Forest fire prediction using IoT and deep learning
J. Ananthi, N. Sengottaiyan, S. Anbukaruppusamy, Kamal Upreti, Animesh Kumar Dubey, A Faroudja, N Izeboudjen, V Zope, T Dadlani, A Matai, P Tembhurnikar, R Kalani, R Sinde, S Kaijage, K Njau, A Latifah, A Shabrina, I Wahyuni, R Sadikin, B Singh, N Kumar, P Tiwari, A Majhi, S Dash, C Barik, R Bhadoria, M Pandey, P Kundu, X Yang, S Xiong, H Li, X He, H Ai, Q Liu, A Labellapansa, N Syafitri, E Kadir, R Saian, A Rahman, M Ahmad, B Kalantar, N Ueda, M Idrees, S Janizadeh, K Ahmadi, F Shabani, A Tiwari, M Shoab, A Dixit, H Lin, X Liu, X Wang, Y Liu, H Zhu, D Gao, S Zhang, M Tehrany, S Jones, F Shabani, F Martnez-Alvarez, B Tien, G Zhang, M Wang, K Liu, M Mohajane, R Costache, F Karimi, Q Pham, A Essahlaoui, H Nguyen, D Wood, K Singh, K Neethu, K Madhurekaa, A Harita, P Mohan, N Baranovskiy, A Podorovskiy, A Malinin, T Preeti, S Kanakaraddi, A Beelagi, S Malagi, A Sudi, R Vikram, D Sinha, D De, A Das, J Zhang, H Zhu, P Wang, X Ling, L Si, L Shu, M Wang, F Zhao, F Chen, Li
Abstract
Forests are valuable concerns for human existence as well as societal progress because they help maintain the universe's entire ecosystem stability [1-3]. Unfortunately, forest fire scenarios occur regularly as a result of certain unregulated human activity and erratic environmental circumstances Such fires are by far the most destructive to environmental assets as well as the human ecology In this situation, forest fire scenarios have significantly increased in regularity as a result of global warming, mortal activity and certain other things