The fusion of AI and drone technology has dramatically improved wildfire detection speed, enabling early response and playing a key role in minimizing massive damage. Moving beyond the limitations of previous wildfire monitoring systems that relied on manpower or fixed surveillance cameras, AI-based drones are building more effective wildfire response systems through real-time data analysis, high-speed detection, autonomous flight, and monitoring capabilities.
Real-time Data Analysis and Predictive Alerts
AI drones are not simply surveillance devices flying in the sky. They collect and deeply analyze various environmental data such as temperature, humidity, and wind in real-time through thermal imaging cameras and various sensors. This real-time data analysis allows for rapid prediction of wildfire possibilities and immediate warnings when risk signs are detected, enabling preemptive responses.
According to the Korea Forest Service’s Smart Forest Disaster Response System, AI drones can immediately grasp situations on-site and quickly deploy response teams when anomalies are detected through instant notifications. This enables rapid response that was impossible with existing watchtowers or fixed cameras.
Remarkable Speed in Wildfire Detection
Some cutting-edge AI drone systems boast the impressive ability to detect flames and smoke in just 2 seconds. Moreover, they measure the exact temperature of fire locations through thermal imaging cameras and immediately report to control rooms, providing accurate information for the initial suppression phase. This high-speed detection capability plays a decisive role in securing the initial golden time to prevent wildfire spread and minimize damage.
According to research from the Electronics and Telecommunications Research Institute (ETRI), drone systems applying AI-based image recognition technology can detect wildfires up to 15 times faster than conventional manpower-based surveillance methods. A significant advantage is the ability to capture accurate wildfire signs even in situations with limited visibility, such as at night or in adverse weather conditions, using thermal imaging technology.
Autonomous Flight and Intelligent Monitoring
AI drones patrol autonomously along pre-set flight paths, focusing on areas with high risk of wildfire occurrence. They are also designed to optimize battery life and detection range to efficiently monitor large areas and autonomously perform necessary measures. This autonomous flight and monitoring capability solves the difficulties of deploying manpower and enables continuous surveillance of extensive areas.
According to a report from the National Institute of Forest Science, a single AI drone can effectively monitor about 500 hectares of forest area, which is too large an area to monitor with manpower. Especially given Korea’s geographical characteristics with many rugged mountainous terrains, drone-based surveillance systems are proving highly effective in preventing wildfires.
A Gangwon Province Forest Service official explained, “Since the introduction of the AI drone system, the initial wildfire suppression rate has improved by about 30%, which has had a direct impact on protecting forest resources and reducing property damage.”
Key Factors Enhancing Accuracy
The excellent wildfire detection capabilities of AI drones are based on the following key factors:
Large-scale Data Learning
AI systems can accurately identify the colors and shapes of flames and smoke by learning from approximately 560,000 vast fire-related data. Based on this accumulated data, AI learns patterns in various environmental conditions similar to actual wildfire situations, reducing false detection rates and increasing detection accuracy.
According to research results from the Korea Advanced Institute of Science and Technology (KAIST) Artificial Intelligence Research Institute, deep learning-based AI models have greatly improved their ability to distinguish between natural phenomena such as simple smoke or fog and actual wildfires by learning wildfire patterns according to various weather conditions and time periods.
Integration of Satellite and IoT Technologies
Data from organizations like NASA and ESA’s satellite observation data and IoT sensor networks are integrated to identify high-risk wildfire areas early and predict wildfire spread paths. This allows for early detection and response to wide-ranging risk signs that were difficult to capture with ground-based surveillance systems alone.
Korea’s Forest Service is building a system that integrates satellite imagery and drone-based surveillance systems to create nationwide wildfire risk maps and optimize drone patrol routes based on these. Such integrated systems enable intensive monitoring of areas with high risk of wildfire occurrence.
Precise Machine Learning Models
High-performance machine learning algorithms such as random forest classifiers are applied to identify hotspots and actual wildfires with high accuracy, with some systems achieving detection success rates of 98.7%. These precise machine learning models support AI drones in detecting and responding to wildfires with high reliability in real environments.
A Seoul National University Computer Engineering research team has introduced technology that detects not only static images but also fire pattern changes over time by developing a hybrid model combining CNN (Convolutional Neural Network) and LSTM (Long Short-Term Memory) networks. This technology shows excellent performance especially in capturing subtle smoke changes in the early stages.
