IOT based Novel speedy Detection of Forest fire using Sensors with improved accuracy by sensing Temperature and Atmospheric Carbon Dioxide Level using Node Microcontroller Unit in comparison with Arduino Microcontroller
{"title":"IOT based Novel speedy Detection of Forest fire using Sensors with improved accuracy by sensing Temperature and Atmospheric Carbon Dioxide Level using Node Microcontroller Unit in comparison with Arduino Microcontroller","authors":"P. R. Reddy, P. Kalyanasundaram, V. Suresh","doi":"10.1109/MACS56771.2022.10022408","DOIUrl":null,"url":null,"abstract":"The main objective of this research is to detect the forest fire by sensing temperature and atmospheric carbon dioxide (CO2) levels to prevent the forest fire and to provide exact information using IOT at faster speed. The efficiency of detection using Node Microcontroller Unit (NodeMCU) is compared with Arduino microcontroller. A total of 40 samples are taken from the Serial monitor of the Arduino IDE. Group 1 has temperature values (n = 10) and atmospheric carbon dioxide (CO2) levels (n = 10) with the Node Microcontroller Unit (Node MCU). Group 2 has temperature values (n = 10) and atmospheric carbon dioxide (CO2) levels (n = 10) using Arduino Microcontroller. In this novel forest fire detection, the G-power analysis was done to the samples and the minimum power is acquired to be 0.8 for the system with an error correction of 0.5. The significance values for the temperature sensor are 0.129 and 0.132 for NodeMCU and Arduino Microcontroller respectively. The significance values for atmospheric carbon dioxide (CO2) levels are 0.212 and 0.224 for NodeMCU and Arduino Microcontroller respectively. Results: Through the implementation of this novel forest fire detection, it is observed that the efficiency of NodeMCU is 92.9 % and efficiency of Arduino microcontroller is 89.95 %. This innovative approach with NodeMCU appears to be more efficient (92.9 %) in detecting the occurrence of forest fire using Arduino Microcontroller with the significance value of temperature and atmospheric carbon dioxide level of 0.129 and 0.212 respectively.","PeriodicalId":177110,"journal":{"name":"2022 14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 14th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACS56771.2022.10022408","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The main objective of this research is to detect the forest fire by sensing temperature and atmospheric carbon dioxide (CO2) levels to prevent the forest fire and to provide exact information using IOT at faster speed. The efficiency of detection using Node Microcontroller Unit (NodeMCU) is compared with Arduino microcontroller. A total of 40 samples are taken from the Serial monitor of the Arduino IDE. Group 1 has temperature values (n = 10) and atmospheric carbon dioxide (CO2) levels (n = 10) with the Node Microcontroller Unit (Node MCU). Group 2 has temperature values (n = 10) and atmospheric carbon dioxide (CO2) levels (n = 10) using Arduino Microcontroller. In this novel forest fire detection, the G-power analysis was done to the samples and the minimum power is acquired to be 0.8 for the system with an error correction of 0.5. The significance values for the temperature sensor are 0.129 and 0.132 for NodeMCU and Arduino Microcontroller respectively. The significance values for atmospheric carbon dioxide (CO2) levels are 0.212 and 0.224 for NodeMCU and Arduino Microcontroller respectively. Results: Through the implementation of this novel forest fire detection, it is observed that the efficiency of NodeMCU is 92.9 % and efficiency of Arduino microcontroller is 89.95 %. This innovative approach with NodeMCU appears to be more efficient (92.9 %) in detecting the occurrence of forest fire using Arduino Microcontroller with the significance value of temperature and atmospheric carbon dioxide level of 0.129 and 0.212 respectively.