A Deep Learning-Based Embedded System for Pest Bird Sound Detection and Proximity Estimation

Abstract

Cultivating crops is vital for driving economies, and maintaining agricultural fields is crucial for sustaining food production. This initiative centers on addressing the issue of pest birds, specifically starlings, within vineyards. The proposed strategy employs sound signals to detect and distinguish starling birds within the vineyard environment. Through an analysis of audio inputs from the surroundings, the system can effectively recognize unique sound patterns associated with starling birds, utilizing deep learning techniques. Furthermore, this project incorporates ultrasonic sensors for distance estimation, enabling the calculation of the bird’s proximity from a fixed point within the vineyard. All of these detection and estimation processes are executed on a RP2040 microcontroller, specifically the Cortex-M0+ 133 MHz variant. Following the detection phase, an autonomous vehicle equipped with red diode lasers can be dispatched to the designated location to deter the pest birds and safeguard the vineyards from unwanted disruptions and crop losses.