Relevancy to Gratheon
This paper is relevant to Gratheon because it informs camera-based hive-scanner and computer-vision models, sensor hardware, telemetry pipelines, and monitoring dashboards, edge-AI deployment, power budgeting, and offline operation. 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.