An innovative solution for forest fire monitoring is proposed, leveraging a wireless sensor network (WSN) based on ESP32 nodes equipped with cameras, BME680 gas sensors, and carbon monoxide (CO) sensors. The main objective of this system is to extend the operational lifespan of the sensor nodes by optimizing their energy consumption while maintaining a high level of reliability in fire detection. This approach is critical in large-scale monitoring applications where energy efficiency and node durability play a key role. The sensor network is composed of four primary nodes strategically placed on elevated points, designed with dual wireless communication technologies. For long-range communication, LoRa is utilized to connect these nodes, which are several kilometers apart. Meanwhile, NRF communication is used for short-range interactions, allowing each node to communicate with others within its local area of coverage. This hybrid communication architecture offers the advantage of covering large forested areas while reducing energy usage, as it selectively employs the most efficient communication protocol based on the node’s distance from its peers. An experimental case study was conducted in the Mechrouha forest, located in Souk-Ahras, in northeastern Algeria, to validate the efficiency of this setup. The chosen test area is prone to wildfires, making it an ideal real-world scenario for the implementation of such a system. This context allowed us to propose a sensor network topology consisting of four groups of basic sensor nodes, each covering a surface area of one square kilometer, with each group controlled by a sink node installed on a mountaintop.The sensor nodes can operate in several modes, each having distinct energy consumption characteristics: Data acquisition: capturing images and/or collecting climate data (temperature, humidity, gas levels), Data processing: performing local computations on the acquired data, Data transmission and reception: sending and receiving information between nodes or to a central base station, Sleep mode: reducing power consumption when the node is not actively processing or transmitting data.Given these varied modes of operation, the energy consumption differs significantly across the modes, and it was crucial to accurately measure the power usage in each scenario. To achieve this, an experimental setup was designed consisting of the sensor node (ESP32 with camera, BME680 gas sensor, and CO sensor), connected to a digital oscilloscope and a precision milliammeter. A precision resistor was placed between the power supply and the sensor node to convert the current drawn by the node into a measurable voltage, which could then be visualized on the oscilloscope. This setup enabled precise real-time measurement of the energy consumption during various node activities.
Boutiouta et al. (Fri,) studied this question.