MonitoR package

Under development

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This package provides workflows in form of R Markdown templates & Shiny-Apps for processing monitoring data, for now mostly focusing on the analysis of long audio files obtained by deploying passive acoustic monitoring (PAM) devices. The package partly relies on NocMigR2. See details there.

To install the package, use pak:

if (!"pak" %in% installed.packages()) install.packages("pak")
pak::pak("mottensmann/MonitoR", dependencies = TRUE)

Load the package once installed:

library(MonitoR)

Shiny-App

Toggling the entire processing pipeline (formatting, classification, inspecting results) using a shiny app. The classification is performed using birdnetR:

birdnet_app(display = "external")

RMarkdown Templates

MonitoR provides RMarkdown templates to set-up post-processing and validation of audio data classified using BirdNET-Analyzer. Using RStudio these are accessible via File -> New File -> RMarkdown

birdnet

• 1. Preprocessing of audio data (renaming to datetime, removing unnecessary file prefixes)
• 2. Extracting results obtained by using a AI-based classifier with BirdNET-Analyzer
• 3. Archiving manually verified records to a xlsx-database

Not further developed. Easier implementation provided in form of the Shiny-App

nestcamera

• 1. Preprocessing of photos (renaming to datetime and resorting)