AirSignal

The Project

AirSignal is a smart traffic signal system that helps reduce air pollution during busy hours by using a Raspberry Pi and a PM2.5 sensor to monitor air quality. We used a Raspberry Pi 4B and a Grove Pi Board to connect a special sensor called the HM3301 PM2.5 sensor. This sensor checks the air for tiny dust particles called PM2.5, which are so small that we can’t see them. These particles can get into our lungs and make people sick, so we wanted to find a way to reduce them and make the air safer to breathe. When pollution levels are high, AirSignal intelligently adjusts traffic light timings to reduce harmful emissions and keep traffic flowing smoothly. It extends green lights in areas where PM2.5 levels are rising, especially along specific directions of the road where pollution is highest. By doing this, AirSignal helps clear congestion quickly, preventing cars from idling and releasing more harmful particles into the air. We used LEDs to act like traffic lights and wrote the code using Python in Thonny IDE. Our system checks the air, makes sure the information is correct, and then changes the lights to keep pollution as low as possible. AirSignal is better than normal traffic lights because it doesn’t just look at time or the number of cars—it actually cares about the air we breathe! By helping reduce harmful dust in the air, AirSignal can make cities cleaner and safer for everyone. We believe this project can help protect people’s health and make the environment better for the future. In this video, we’ll show you how AirSignal works, explain how we built it, and demonstrate how it can make our cities cleaner and healthier. 🌍💨 Don’t forget to like and subscribe to support our journey in Youtube channel building smart solutions for a better future! ## AirSignal Code and Build Guide ## http://castem.club/projects/AirSignal/

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Judge Feedback

This was a really cool project! I enjoyed watching the demos both in the classroom and in traffic space. This project has great thinking about positive outcomes, and a realistic vision of technology's potential contribution.

About the team

  • United Kingdom

Team members

  • Anvi
  • Ashar
  • Harish
  • Yiliang