Time-series dataset of honey bee colony dynamics before, during, and after sunflower pollination

Abstract Objectives Precision beekeeping is an integral part of precision agriculture, which relies on sensor technologies and high-quality datasets to quantify and optimize ecosystem services such as crop pollination. To support reproducible research and the planning and evaluation of crop pollination campaigns in precision beekeeping, we release a time-series dataset that characterizes colony dynamics before, during, and after pollination, using sunflower as a case study. Data description We release synchronized, non-invasive time series from nine smart hives ( Apis mellifera ) monitored in Ukraine (Europe/Kyiv) from 01 May to 31 Aug 2024, including a sunflower pollination service window (07–23 Jul 2024) and a documented attractant intervention. Sensors record hive weight, in-hive and ambient temperature, in-hive and ambient relative humidity, and device signals (processor temperature and stabilized solar voltage). The repository includes raw telemetry exports, cleaned hourly series aligned to a fixed local time grid, and a beekeeper event log, together with reproducible scripts and a documented processing protocol.