Forest Fire Rescue Research Articles

Improved Particle Swarm Path Planning Algorithm with Multi-Factor Coupling in Forest Fire Spread Scenarios

In this paper, a solution based on an improved particle swarm algorithm is proposed for the path planning problem without a road network in forest fire rescue scenarios. The algorithm adopts an adaptive inertia weight and a dynamically updated learning factor strategy to enhance the global and local search capabilities of the algorithm. In terms of cost function design, the article considers three factors: path length, terrain slope, and obstacle avoidance ability to ensure the safety and effectiveness of the path. The experimental results show that: (1) the path planning algorithm based on improved particle swarm optimization can effectively avoid spreading wildfire and reach the designated target point with a good “detour” effect; (2) the path planned by the improved PSO algorithm performs better than the original PSO algorithm in terms of fitness evaluation and average slope; and (3) changes in the particle population, dimensions, and learning factors in the particle swarm optimization algorithm can affect the convergence of the final path. Increasing the particle dimensions can bring more reasonable and specific paths; decreasing the learning factor increases the convergence iterations, but also obtains a better path planning solution and higher fitness.

Firefighting multi strategy marine predators algorithm for the early-stage Forest fire rescue problem

Firefighting multi strategy marine predators algorithm for the early-stage Forest fire rescue problem

Modification of Freezing Point for Hydrogel Extinguishant and Its Effect on Comprehensive Properties in Simulated Forest Fire Rescue

Hydrogels, as an emerging extinguishant, exhibit outstanding performance in forest fire rescues. However, the near-zero freezing point limits their application at low temperatures. Herein, a sensible candidate commercial extinguishant was selected for analysis, and its freezing point was modified based on the evaluation of water absorption rate, agglomeration, viscosity, and water dispersibility. Notably, the introduction of different antifreeze and flame retardant exhibited a significant disparate impact on the viscosity representative factor. Ten orthogonal experiments were performed to optimize the specific formulation. When ethylene glycol, urea and ammonium bicarbonate, and xanthan gum were applied as antifreeze, flame retardant, and thickener, with the addition amounts of 5 mL, 0.08 g and 0.04 g, and 0.12 g, respectively, the hydrogel extinguishant with 1% ratio in 50 mL of ultra-water featured the remarkable performance. Compared with the original extinguishant, the freezing point of the modified sample decreased from −0.3 to −9.2 °C. The sample’s viscosity was improved from 541 to 1938 cP, and the flame retardance time was more than 120 s. The results of corrosion and biotoxicity show that the optimized hydrogel extinguishant satisfies the national standards. This understanding provides a deeper insight into the application of low-temperature extinguishants in forest fires.

Research on Forest Fire Rescue Path Planning Based on Improved A* Algorithm

Forest fires are known as one of the eight natural disasters in the world. They are sudden and destructive, have a profound impact on the living environment of human beings, and cause serious damage to the atmosphere. Therefore, once a forest fire occurs, how to plan the path in the first time so that the firefighters can climb the distance from the nearby highway to the location of the fire is of practical and urgent significance. Based on the introduction of innovative NDVI and slope weight factors, this paper normalizes and superimposes the relevant factors by improving the A* path planning algorithm, and obtains an optimized pathfinding algorithm. Experiments show that the planning of forest fire rescue paths is highly feasible.

A forest fire rescue strategy based on variable extinguishing rate

In mathematics, forest fires are mainly described by the fire spread model. The model analyzes the tree-to-tree (T2T) spread of the fire, providing the optimal solution for rescuers. This paper aims to develop a forest fire rescue strategy based on variable extinguishing rate (VER). Firstly, a dynamic model was established for the T2T propagation of forest fire. Then, the classic forest fire rescue strategy was improved to adapt to the changing extinguishing rate of trees. Finally, the improved strategy was proved correct and rational through simulation. Our forest fire rescue strategy can adjust dynamically to the tree state and rescue rate. The best rescue rate of forest fire was obtained in the equilibrium state of fire propagation. The research results help to minimize the damage and rescue cost of forest fire.

Ensemble framework by using nature inspired algorithms for the early-stage forest fire rescue — A case study of dynamic optimization problems

In this paper, we propose rescue ensemble to simulate the dynamic rescue process between forest fire spread and forest fire rescue, while simultaneously formulating this process as a dynamic optimization problem. However, there is still little research about simulating this kind of the dynamic rescue process, even when many new unmanned monitoring systems and large-scale firefighting aircraft emerge in the forest-fire-rescue field. Our rescue ensemble that consists of rescue simulator and rescue algorithm is characterized by supporting the offline simulation of the dynamic rescue process between forest fire spread (like offensive forces) and forest fire rescue (like defensive forces). Based on modifying the cellular automaton model of forest fire spread, rescue simulator is able to simulate forest fire spread and aircraft firefighting, simultaneously. Besides, the main goal of rescue algorithm is to realize the aircraft task allocation. Firefighting particle swarm optimization is proposed by us as our rescue algorithm, which is characterized by considering fire edge suppression, the burning-cell continuity, and wind direction. We construct our test problems based on real forest maps and aircraft firefighting capability. Comparing with four compared rescue algorithms, we test the different capabilities of firefighting particle swarm optimization, such as searching dynamic optimal solution, shortening the rescue time, controlling the spread speed of fire edge, and minimizing the burned cost. Experimental results demonstrate that the framework of rescue ensemble is feasible. Meanwhile, the results of firefighting particle swarm optimization are satisfactory in most cases.

Mission Planning for Multiple Vehicles with Temporal Specifications using UxAS

In this paper, we present extensions to Unmanned Systems Autonomy Services (UxAS) to handle mission specifications that require a synchronization of task execution. UxAS uses Process Algebra (PA) as a formal language to specify mission requirements for unmanned aerial vehicle (UAV) operations. However, the current implementation of PA in UxAS utilizes assigned semantics which does not guarantee the order of task completion and is unable to provide a mission planning required vehicle-synchronization. To enable the capability of UxAS in operating synchronized mission specifications, we introduce a notion of Synchronized Process Algebra (SPA) which extends PA by adding a synchronized composition operator to the syntax of PA. Such an operator allows us to specify the task’s duration and enforce the next task is executed after the previous one has terminated. Moreover, we provide a new service in UxAS, called Temporal Service (TS) to control the flow of the planning process with respect to timing specifications. We apply SPA and TS to specify and operate the mission specification of a forest fire rescue scenario required the synchronized arrivals of multiple UAVs.

Dual Aircrafts Path Planning for Forest-Fire Rescue by Artificial Immune Algorithm

Path planning for dual aircrafts is preceded by artificial immune algorithm in forest fire rescue. We analysis and compare several parameters which will influence path planning. Based on above results we sum the reasonable parameters which should be used in further experiment. Moreover, to improve the operability of aircraft, restrictions of gradient smoothing algorithm, curvature smoothing algorithm are performed to smooth track in vertical aspect. Experimental results show that we can successfully get the satisfied flight paths for dual aircrafts in fire rescue under complex circumvent. At the same time the paths we planned have certain practical value by consideration the aircrafts fly-ability constraints.