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Advancing Artificial Intelligence for Wildfire Prediction and Control: New Edges in Environmental Safety and Fire Ecology
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Author(s): Tarun Kumar Kaushik (Sharda University, India), Ravish (Meerut College, India), Anurag Singh (Meerut College, India), Anjali Raghav (Sharda University, India), Bhupinder Singh (Sharda University, India)and Kittisak Wongmahesak (Shinawatra University, Thailand)
Copyright: 2025
Pages: 24
Source title:
Machine Learning and Internet of Things in Fire Ecology
Source Author(s)/Editor(s): Christian Kaunert (Dublin City University, Ireland), Rishabha Malviya (Galgotias University, India), Bhupinder Singh (Sharda University, India), Sahil Lal (School of Law, Sharda University, Greater Noida, India)and Manmeet Kaur Arora (Sharda University, India)
DOI: 10.4018/979-8-3693-7565-5.ch002
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Abstract
The advancements in data science, along with the advancements in digital and satellite technologies, have increased the capabilities for using artificial intelligence (AI) in the fields of forestry and wildlife. However, the rapid expansion of construction projects, agricultural activities, and urban regions presents a substantial risk to biodiversity worldwide. Therefore, using cutting-edge technology like artificial intelligence (AI) in the domains of forests and biodiversity might enhance the effective monitoring, management, and conservation of biodiversity and forest resources. This chapter aims to provide a thorough overview of the global use of AI and machine learning (ML) algorithms in the forestry sector and biodiversity protection. Moreover, this study investigates the challenges faced during the use of AI technology in the domains of forestry and biodiversity. The results of this study would motivate forest officials, scientists, researchers, and conservationists to explore the possibilities of using AI technology for forest management and biodiversity protection.
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