Real-world Application Cases
AI drone wildfire detection technology is already being used in various regions, and its effectiveness has been proven.
Gangwon Province Wildfire Prevention System
After the large-scale wildfire in 2019, Gangwon Province fully introduced an AI drone-based wildfire surveillance system. It conducts intensive drone-based patrols especially during the dry spring season and autumn leaf-falling period. In 2021, this system detected 7 wildfires in their early stages, preventing them from spreading into large-scale fires.
A Gangwon Province Forest Service official stated, “The AI drone system is particularly effective in remote areas difficult for people to access and at night, and has reduced the average wildfire initial discovery time from 25 minutes to within 5 minutes.”
Jeju Island Smart Forest Management
Since 2022, Jeju Island has been operating a smart forest management system using AI drones to protect the forests around Mount Halla. This system monitors real-time fire risks from illegal cooking or smoking, especially during periods with many tourists, and is also equipped with the function of delivering warning messages through speakers when dangerous behavior is detected.
According to a report from Jeju Island’s Environmental Conservation Bureau, the number of fire incidents within Mount Halla National Park has decreased by about 40% compared to the previous year since the introduction of this system, and the fire risk from illegal activities around hiking trails has been significantly reduced.
Gyeongsangbuk-do Wildfire Early Warning System
Since 2023, Gyeongsangbuk-do has been building and operating a wildfire early warning system combining AI drones and IoT sensors. This system conducts real-time assessment of wildfire risk by having AI analyze integrated data from temperature, humidity, wind direction, and wind speed sensors installed throughout forest areas and drone video data.
A Gyeongsangbuk-do Fire Department official explained, “The integrated operation of sensor networks and drones has enabled us to identify areas with high risk of wildfire occurrence in advance and take preventive measures,” adding, “AI’s analysis of weather data and past wildfire occurrence patterns has been particularly helpful in improving the accuracy of wildfire risk forecasts.”
Future Development Directions
AI drone technology continues to evolve and is expected to develop into more advanced wildfire detection and response systems in the future.
Longer Flight Time and Wider Surveillance Range
Currently, most drones have flight times of about 30 minutes to 1 hour due to battery constraints. However, next-generation drones using hydrogen fuel cells or solar panels are expected to extend flight time up to 3-4 hours. This means one deployment can monitor a wider area.
The Korea Aerospace Research Institute is pursuing the development of high-altitude solar-powered unmanned aircraft capable of continuous flight for 24 hours, and if this technology is applied to wildfire monitoring drones, a single drone will be able to continuously monitor a wide area.
5G-based Real-time Collaboration System
With the spread of 5G networks, systems where multiple drones share information and collaborate in real-time are expected to become possible. This will enable multiple drones to simultaneously monitor different areas while performing integrated analysis, beyond the limitations of a single drone.
The ‘5G-based Drone Swarm System’ being jointly developed by SK Telecom and the Electronics and Telecommunications Research Institute aims to maximize the efficiency of wildfire detection and response by having up to 50 drones fly simultaneously and exchange information, with a central AI system analyzing this in real-time.
Combination of AI and Robotics Technology
In the future, it is expected that integrated systems will be established where fire-fighting robots are automatically deployed to wildfire sites detected by AI drones to perform initial extinguishing operations. This will enable rapid initial response without risk of human casualties.
The Korea Institute of Robot and Convergence is developing a prototype of a ‘Smart Wildfire Response System’ linking drones and ground fire-fighting robots, aiming for practical application by 2026. When this system is completed, the combination of drone detection capabilities and robot initial extinguishing capabilities will enable more effective wildfire response.
Conclusion: Steps Toward a Safer Future
AI drone systems provide much faster and more precise detection capabilities compared to existing wildfire surveillance methods, and dramatically strengthen real-time response capabilities. These innovative technologies are expected to play an important role in protecting valuable forest resources and minimizing human and property damage. AI drone technology will contribute even more significantly to future society as a powerful tool for environmental protection and disaster recovery, beyond simple surveillance.
Forests in Korea cover approximately 63% of the national land and are a precious resource. As dry weather and strong winds increase due to climate change, the risk of wildfires is also rising. In this environment, AI drone technology will serve as a reliable guardian protecting our precious forests. We hope to see more advanced AI drone-based wildfire detection systems spread nationwide through continuous cooperation between the Forest Service, local governments, and technology companies.
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