Abstract

Forest fire is a matter of concern as it affects our ecological cycle and incurs a huge economical loss. There are various sensor-based systems built to detect fire at an early stage but the maintenance and covering the huge area is not feasible. Deep learning-based systems are also developed for fire detection however early detection, real time processing and monitoring of the region of interest is a major problem. To overcome these issues a remote sensing and deep learning-based forest fire detection system is proposed. The main objective is to monitor the forest and detect fire at an early stage. Remote sensing is used for versatile data collection which is used for training the model. ‐‐‐‐ based model is used to detect fire with ‐‐accuracy.

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