Forest Fire Detection with Drone Camera Using Computer Vision and Artificial Intelligence Technology

Challenge Background

Climate change is increasing the frequency of forest fires and the damage they cause and threatening people with food and water scarcity, increased flooding, extreme heat, more disease, and economic loss. The World Health Organization (WHO) calls climate change the greatest threat to global health in the 21st century and one of the most talked-about consequence of the crisis is forest fires putting millions of our children at risk from air pollution.

Indonesia’s forest fires have made headlines globally over the past few years. According to the latest report in 2019 from the Indonesian National Disaster Management Agency (Badan Nasional Penanggulangan Bencana or BNPB) there are more than 2,000 hotspots in six provinces mainly in Kalimantan and Sumatera Islands. From January to August 2019, 328,724 Ha of land have been burnt by the fire.

The Problem

Indonesia’s forest fires have made headlines globally over the past few years. According to the latest report in 2019 from the Indonesian National Disaster Management Agency (Badan Nasional Penanggulangan Bencana or BNPB) there are more than 2,000 hotspots in six provinces mainly in Kalimantan and Sumatera Islands. From January to August 2019, 328,724 Ha of land have been burnt by the fire.

We are now progressing on building AI solution for powering drones in disaster relief scenarios and operations such as wildfires to facilitate early fire detection before a catastrophic event happens.

Goal of the Project

1. Collect more annotated fire images and scope it to forest distribution.
2. Build a dedicated model to detect fires in a forest.
3. Optimize the model so it can run on edge devices (drones, UAVs etc).
4. Publish interactive dashboard to display how efficient our AI solution to detect fires.

Project Timeline

What you'll learn

1. Understand the problem and current methods to solve the forest fire issue in Indonesia.
2. Participate in collecting relevant datasets for the issue.
3. Engage in the research process of building an AI solution for solving the issue.
4. Educate the community by establishing a sense of urgency regarding the forest fire issue in Indonesia.