Inspiration

We noticed that overflowing bins, mixed waste, and inefficient collection routes are common problems in cities. We wanted to use AI and smart technology to make waste collection more organized and recycling easier.

What it does

Our project, AI-Based Smart Waste Management and Recycling System, monitors waste bins and helps improve waste collection. It uses sensors to check bin fill levels and AI-based image classification to identify waste types. This information can help collection teams prioritize bins, plan better routes, and separate recyclable materials from general waste.

How we built it

We designed a system that combines smart bin monitoring, AI-based waste classification, and a dashboard. Bin sensors provide fill-level information, while image classification helps identify the type of waste. The collected data can be used to display bin status and support more efficient waste collection and recycling decisions.

Challenges we ran into

One challenge was bringing bin monitoring, waste classification, and route planning together in one system. We also had to consider how the system would handle different waste types and changing bin conditions. Making the system practical for real-world waste collection was another important challenge.

Accomplishments that we're proud of

We are proud to develop a project that addresses a real environmental problem using AI and smart technology. Our main accomplishment is bringing together waste monitoring, waste classification, and collection planning in one solution that can support cleaner surroundings and better recycling practices.

What we learned

We learned how AI and sensor-based monitoring can help solve everyday environmental problems. We also understood the importance of proper waste segregation, efficient collection routes, and using technology to reduce unnecessary waste collection trips.

What's next for Smart Waste Management and Recycling System Using AI

We plan to improve the accuracy of waste classification, test the system with different types of waste, and develop a more reliable route optimization method. In the future, we would like to test the system with real bins and collection data to understand its performance in practical conditions.