Mountain forest intelligent fire monitoring and early disposal system

Abstract

The present application relates to the technical field of forest fire prevention, and discloses a mountain forest intelligent fire situation monitoring and early treatment system, which comprises a space-air-ground multi-source three-dimensional monitoring module, a fire situation AI intelligent identification and positioning module, a hierarchical early automatic treatment module, a mountain adaptation power supply communication module and an intelligent linkage command module; the space-air-ground multi-source three-dimensional monitoring module adopts a four-level three-dimensional architecture, and comprises a ground low-power consumption sensing unit arranged in the forest, a lookout tower dual-spectrum intelligent unit arranged at a commanding height, a tethered floating monitoring platform unit in the low-altitude airspace and an unmanned aerial vehicle inspection cluster unit. Through the complementary of the four-level monitoring network, the ground node detects hidden fires, the lookout tower continuously monitors day and night, the floating platform covers a wide range, and the unmanned aerial vehicle checks in close proximity, so that 24-hour full-coverage monitoring is realized; the multi-spectrum fusion AI algorithm excludes various interferences, the identification accuracy is greater than or equal to 98%, the false alarm rate is less than or equal to 2%, and the missing report rate is reduced to below 1%, which is much better than the traditional monitoring mode.

Description

Technical Field

[0001] This invention relates to the field of forest fire prevention technology, specifically to an intelligent forest fire monitoring and early response system for mountainous areas. Background Technology

[0002] Forest fire prevention refers to the systematic work of preventing and fighting forest fires through administrative and technical means. Based on the location and spread characteristics of the fire, forest fires can be divided into three categories: surface fires, crown fires, and underground fires. Among them, natural fire sources (such as lightning strikes) account for only 1% of the total causes of fires.

[0003] Forest fires are among the most destructive and difficult-to-control natural disasters. Over 70% of my country's land is mountainous and forested, with complex terrain, poor transportation, and sparse populations. Late fire detection and slow response are the core reasons why small fires escalate into major disasters. According to statistics from the Ministry of Emergency Management in 2025, more than 85% of major and catastrophic forest fires in my country originated from the failure to detect and control fires in their early stages; the average window from ignition to the formation of a large-scale fire is only 30 minutes.

[0004] Traditional manual lookout towers rely on human experience and are affected by nighttime, fog, and mountainous terrain, resulting in a false alarm rate exceeding 40%. Satellite remote sensing has a long revisit cycle and low spatial resolution, only able to monitor large fires on the square kilometer scale, unable to detect initial surface fires. Ordinary visible light video monitoring is affected by sunlight reflection, clouds, fog, and straw burning, resulting in a false alarm rate as high as 30%, and cannot work at night. Existing systems only have monitoring and early warning functions, lacking early response capabilities. From the discovery of a fire to the arrival of firefighters, it takes an average of more than 45 minutes, and even more than 2 hours in complex mountainous terrain. The optimal time to extinguish an initial fire is within 10 minutes of its ignition, and most small fires have already spread into a disaster before personnel arrive. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent forest fire monitoring and early response system for mountainous areas, which solves the problems of limited monitoring methods, high rates of missed and false alarms, and severely delayed response and handling, resulting in missed opportunities for optimal firefighting.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solution: a mountain forest intelligent fire monitoring and early response system, including a multi-source three-dimensional monitoring module, a fire AI intelligent identification and positioning module, a graded early automatic response module, a mountain-adaptive power supply and communication module, and an intelligent linkage command module; The multi-source three-dimensional monitoring module adopts a four-level three-dimensional architecture, including a ground-based low-power sensing unit deployed under the forest, a dual-spectrum intelligent unit deployed at a commanding height, a tethered floating monitoring platform unit at medium and low altitudes, and a drone inspection cluster unit, to achieve all-time and full-coverage fire monitoring. The fire AI intelligent identification and positioning unit adopts an edge + cloud two-level computing architecture, with a built-in multispectral fusion fire identification algorithm. It combines visible light, infrared thermal imaging, and smoke characteristics to make a comprehensive judgment, eliminates environmental interference, and combines GIS three-dimensional terrain to achieve accurate fire point positioning. The graded early automatic response module adopts a three-level architecture of pre-positioned fixed-point response + UAV mobile response + isolation zone protection, including a pre-positioned intelligent fire extinguishing projectile launching unit, a high-pressure fine water mist isolation unit and a UAV fire extinguishing delivery unit, which automatically activates the corresponding level of response measures after receiving the alarm. The mountain-adaptive power supply and communication module includes a solar energy storage unit, a Mesh self-organizing network unit, and a Beidou short message unit, enabling self-sufficiency in power supply and seamless communication coverage in remote mountainous and forested areas. The intelligent linkage command module communicates with all units and realizes hierarchical early warning, fire simulation, force dispatch and closed-loop management of the whole process based on GIS three-dimensional map.

