EchoLogger: embedded system for calculating acoustic richness index in non-invasive environmental monitoring

• Pedro Lucas Bezerra Mendes UFAM
• Rodolfo Stoll UNRC
• Juan G. Colonna UFAM

DOI: https://doi.org/10.5753/sbcup.2025.9242

Abstract

This article presents the EchoLogger, a low-cost embedded system for environmental bioacoustic monitoring. Based on the ESP32, the device captures and processes audio in real time, calculating the Acoustic Richness Index (AR) to estimate sound diversity. The methodology includes a comparison of EchoLogger’s calculations with the scikit-maad library and a field test to assess the feasibility of embedded processing. The results indicate high accuracy in the median and entropy calculations, with an MAE of 0.0429 for the median and 0.0776 for the entropy, demonstrating that real-time processing does not compromise data quality. The study confirms the efficiency and accessibility of EchoLogger for environmental monitoring, highlighting its potential in biodiversity and conservation.

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