Collaborative web platform for recording, annotating, and visualizing bat echolocation signals

Abstract

Monitoring bat echolocation using ultrasound microphones is essential in ecological studies due to its non-invasive nature and wide spatial-temporal coverage. However, the large volume of data and high temporal resolution of the signals pose challenges in terms of management, storage, visualization, and annotation for scientific analysis. These tasks are limited by the dispersion of information across multiple storage media and dependence on proprietary software, which hinders collaborative work and increases research costs. This work presents the design and development of a web platform for high-resolution spectral visualization and collaborative taxonomic annotation of ultrasonic echolocation signals. A software engineering approach was adopted, implementing a decoupled architecture using Django REST Framework in the backend for robust data management and Next.js in the frontend to ensure a responsive user interface, integrating the Web Audio API and rendering with HTML5 Canvas, allowing high-resolution digital signal processing directly in the browser without loss of quality. As a result, a functional prototype was developed for the online visualization of echolocation signal spectrograms, enabling the recording of taxonomic and behavioral information, automatic signal processing and the extraction of spectral features, facilitating collaborative work in bat bioacoustics.