[0007] Preferably, the watchtower's dual-spectrum intelligent unit is equipped with a visible light + infrared thermal imaging dual-spectrum gimbal camera that can rotate 360° continuously, with a single unit covering a radius of 5 to 8 km, and can identify open flames and high-temperature smoldering fires as small as 0.1 m²; the edge end has a built-in AI recognition chip that analyzes the image in real time, with an accuracy rate of ≥98% and a false alarm rate of ≤2%.

[0008] Preferably, the ground-based low-power sensor node unit integrates infrared flame, smoke, temperature and humidity, wind speed and direction sensors, adopts a sleep-wake low-power mode, has a sleep current ≤20μA, a detection radius of 50m, uses LoRa communication, and has a service life of ≥5 years powered by solar energy and batteries.

[0009] Preferably, the tethered buoyant monitoring platform unit is powered and communicated via a tethered cable, with an airborne altitude of 200–500 m, and is equipped with a multispectral camera and a thermal imager. A single unit can cover an area of ​​≥30 km², enabling large-scale continuous monitoring.

[0010] Preferably, the front-mounted intelligent fire extinguishing projectile launching unit is equipped with multiple ultra-fine dry powder fire extinguishing projectiles, with built-in infrared fire tracking and automatic aiming gimbal, a range of 100-200m, and automatically launches within 30 seconds after receiving a fire signal; the high-pressure fine water mist isolation unit is deployed in the firebreak, and automatically activates to form a water curtain to block the fire when the fire approaches.

[0011] Preferably, the front-mounted intelligent fire extinguishing projectile launching unit is equipped with multiple ultra-fine dry powder fire extinguishing projectiles, with built-in infrared fire tracking and automatic aiming gimbal, a range of 100-200m, and automatically launches within 30 seconds after receiving a fire signal; the high-pressure fine water mist isolation unit is deployed in the firebreak, and automatically activates to form a water curtain to block the fire when the fire approaches.

[0012] Preferably, the fire AI intelligent identification and positioning module adopts a lightweight improved YOLOv8 model, with a single frame identification time of ≤50ms at the edge end. It can distinguish between three types of fires: open flame, smoldering, and smoke. After cross-positioning by multiple devices, the fire point positioning accuracy is ≤5m, and it can automatically calculate the fire spread trend.

[0013] Preferably, the graded early automatic treatment unit is equipped with a three-level triggering mechanism: Level 1 warning: Automatically dispatch gimbals and drones for close-range verification; Level 2 warning: Triggers the automatic response of the pre-positioned fire extinguishing device and simultaneously notifies the forest ranger; Level 3 warning: Activate the fine water mist isolation device, dispatch drones to drop bombs, and coordinate with professional fire-fighting teams.

[0014] Preferably, the intelligent linkage command module includes a GIS three-dimensional command unit, a hierarchical early warning unit, a fire simulation unit, and a force dispatch unit. After a fire occurs, it automatically generates a firefighting plan, issues early warnings through multiple channels, and achieves closed-loop management throughout the entire process.

[0015] This invention provides an intelligent forest fire monitoring and early response system for mountainous areas. It offers the following advantages: 1. This invention achieves 24-hour full coverage monitoring through a complementary four-level monitoring network of ground, air, and space, with ground nodes detecting hidden fires, watchtowers providing continuous day and night monitoring, floating platforms providing wide-area coverage, and drones conducting close-range verification. The multispectral fusion AI algorithm eliminates various interferences, achieving an accuracy rate of ≥98%, a false alarm rate of ≤2%, and a missed alarm rate of less than 1%, which is far superior to traditional monitoring methods.

[0016] 2. The pre-emptive response equipment of this invention is linked with the monitoring system. Automatic response can be initiated within 10 minutes after the fire is confirmed. More than 90% of initial fires can be extinguished before personnel arrive, completely solving the problem of slow response in the traditional mode and greatly reducing the probability of major fires.

