Design and mathematical modeling of a device for detecting and locating potentially dangerous sounds in the forest

Illegal logging poses a significant threat to European forests, with roughly 30 million cubic meters of wood—out of 400 million extracted annually—being harvested unlawfully. This paper presents a novel acoustic monitoring device designed to combat this issue through the rapid detection and precise localization of the sound sources associated with such activities, such as chainsaws or heavy machinery (i.e., potentially dangerous sounds). The core of our solution is a time-decimation Discrete Fourier Transform (DFT) algorithm. This algorithm serves a dual purpose: first, it performs real-time frequency analysis to identify the unique acoustic signature of logging equipment. Second, it enables geographic triangulation by analyzing the slight differences in a sound's arrival time at multiple, distributed listening posts. This allows the designed system to pinpoint the sound source's location with 
high accuracy [1]. 
Our design prioritizes both computational efficiency and system redundancy to ensure reliable operation in a remote forest environment. The DFT algorithm was selected for its favorable balance between processing complexity and performance. Furthermore, the device incorporates a backup power system to maintain functionality even under adverse weather conditions that could compromise primary power sources. Beyond its primary anti-logging function, the system's 
architecture is adaptable for broader ecological monitoring, such as tracking wildlife or studying forest soundscapes.