On the occasion of the upcoming high forest fire risk campaign, the SenForFire project of the Interreg Sudoe programme has participated in experimental tests to evaluate sensor-based early fire detection technologies. These tests were carried out on 7 May in the industrial estate of Vicolozano (Ávila), in the framework of the collaboration with the European project TREEADS (‘Improving forest management with a focus on protection and regeneration’, H2020, 2021-2025), promoted by the Diputación de Ávila.
During the day, four controlled burns of different types of agricultural and forestry fuels were carried out: straw, thick branches of holm oak, pellets and thin branches of pruning waste. The duration of the burns ranged between 10 and 30 minutes, allowing the performance of the sensor modules developed in SenForFire to be evaluated under real conditions.
Before the burns, the project partners -ITEFI-CSIC, University of Extremadura (UEx), RAY Ingeniería Electrónica (RAY IE) and ARANTEC- deployed the sensors on the plot to monitor in real time key variables such as weather conditions, flue gas concentration, volatile organic compounds (VOCs) and particulate matter (PM). Simultaneously, the INIA-CSIC team took samples of the fuels and determined their moisture content by gravimetric analysis in the laboratory.
Preliminary results indicate that the orientation of the sensors with respect to the wind direction is crucial to optimise the early detection of an incipient fire outbreak. Under optimal alignment conditions, the particulate matter and VOC sensors showed the best results, depending on the predominant combustion type: higher smoke emission (as in straw) or prominent flame presence (as in oak wood).
Another relevant finding was the consistency in measurements obtained between different types of wind sensors, ranging from high-precision ultrasonic sensors used in professional weather stations, to low-cost conventional mechanical sensors (anemometer and wind vane) and very low-cost MEMS electronic micro-sensors. These results support the possibility of SenForFire developing a small, lightweight and energy-efficient weather station, designed to be installed in many locations simultaneously as part of smart networks of internet-connected sensors (IoT).
The ultimate goal is to generate wind maps with high spatial and temporal resolution, essential for early detection and proactive management of fire risk in vulnerable areas. These tests represent a significant advance in the development of accessible, efficient and scalable technologies for the protection of the natural environment.
