space ✅ Driver updates – Bus drivers can manually update status for accuracy

But that's not all! Our application goes beyond just crowd control. With AI-driven analytics, we can predict transit patterns and optimize bus scheduling for efficiency and reliability.

How We Developed This Idea In 2025, we started by considering a general mapping solution. However, as we researched, we realized competing with platforms like Google Maps or Transit in just 24 hours was unrealistic. Instead, we focused on a real, unsolved problem—one that could genuinely improve the daily lives of transit users.

💡 Why Our Idea is Unique:

No existing transit platform provides real-time AI-powered bus crowd tracking This innovation directly improves ridability, user experience, and efficiency We are proud to be the first team to introduce this intelligent solution Impact of Our Solution Our application solves critical transit issues, including: ✅ Reducing waiting times in cold or rush hours ✅ Eliminating uncertainty about bus occupancy ✅ Enabling better trip planning, saving time and money

By providing real-time, reliable data, passengers can confidently plan their commutes without worrying about unexpected delays or overcrowding.

Technology Stack 🛠 Backend: Flask, Redis, YOLO, Open Data, PostgreSQL, Protocol Buffers 🎨 Frontend: React, TailwindCSS 🗺 Data Sources: OpenStreetMap, GTFS static data 🔮 Future Enhancements: AI-driven bus frequency analysis, real-time position prediction using TensorFlow.js

Hardware Implementation To ensure scalability and real-time accuracy, we integrate hardware modules: 🔹 Raspberry Pi (Pico 3, 4, 5) + Camera Modules for AI-powered crowd detection 🔹 GPS integration (for future improvements)

Driver Application & Future Enhancements Even without AI, our system allows drivers to manually update bus status—ensuring early-stage implementation is effective.

🚀 Planned Upgrades:

Cross-platform support for mobile and web Advanced authentication & security Hardware integration for enhanced accuracy 🔥 We are proud to be pioneers in solving a real, everyday transit challenge with AI-driven innovation. Our solution isn’t just an idea—it’s a game-changer for urban mobility. 🚍

Built With

• apilimiter
• fastapi
• gtfs
• openstreetmap
• pgroute
• postgresql
• protobuff
• python
• react
• redis
• tailwind
• yolo