[0017] 3. This invention features a solar-powered self-sufficient power supply + Mesh self-organizing network design, eliminating the need for mains power and fiber optic cabling. It is suitable for the complex environment of remote mountainous forest areas, shortening the installation and deployment cycle by 70% and reducing operation and maintenance costs by 50%. Beidou backup communication ensures uninterrupted early warning even in extreme environments. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a schematic diagram of the multi-source three-dimensional monitoring module for air, space, and ground of the present invention; Figure 3 This is a schematic diagram of the multi-source three-dimensional monitoring module for air, space, and ground of the present invention; Figure 4This is a schematic diagram of the multi-source three-dimensional monitoring module for air, space, and ground of the present invention; Figure 5 This is a schematic diagram of the multi-source three-dimensional monitoring module for air, land, and space of the present invention. Detailed Implementation

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0020] Please see the appendix Figure 1 -Appendix Figure 5 This invention provides a mountain forest intelligent fire monitoring and early response system, including a multi-source three-dimensional monitoring module, a fire AI intelligent identification and positioning module, a graded early automatic response module, a mountain-adaptive power supply and communication module, and an intelligent linkage command module. The multi-source three-dimensional monitoring module adopts a four-level three-dimensional architecture, including a ground-based low-power sensing unit deployed under the forest, a dual-spectrum intelligent unit deployed at a commanding height, a tethered floating monitoring platform unit at medium and low altitudes, and a drone inspection cluster unit, to achieve all-time and all-coverage fire monitoring. The fire AI intelligent identification and positioning unit adopts an edge + cloud two-level computing architecture, with a built-in multispectral fusion fire identification algorithm. It combines visible light, infrared thermal imaging, and smoke characteristics to make a comprehensive judgment, eliminates environmental interference, and combines GIS three-dimensional terrain to achieve accurate fire point positioning. The graded early automatic response module adopts a three-level architecture of pre-positioned fixed-point response + drone mobile response + isolation zone protection, including a pre-positioned intelligent fire extinguishing projectile launching unit, a high-pressure fine water mist isolation unit and a drone fire extinguishing delivery unit. After receiving the alarm, it automatically activates the corresponding level of response measures. The mountain-adaptive power supply and communication module includes a solar energy storage unit, a Mesh self-organizing network unit, and a Beidou short message unit, enabling self-sufficiency in power supply and seamless communication coverage in remote mountainous and forested areas. The intelligent linkage command module communicates with all units and realizes hierarchical early warning, fire simulation, force dispatch and closed-loop management of the whole process based on GIS three-dimensional map.

[0021] The watchtower's dual-spectrum intelligent unit is equipped with a visible light + infrared thermal imaging dual-spectrum gimbal camera that can rotate 360° continuously. A single unit can cover a radius of 5 to 8 km and can identify open flames and high-temperature smoldering fires as small as 0.1 m². The edge end has a built-in AI recognition chip that analyzes the images in real time, with an accuracy rate of ≥98% and a false alarm rate of ≤2%.

[0022] The ground-based low-power sensor node unit integrates infrared flame, smoke, temperature and humidity, wind speed and direction sensors. It adopts a sleep-wake low-power mode, with a sleep current ≤20μA, a detection radius of 50m, and uses LoRa communication. It is powered by solar energy and batteries and has a service life of ≥5 years.

[0023] The tethered aerial monitoring platform unit is powered and communicated via tethered cables, with an altitude of 200–500m. It is equipped with multispectral cameras and thermal imagers, and a single unit can cover an area of ​​≥30km², enabling large-scale continuous monitoring.

[0024] The front-mounted intelligent fire extinguishing bomb launcher is equipped with multiple ultra-fine dry powder fire extinguishing bombs, and features an infrared fire tracking and automatic aiming gimbal with a range of 100-200m. It automatically launches within 30 seconds of receiving a fire signal. The high-pressure fine water mist isolation unit is deployed in the firebreak and automatically activates to form a water curtain to block the fire when it approaches.

[0025] Mesh self-organizing network units automatically relay around mountain obstructions, achieving seamless communication in forest areas; Beidou short message units serve as backup communication in public network blind spots, ensuring reliable transmission of early warning information; solar energy storage units are equipped with lithium iron phosphate batteries, enabling normal operation for more than 15 days during continuous cloudy and rainy days.

[0026] The fire AI intelligent identification and positioning module adopts a lightweight improved YOLOv8 model, with a single frame recognition time of ≤50ms at the edge. It can distinguish between three types of fires: open flame, smoldering, and smoke. After cross-positioning by multiple devices, the fire point positioning accuracy is ≤5m, and it can automatically calculate the fire spread trend.

[0027] The graded early automatic treatment unit is equipped with a three-level triggering mechanism: Level 1 warning: Automatically dispatch gimbals and drones for close-range verification; Level 2 warning: Triggers the automatic response of the pre-positioned fire extinguishing device and simultaneously notifies the forest ranger; Level 3 warning: Activate the fine water mist isolation device, dispatch drones to drop bombs, and coordinate with professional fire-fighting teams.

