A. Reyana^1,*, P. Vijayalakshmi²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1013-1025, 2023, DOI:10.32604/iasc.2023.032538 - 29 September 2022

Abstract Destructive wildfires are becoming an annual event, similar to climate change, resulting in catastrophes that wreak havoc on both humans and the environment. The result, however, is disastrous, causing irreversible damage to the ecosystem. The location of the incident and the hotspot can sometimes have an impact on early fire detection systems. With the advancement of intelligent sensor-based control technologies, the multi-sensor data fusion technique integrates data from multiple sensor nodes. The primary objective to avoid wildfire is to identify the exact location of wildfire occurrence, allowing fire units to respond as soon as possible. More >

T. Ghisu¹, B. Arca², G. Pellizzaro², P. Duce²

CMES-Computer Modeling in Engineering & Sciences, Vol.102, No.1, pp. 83-102, 2014, DOI:10.3970/cmes.2014.102.083

Abstract Level-set approaches are efficient and versatile methods for solving interface tracking problems and have been used in recent years to describe wildland fire propagation. Being based on an Eulerian description of the spread problem, their numerical implementation offers improved computational agility and better portability to parallel computing environments with respect to vector-based simulators. The use of a continuous representation of the fire perimeter in place of the binary formulation used in Cellular Automata avoids the commonly observed distortion of the fire shape. This work presents an algorithm for fire-spread simulation based on a level-set formulation. More >