A system that collects and analyzes fire-related posts from social media (SNS) and converts them into structured information. It provides accurate location information by combining real-time SNS data with external sources for early fire detection.

Early detection of forest fires is crucial but challenging. Traditional methods like CCTV + AI, IoT sensors, satellites, and drones require monitoring vast mountainous areas continuously. Due to the extensive coverage needed, it's difficult and expensive to install CCTVs that capture all potential fire hazards.

However, humans can also recognize forest fires when they occur. Many people hike or walk around mountains and can spot fires early. Human visual capabilities sometimes surpass AI detection systems. We aim to leverage this social capacity as another tool for capturing forest fires as early as possible.

Humans can identify small fires and want to share this information as social beings. There is evidence that people sometimes capture forest fires earlier than CCTV or other traditional monitoring systems. Our system harnesses this collective human intelligence through social media to create an additional layer of early fire detection.