Advanced Scanning LiDAR for Real-Time Detection of Wildfires and Industrial Fires

This study introduces the development and application of the advanced scanning LiDAR system, SMART LiDAR MK-II(Samwoo TCS co., Ltd), designed for the early detection of wildfires and industrial fires. Traditional fire detection methods face limitations due to diverse atmospheric conditions, topographical factors, and variability in fire and smoke characteristics. To address these challenges, monitoring systems with spatial resolutions below 30 meters are essential. The SMART LiDAR MK-II employs dual wavelengths (532 nm and 1064 nm) and provides 360° observations with an angular resolution of approximately 3° within a 30-minute interval, enabling the real-time detection of smoke and particulate matter under various environmental conditions.

 

The system was validated through field deployment in the Sihwa Industrial Complex, South Korea, during a fire at an automotive painting factory on July 22, 2024. Positioned at a monitoring height of 55 meters and approximately 20 meters from the fire source, the SMART LiDAR MK-II detected smoke with peak PM₁₀ and PM_2.5 concentrations of 724 µg/m³ and 334 µg/m³, respectively. The smoke plume was observed dispersing over 5 km northward, influenced by prevailing winds. Furthermore, the system successfully captured the temporal reduction in particulate matter concentrations following fire suppression, demonstrating its capability to monitor emission dynamics and dispersion patterns.

 

Currently, SMART LiDAR MK-II is undergoing rigorous waterproof and dustproof testing to ensure operational reliability under diverse conditions, with commercialization in progress. This cutting-edge technology represents a significant advancement in LiDAR-based fire detection, offering high spatial resolution, sensitivity, and reliability for real-time monitoring of smoke emissions and atmospheric impacts. The results highlight the transformative potential of SMART LiDAR MK-II to enhance global fire detection and environmental monitoring capabilities.

 

Acknowledgment: This research was supported by a grant (2023-MOIS-20024324) from the Ministry-Cooperation R&D Program of Disaster-Safety funded by the Ministry of Interior and Safety (MOIS, Korea).