Greenwatch

Inspiration

We were inspired to create this project by the increasing threat of forest fires around the world. With climate change leading to more frequent and intense fires, we wanted to use technology to proactively address this issue.

What it does

How we built it

Our Forest Fire Detection System uses a network of sensors placed strategically in forests. These sensors monitor temperature, humidity, and smoke levels, sending data to a central hub for analysis. The system uses machine learning to interpret this data, trained on historical fire data to identify potential threats early. When a fire is detected, it alerts authorities with the fire's precise location for rapid response.

Challenges we ran into

Developing such a system had its challenges. Ensuring reliable data transmission from remote areas was tough, but we implemented robust communication protocols to solve this. Designing energy-efficient sensors that can withstand harsh conditions was another challenge, but we found solutions through power management strategies and rugged hardware designs.

Accomplishments that we're proud of

We're proud to have created a system that combines IoT, sensor networks, and AI to protect the environment and communities from forest fires.

What we learned

During the project, we explored various fields, including IoT, sensor networks, data analysis, and AI. We learned how to build a system of sensors that can collect real-time data from remote forests and use machine learning to detect signs of fire early.

What's next for Greenwatch

As we continue to refine and enhance the system, we hope to contribute to a future where our precious natural resources are safeguarded, and the delicate balance of ecosystems is preserved for generations to come.