Wildfire Detection Using Sound Spectrum Analysis Based on the Internet of Things

Abstract

Wildfire is a sudden and hazardous natural disaster. Currently, many schemes based on optical spectrum analysis have been proposed to detect wildfire, but obstacles in forest areas can decrease the efficiency of spectral monitoring, resulting in a wildfire detection system not being able to monitor the occurrence of wildfire promptly. In this paper, we propose a novel wildfire detection system using sound spectrum analysis based on the Internet of Things (IoT), which utilizes a wireless acoustic detection system to probe wildfire and distinguish the difference in the sound between the crown and the surface fire. We also designed a new power supply unit: tree-energy device, which utilizes the biological energy of the living trees to generate electricity. We implemented sound spectrum analysis on the data collected by sound sensors and then combined our classification algorithms. The results describe that the sound frequency of the crown fire is about 0–400 Hz, while the sound frequency of the surface fire ranges from 0 to 15,000 Hz. However, the accuracy of the classification method is affected by some factors, such as the distribution of sensors, the loss of energy in sound transmission, and the delay of data transmission. In the simulation experiments, the recognition rate of the method can reach about 70%.

IoT-based sound-level control for audio amplifiers: mosques as a case study

“…However, this is only valid for indoor distances and for one IoT at a time. Zhang et al [16] used an IoT platform to analyze the sound spectrum in forests to distinguish between crown and surface fires. Their work cannot be used to determine the distance of the fire.…”

A Framework for Agricultural Pest and Disease Monitoring Based on Internet-of-Things and Unmanned Aerial Vehicles

“…At present, the mainstream pest and disease monitoring technologies applied internationally can be divided into two categories: IoT technology and remote-sensing technology. The IoT technology has emerged as a significant promising technology [26,27], containing numerous inexpensive sensor nodes randomly scattered over the area of interest to collect information on entities of interest [27][28][29], have been used for wide-ranging applications in the fields of climate simulation monitoring [30], real-time video monitoring of pests and diseases [31], and real-time early warning systems for predicting the occurrence of pests and diseases [32]. For agroclimatic diseases (such as wheat powdery mildew), the establishment of climate models through data collected by small climatic instruments arranged in the field can markedly reduce the incidence of pests of crops [33].…”

Environmental Acoustics Modelling Techniques for Forest Monitoring

“…Detecting other illegal activities like hunting in forest or ecological reserves, by spotting gun shots, or human voices would be a useful application [6]- [9]. In recent times, solutions based on environmental sound recognition are applied in early wildfire detection [10].…”