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

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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.

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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.

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The mid-Cretaceous period was one of the warmest intervals of the past 140millionyears1-5, driven by atmospheric carbon dioxide levels of around 1,000parts per million by volume6. In the near absence of proximal geological records from south of the Antarctic Circle, it is disputed whether polar ice could exist under such environmental conditions. Here we use a sedimentary sequence recovered from the West Antarctic shelf-the southernmost Cretaceous record reported so far-and show that a temperate lowland rainforest environment existed at a palaeolatitude of about 82°S during the Turonian-Santonian age (92 to 83millionyearsago). This record contains an intact 3-metre-long network of in situ fossil roots embedded in a mudstone matrix containing diverse pollen and spores. A climate model simulation shows that the reconstructed temperate climate at this high latitude requires a combination of both atmospheric carbon dioxide concentrations of 1,120-1,680parts per million by volume and a vegetated land surface without major Antarctic glaciation, highlighting the important cooling effect exerted by ice albedo under high levels of atmospheric carbon dioxide.

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Rising atmospheric carbon dioxide may alter plant/herbivore interactions. The projected rise in atmospheric carbon dioxide is expected to increase plant productivity, but little evidence is available regarding effects on insect feeding or growth. Leaves of soybean plants grown under three carbon dioxide regimes (350, 500, and 650 µl/liter)were fed to soybean looper larvae. Larvae fed at increasingly higher rates on plants from elevated carbon dioxide atmospheres: 80% greater rates on leaves from the 650 µl/liter treatment than on leaves from the 350 µl/liter treatment. Variation in larval feeding was related to the leaf content of nitrogen and water and to the leaf-specific weight. each of which was altered by the carbon dioxide growth regime of the soybean plants. This study suggests that the impact of herbivores may increase as the level of atmospheric carbon dioxide rises.

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