Research library

The Be-Hive Project - Counting Bee Traffic based on Deep Learning and Pose Estimation

Beekeeping is an important practice for ensuring the abundance of pollinators and for honey production. Traditionally, beekeepers inspect hives regularly to monitor their bees’ populations, but this method is invasive and can cause stress to the bees. It is also impractical, for beekeepers having hundreds or thousands of beehives. In recent decades, various attempts have been made to automate the monitoring of bee colonies using emerging technologies. These technologies include sensors that collect micro-climate parameters, photos, video and audio from inside the hives and the nearby environment, which are then analyzed using automatic or manual.

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Publication details

Organizations
🇨🇾 CYENS Centre of Excellence🇨🇾 Cyprus University of Technology🇳🇱 University of Twente
Year
2023
Type
Conference

Relevancy to Gratheon

This paper is relevant to Gratheon because it informs entrance and behavior analytics in the Gratheon web app, camera-based hive-scanner and computer-vision models. Its methods and findings can be translated into product requirements for reliable field deployments: what should be sensed, how signals should be interpreted, and which uncertainty or validation limits need to be surfaced to beekeepers. For Gratheon, the work is most useful as an evidence-backed design reference for connecting local hive observations with actionable recommendations in the web app while keeping hardware practical for remote apiaries.