<![CDATA[Forest fires are catastrophic events that pose serious threats to ecosystems, biodiversity, and human health. Conventional monitoring techniques are often limited in coverage and response time, making early detection difficult and ineffective. This study proposes the development of an advanced forest fire monitoring system utilizing unmanned aerial vehicles (drones) equipped with integrated microcontroller-based technology. The system consists of a master microcontroller installed on the drone and a slave microcontroller connected to various environmental sensors, including temperature, humidity, hazardous gas detection, and flame sensors. Sensor data is transmitted in real-time to a web server, enabling remote visualization and monitoring of potential fire occurrences. The research focuses on the design, integration, and implementation of the monitoring system, as well as the development of a user-friendly web interface for real-time data presentation. The expected outcomes of this study include improved accuracy in forest fire detection, enhanced data availability for environmental analysis, reduced operational costs, and a more responsive forest monitoring framework. This system is anticipated to serve as a reliable and scalable solution for early warning and disaster mitigation in forest fire management.]]>
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