What is RFCx Arbimon?
RFCx Arbimon is a free web interface for biologists, ecologists and citizen scientists to work with audio data collected from the field using an AudioMoth, Swift, SongMeter, RFCx Guardian or any other recording device. The Arbimon web app was designed for ecologists and biologists needing to conduct sophisticated scientific analyses on large volumes of audio data collected from the field. Arbimon is a sophisticated and highly flexible analytical tool which is able to slice and dice audio data in countless variations in order to answer specific research questions. This data can then be exported and analyzed further using advanced statistical analyses tools.
From there, biologists and ecologists can formulate conclusions which can guide publications of scientific papers and/or inform conservation practices. In order to accomplish this, the Arbimon platform offers the following features to perform several kinds of analyses: Pattern Matching (object recognition using a cross correlation analysis to identify presence of similar patterns in other audio files), Soundscape Analysis, Random Forest Model (RFM) analysis (which uses AI), and a host of other features. Arbimon is now being used by scientists to support conservation/biodiversity projects all over the world. Check out our Arbimon articles to learn how to get set up and conduct analysis in Arbimon.
Major functions and analysis tools in Arbimon include:
- Visualizing audio
- Creating audio playlists
- Analyzing audio with Pattern Matching (PM)
- Analyzing audio with Soundscapes
- Random Forest Model (RFM)
- Convolutional Neural Network (CNN) Models
Note: Currently the ability to analyze audio using CNN models is only available to the Rainforest Connection Science Team.
The screenshot above shows a soundscape analysis covering 24 hours of recordings. Soundscape analyses are used to observe various frequencies and intensities of acoustic activity in an ecosystem.