Novel Detection of Forest Fire using Temperature and Carbon Dioxide Sensors with Improved Accuracy in Comparison between two Different Zones

Abstract

Aim: This detailed research involves in improving the performance accuracy of forest fire detection in comparison between evergreen forest zone and temperate forest zone by sensing temperature and atmospheric carbon dioxide level. Materials and Method: In this analysis, Group 1 consists of temperature values (n = 16) and atmospheric carbon dioxide concentration levels (n = 16) in an evergreen forest zone. Group 2 consists of temperature values (n = 16) and atmospheric carbon dioxide concentration level (n = 16) after incidence of fire. This novel Fire detection method, the G-power analysis was done on the samples with maximum power of 0.8 for the system with an error correction of 0.5. Results: The proposed novel forest fire detection has a better accuracy in evergreen forest (93.3 %) in comparison with temperate forest (90.8 %). The significance value is observed to be 0.198 using temperature sensors and 0.219 using carbon dioxide sensors. Conclusion: The novel forest fire detection system using temperature and carbon dioxide sensors, appears to have better accuracy of 93.3 % to locate the existence of forest fire in evergreen forest.