Research library

MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees

www.nature.com/scientificdata MSPB: a longitudinal multi-sensor Data Descriptor dataset with phenotypic trait measurements from honey bees OPEN Yi Zhu 1 ✉, Mahsa Abdollahi1, Ségolène Maucourt2, Nico Coallier Pierre Giovenazzo2 & Tiago H. Guimarães1, We present a one-year-long multi-sensor dataset collected from honey bee colonies (Apis mellifera) with rich phenotypic measurements. Data were collected non-stop from April 2020 to April 2021 from 53 hives located at two apiaries in Québec, Canada. The sensor data included audio features, temperature, and relative humidity.

Publication details

Authors
Yi Zhu
Organizations
🇨🇦 Institut National de la Recherche Scientifique🇨🇦 Université Laval🇨🇦 Nectar Technologies Inc.
Year
2024
Type
Journal

Relevancy to Gratheon

This paper is relevant to Gratheon because it informs sensor hardware, telemetry pipelines, and monitoring dashboards, audio-acoustic monitoring models for remote hive status detection, dataset design, benchmarking, and model validation workflows. 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.