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7 articles for “wildfire detection”
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Wildfire Detection and Tracking System
Abstract: To create a precise forecast of the wildfire, it is crucial to possess the capability to recognize it and anticipate how it will distribute. The devastation of vegetation, the loss of assets, the rise in greenhouse gases, the extinction of Numerous animal species and even human fatalities can all result from wildfires. To trim back this danger, there must be a mechanism capable of detecting a fire the moment it …
Published in International Journal on Drones · Vol. 2, Issue 2, 2026 · pp. 21–29 Read article
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Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Leveraging IoT for Real-Time Disaster Management: Enhancing Preparedness and Response Through Smart Monitoring
Abstract: Natural disasters, including floods, earthquakes, and wildfires, pose risks to human life, infrastructure, and the environment. Many of the technological innovations are there, but in managing such disasters, there still is room for inefficiencies resulting from communication delay, unavailability of real-time data, and poor coordination at times. The inefficiencies lead to response times that are too long, inappropriate allocation of resources, and increased vulnerability to the impacts of disasters. Integration …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 11–17 Read article
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Forest Fire Detection System
Abstract: The IOT industry is rapidly growing in the current scenario. Each one of us now understands the significance of Internet of Things. At present, it is being used in almost all industries making our lives a bit easier. Forest fires have become a massive threat across the globe, causing numerous negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are among the consequences of such …
Published in Journal of VLSI Design Tools and Technology · Vol. 13, Issue 1, 2023 · pp. 1–5 Read article
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Forest Fire Early Detection and Online Remote Monitoring Using Sensors
Abstract: Forest fire device networks represent a strong technology, particularly appropriate for environmental observation. With relation to wildfires, above all, they permit low-priced police work of venturesome locations like wild land urban interfaces. This report presents the work developed throughout the last 4 years targeting a fire device network node for the reliable, on-site detection of forest fires. The tasks dispensed ranged from detective work or sensing of conditions that rise …
Published in Journal of Industrial Safety Engineering · Vol. 9, Issue 1, 2022 · pp. 16–20 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article