Affiliation:
1. Dig Connectivity Research Laboratory (DCRLab), Kampala, Uganda & School of Digital Science, Universiti Brunei Darussalam, Brunei
Abstract
The main goal is to appropriately utilize advanced algorithms to analyze environmental data, improve early disease detection and intervention tactics, and reduce the harmful effects of forest fires on human beings. Analyze the challenges faced by traditional methods in addressing the constantly evolving nature of wildfires and the need for more adaptable and proactive approaches, and highlight the advantages of AI. Discusses the main constituents incorporated into the AI model, comprising meteorological data, satellite imagery, and historical fire records. It analyzes the selection of AI algorithms specifically tailored for forest fire prevention, considering parameters. Analyze the challenges faced during the creation and implementation of AI models for forest fire prevention and viability of integrating artificial intelligence models into existing fire management infrastructure and emergency response systems. It showcases the current research, progress, and use of AI-driven solutions to address the challenges posed by wildfires and provides a concise overview of the chapter's findings.
Cited by
2 articles.
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1. Sustainable Development;Advances in Hospitality, Tourism, and the Services Industry;2024-07-26
2. Environmental Conservation and Sustainable Development;Advances in Computer and Electrical Engineering;2024-07-12