Abstract
Forest is one of the essential pillars of the ecosystem. Moreover, it provides all the essentials required for our very own existence. However, forest fires have been a significant area of concern over the years. For this purpose, various devices have been used over the years. Internet of Things (IoT) has been a significant advancement in early detection and mitigation. IoT, along with various software, enables error-free data in real time. This paper has highlighted three significant advancements using IoT, enabling the early detection of a forest fire. Firstly, Convolution Neural Network (CNN) is used for forest fire detection. Another method utilises a series of sensor network paradigms to get real-time data for forest fires. The final method utilises an EP32 board along with sound, rain, DHT11, and PIR sensors for its swift and systematic reporting of forest fires.
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Singh, A.K., Rafeek, S.M., Harikrishnan, P.S., Wilson, I. (2023). Review of Study on Various Forest Fire Detection Techniques Using IoT and Sensor Networks. In: Siddiqui, N.A., Baxtiyarovich, A.S., Nandan, A., Mondal, P. (eds) Advances in Waste Management. AIR 2021. Lecture Notes in Civil Engineering, vol 301. Springer, Singapore. https://doi.org/10.1007/978-981-19-7506-6_3
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DOI: https://doi.org/10.1007/978-981-19-7506-6_3
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