[0028] The intelligent linkage command module includes a GIS 3D command unit, a hierarchical early warning unit, a fire simulation unit, and a force dispatch unit. After a fire occurs, it automatically generates a firefighting plan, issues early warnings through multiple channels, and achieves closed-loop management throughout the entire process.

[0029] System Deployment Plan Ground sensor nodes: 300 low-power ground sensor nodes are deployed in key areas under the forest, one every 500m. They integrate infrared flame, smoke, temperature and humidity sensors, use LoRa communication, and are equipped with 10 LoRa gateways. The nodes are powered by solar energy and batteries, and have a standby life of 5 years.

[0030] Watchtower Terminals: One dual-spectrum intelligent monitoring terminal is deployed at each of the five highest mountain peaks, with a single unit covering a radius of 6km, forming overlapping coverage and eliminating monitoring blind spots; the terminals are equipped with edge AI chips, enabling local real-time identification of fire conditions and uploading abnormal images to the command center.

[0031] Tethered Aerial Platform: One tethered aerial monitoring platform 13 will be deployed in the central area of ​​the forest farm, with a hovering height of 300m and a coverage area of ​​35km², to serve as a large-scale supplementary monitoring platform, with a focus on monitoring the core forest area.

[0032] Drone swarm: Deploy 2 drone take-off and landing points, and configure 4 inspection drones and 2 fire-fighting drones. They will automatically conduct 2 inspections per day and take off within 5 minutes after a fire is triggered.

[0033] Pre-emptive response equipment: Pre-emptive intelligent fire extinguishing projectile launchers 31 are deployed in 8 key areas, including the surrounding villages, oil depots, and ancient tree clusters. Each launcher is equipped with 12 ultra-fine dry powder fire extinguishing projectiles with a range of 150m and automatic aiming and launching. Six sets of high-pressure fine water mist isolation devices 32 are deployed in the main firebreaks.

[0034] Power supply and communication: All field equipment is equipped with solar energy storage modules 41 to meet the power supply requirements for 15 consecutive days of cloudy and rainy days; 25 Mesh self-organizing network nodes 42 are deployed to form a communication network covering the entire forest area, and the command center is equipped with a Beidou short message terminal 43 as a backup.

[0035] Command Platform: The forest fire prevention command center is equipped with an intelligent linkage command platform 5, featuring an 85-inch GIS screen to display real-time monitoring data and equipment status for the entire forest area.

[0036] Fire response simulation test A 0.5㎡ initial open flame was simulated at the edge of the forest area to test the system's full-process response: Detection and identification: The dual-spectrum terminal of the lookout tower, 2.3km away from the fire, first captured the infrared high-temperature point. The edge AI identified it as an open flame with a confidence level of 96.8%. At the same time, the ground sensor node detected smoke and temperature anomalies, confirming the fire situation twice. The system automatically located the latitude and longitude of the fire point with a positioning error of 3.2m.

[0037] Early warning and verification: The system triggers a level 2 early warning, and an alarm pops up on the command platform's large screen, simultaneously pushing information to the forest ranger's APP; at the same time, the nearest drone is dispatched to fly to the fire point for close verification, and the drone arrives 3 minutes and 20 seconds later, transmitting high-definition images to confirm the fire situation.

[0038] Early automatic response: The nearest forward-deployed fire extinguishing device was 120m from the fire point. After receiving the alarm, the device automatically rotated its gimbal to aim at the fire point and fired two fire extinguishing bombs 28 seconds later, successfully covering the fire point and extinguishing the open flames; the drone continued to monitor and confirm that there was no reignition.

[0039] Follow-up actions: Forest rangers arrived at the scene 8 minutes later, cleared the remaining fire, and the system recorded all data and generated a fire response report.

[0040] Operational performance statistics The system operated continuously for 6 months, during which it successfully monitored and handled 3 initial fires, all of which were extinguished within 10 minutes, without causing large-scale damage. Fire detection accuracy: 98.7%, with 3 false alarms (all of which were villagers burning stubble, which were marked by AI as agricultural fires and triggered manual verification). Average fire point positioning accuracy: 4.1m; Average response time: 7 minutes and 40 seconds; Equipment online rate: 99.2%, operating normally for 12 consecutive days of cloudy and rainy weather; Communication reliability: Mesh network coverage is 100%, and BeiDou backup communication remains normal even in extreme weather conditions.

