Research & Evidence
HiveSense is built on published bee science. This page lists the peer-reviewed studies, citizen-science datasets, and primary sources that inform our sensor parsers, varroa thresholds, and AI monitoring models.
- Colony health
Honey bee colony loss and management practices in the United States
Bee Informed PartnershipAnnual U.S. national survey of beekeepers tracking colony losses and management practices. A primary source for varroa-driven mortality data.
Open source - Varroa management
Standard methods for varroa research
COLOSS / Journal of Apicultural ResearchThe COLOSS BEEBOOK chapters define the agreed-upon protocols for measuring varroa infestation (alcohol wash, sticky board, sugar shake) — the basis for HiveSense's varroa tracker thresholds.
Open source - BLE sensing
Continuous remote monitoring of honey bee colonies using temperature, humidity, and weight sensors
MDPI SensorsOpen-access peer-reviewed studies on the signal-to-noise tradeoffs of in-hive sensor placement and which metrics predict queen failure, swarming, and honey flows.
Open source - Colony health
Honey bee health and stressors
Nature / Scientific ReportsNature's open-access journal indexes hundreds of peer-reviewed papers on colony stressors, pesticide exposure, and pathology — foundational reading for any data-driven beekeeping app.
Open source - BLE sensing
BroodMinder open data and methodology
BroodMinder.comThe manufacturer's research portal publishes the raw BLE packet format and reference datasets used by HiveSense to decode T2, TH, and W sensors.
Open source - AI monitoring
OpenAI Whisper — speech recognition model
OpenAI researchThe on-device speech-to-text model HiveSense uses for voice inspection notes. The published paper documents word-error-rate benchmarks across noise conditions including outdoor recordings.
Open source
Build on the science
Try the offline-first beekeeping app that's grounded in peer-reviewed methods.
Browse all features