This work involves the development and implementation of an Internet of Things (IoT) system for the early detection of forest fires. This initiative addresses the pressing need for effective and precise tools to prevent and combat forest fires, which pose significant threats to natural ecosystems, biodiversity, and human communities. This work has achieved a notable improvement in forest fire detection efficiency, significantly reducing the response time needed to implement preventive or containment measures. An integrated system has been developed and deployed, incorporating IoT sensors inside an ESP32 microcontroller, a communication network, LoraWan Network, webpage, and a real-time monitoring platform, enabling continuous oversight of remote forested areas. The prototype has demonstrated high accuracy in detecting events related to forest fires, minimizing both false positives and false negatives, thus providing a solid foundation for informed decision-making. Furthermore, the system has been designed to operate reliably in challenging forest environments, withstanding extreme weather conditions to ensure operational continuity. Special attention has been given to the sustainability of the system in terms of energy efficiency and environmental impact, ensuring that its implementation contributes positively to environmental conservation.