EFFSIP: Efficient forest fire system using IoT and parallel computing

The escalating issue of forest fires poses severe risks to ecosystems and human habitats, primarily due to the greenhouse effect and sudden climate changes. These fires, mostly occurring naturally, necessitate prompt detection and control. Addressing this, the paper introduces the Efficient Forest Fire System using an innovative Internet of Things (IoT) and Parallel computing (EFFSIP) solution. The EFFSIP system leverages a wireless sensor network to efficiently detect and analyze fire behavior, providing real-time data on fire spread, speed, and direction. The system processes environmental parameters such as temperature (T), relative humidity (RH), and the Chandler Burning Index (CBI) against set thresholds to enable early fire detection.

Designed for the challenging forest environment, the EFFSIP system prioritizes minimal power usage and simple components, crucial in areas with limited power resources. Its resilient design ensures that the wireless sensor network and sensor nodes withstand harsh weather and fire conditions, maintaining functionality and reliability. The system’s efficiency is enhanced through the use of Pthreads for parallel processing, allowing multiple tasks such as data collection, processing, and fire checking to be handled concurrently. This approach significantly reduces response time by processing sensor data in parallel, ensuring rapid detection and accurate prediction of fire behavior.

Field tests of the EFFSIP system in various Jordanian forest locations, including Burgish-Ajloun, demonstrated its effectiveness. The system detected a fire at 10:42 am with an initial CBI value of 32.5, which increased sharply to 97.92 as the fire progressed. Additionally, the system recorded a decrease in humidity from 53% to 22% and an increase in temperature from 28 °C to 48.6 °C. For example, the system predicted a fire at node 12 would occur in 0.477 min, allowing preemptive actions to be taken before the fire started. The system’s ability to provide real-time alerts and detailed analysis of fire spread, speed, and direction makes it a valuable tool for forest fire management. The strategic placement of sensor nodes and the use of durable components reduce the risk of system damage due to environmental extremities. The EFFSIP system offers a significant contribution to fighting forest fires, and future enhancements may include leveraging GPGPU (General-Purpose computing on Graphics Processing Units) technology to further increase computational power and system efficiency.