Code for processing Beebox development ata

Pollinators, particularly bumblebees, play a vital role in global food production, yet their populations face severe declines due to environmental disturbances and habitat loss. While conservation efforts have focused on food provision, the critical need for suitable nesting habitats has been largely overlooked. We present a novel artificial nestbox, the BeeBox, designed to support bumblebee nesting and enhance research, conservation, and public engagement. Developed using additive manufacturing (AM) principles, the BeeBox underwent iterative design improvements to optimize thermal insulation, humidity control, and durability. Field tests demonstrated that our design significantly improved internal environmental stability, colony health and longevity.
The modular design facilitates in-nest behavioural studies using high-resolution video recording, providing a robust tool for understanding the impacts of environmental stressors. Additionally, the BeeBox offers scalable, cost-effective co..., , , # Beebox processing code

[https://doi.org/10.5061/dryad.j6q573nqh](https://doi.org/10.5061/dryad.j6q573nqh)

## Description of the data and file structure

Python scripts for capture of video/audio data from BeeBox device. STL files for research use are available directly from the authors only by contacting them at: [[e-mail]](mailto:[e-mail]).

### Files and variables

#### File: video\_analysis.py

**Description:** script for digital processing of movement data. 

This Python script analyzes `.mp4` video files to quantify movement activity within a specified Region of Interest (ROI). It segments videos into 10-minute blocks, computes pixel-level differences between consecutive frames in the ROI, and saves statistical summaries to a CSV file.

## Features

* Extracts timestamps from filenames (format: `capture_YYYYMMDD_HHMMSS.mp4`)
* Processes videos in 10-minute (36,000 frame) segments
* Computes movement metrics:
* Average movement (pixel sum difference...,