Emily Bick | Searcharxiv

arXiv2026

BickGraphing: Web-Based Application for Visual Inspection of Audio Recordings

BickGraphing is a browser based research tool that enables visual inspection of acoustic recordings. The tool was built in support of visualizing crop feeding pest sounds in support of the Insect Eavesdropper project; however, it is widely applicable to all audiovisualizations in research. It allows multiple uploads of large .wav files, computes waveforms and spectrograms locally, and supports interactive exploration of audio events in time and frequency. The application is implemented as a SvelteKit and TypeScript web app with a client side signal processing pipeline using WebAssembly compiled FFmpeg and custom FFT utilities. The software is released on an open Git repository (https://github.com/bicklabuw/BickGraphing) and archived under a standard MIT license and can be reused for rapid visual quality checks of .wav recordings in insect bioacoustics and related fields. BickGraphing has the potential to be a local, easy to use coding free visualization platform for audio data in research.

eess.AS↗

arXiv2021

Automating insect monitoring using unsupervised near-infrared sensors

Insect monitoring is critical to improve our understanding and ability to preserve and restore biodiversity, sustainably produce crops, and reduce vectors of human and livestock disease. However, conventional monitoring methods of trapping and identification are time consuming and thus expensive. Here, we present a network of distributed wireless sensors, recording backscattered near-infrared modulation signatures from insects. The instrument is a compact sensor based on dual-wavelength infrared light emitting diodes and is capable of unsupervised, autonomous long-term insect monitoring over weather and seasons. The sensor records the backscattered light at kHz pace from each insect transiting the measurement volume. Insect observations are automatically extracted and transmitted with environmental metadata over cellular connection to a cloud-based database. The recorded features include wing beat harmonics, melanisation and flight direction. To validate the sensor's capabilities, we tested the correlation between daily insect counts from an oil seed rape field measured with six yellow water traps and six sensors during a 4-week period. A comparison of the methods found a Spearman's rank correlation coefficient of 0.61 and a p-value of 0.0065, with the sensors recording approximately 19 times more insect observations and demonstrating a larger temporal dynamic than conventional trapping.

physics.ins-det↗