[0041] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart forest fire monitoring and early response system for mountainous areas, characterized in that, It includes a multi-source three-dimensional monitoring module for air, land, and space; an AI-powered intelligent fire identification and positioning module; a graded early automatic response module; a mountain-adaptive power supply and communication module; and an intelligent linkage command module. The multi-source three-dimensional monitoring module adopts a four-level three-dimensional architecture, including a ground-based low-power sensing unit deployed under the forest, a dual-spectrum intelligent unit deployed at a commanding height, a tethered floating monitoring platform unit at medium and low altitudes, and a drone inspection cluster unit, to achieve all-time and full-coverage fire monitoring. The fire AI intelligent identification and positioning unit adopts an edge + cloud two-level computing architecture, with a built-in multispectral fusion fire identification algorithm. It combines visible light, infrared thermal imaging, and smoke characteristics to make a comprehensive judgment, eliminates environmental interference, and combines GIS three-dimensional terrain to achieve accurate fire point positioning. The graded early automatic response module adopts a three-level architecture of pre-positioned fixed-point response + UAV mobile response + isolation zone protection, including a pre-positioned intelligent fire extinguishing projectile launching unit, a high-pressure fine water mist isolation unit and a UAV fire extinguishing delivery unit, which automatically activates the corresponding level of response measures after receiving the alarm. The mountain-adaptive power supply and communication module includes a solar energy storage unit, a Mesh self-organizing network unit, and a Beidou short message unit, enabling self-sufficiency in power supply and seamless communication coverage in remote mountainous and forested areas. The intelligent linkage command module communicates with all units and realizes hierarchical early warning, fire simulation, force dispatch and closed-loop management of the whole process based on GIS three-dimensional map.

2. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The watchtower's dual-spectrum intelligent unit is equipped with a visible light + infrared thermal imaging dual-spectrum gimbal camera that can rotate 360° continuously. A single unit can cover a radius of 5 to 8 km and can identify open flames and high-temperature smoldering fires as small as 0.1 m². The edge end has a built-in AI recognition chip that analyzes the images in real time, with an accuracy rate of ≥98% and a false alarm rate of ≤2%.

3. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The ground-based low-power sensor node unit integrates infrared flame, smoke, temperature and humidity, wind speed and direction sensors. It adopts a sleep-wake-up low-power mode, with a sleep current ≤20μA, a detection radius of 50m, LoRa communication, and a solar + battery power supply lifespan ≥5 years.

4. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The tethered buoyant monitoring platform unit is powered and communicated via tethered cables, with an altitude of 200–500m. It is equipped with a multispectral camera and a thermal imager, and a single unit can cover an area of ​​≥30km², enabling large-scale continuous monitoring.

5. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The front-mounted intelligent fire extinguishing projectile launching unit is equipped with multiple ultra-fine dry powder fire extinguishing projectiles, and has its own infrared fire point tracking and automatic aiming gimbal. It has a range of 100-200m and automatically launches within 30 seconds after receiving a fire signal. The high-pressure fine water mist isolation unit is deployed in the firebreak and automatically activates to form a water curtain to block the fire when the fire approaches.

6. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 5, characterized in that, The Mesh self-organizing network unit automatically relays around mountain obstructions, achieving seamless communication in forest areas; the Beidou short message unit serves as backup communication in public network blind spots, ensuring reliable transmission of early warning information; the solar energy storage unit is equipped with lithium iron phosphate batteries, which can operate normally for more than 15 days in continuous cloudy and rainy weather.

7. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The fire AI intelligent identification and positioning module adopts a lightweight improved YOLOv8 model, with a single frame recognition time of ≤50ms at the edge. It can distinguish between three types of fires: open flame, smoldering, and smoke. After cross-positioning by multiple devices, the fire point positioning accuracy is ≤5m, and it can automatically calculate the fire spread trend.

8. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The graded early automatic handling unit is equipped with a three-level triggering mechanism: Level 1 warning: Automatically dispatch gimbals and drones for close-range verification; Level 2 warning: Triggers the automatic response of the pre-positioned fire extinguishing device and simultaneously notifies the forest ranger; Level 3 warning: Activate the fine water mist isolation device, dispatch drones to drop bombs, and coordinate with professional fire-fighting teams.

9. The intelligent forest fire monitoring and early response system for mountainous areas according to claim 1, characterized in that, The intelligent linkage command module includes a GIS 3D command unit, a hierarchical early warning unit, a fire simulation unit, and a force dispatch unit. After a fire occurs, it automatically generates a firefighting plan, issues early warnings through multiple channels, and achieves closed-loop management throughout the entire process.

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