HiveMind

Urban beekeepers currently have no reliable way to monitor hive health remotely. Assessing a colony’s condition requires physically opening the hive; a process that is time-consuming, disruptive to the bees, and offers only a momentary snapshot rather than an ongoing picture of hive health. Existing commercial monitoring solutions are expensive, proprietary, and poorly suited to South African conditions, where load-shedding and inconsistent connectivity make continuous cloud-based monitoring unreliable. Sponsored by Walter Uys on behalf of The Warehouse Trust, this project set out to give urban beekeepers real-time, remote visibility into hive conditions without the cost and fragility of existing options.

HiveMind is a low-cost, open, IoT-based hive monitoring system built around this need. A non-invasive ESP32 sensor node collects hive metrics, including temperature, humidity, weight, sound, vibration, and light, directly from the hive. This data is relayed through a Raspberry Pi gateway running Home Assistant, which buffers readings locally to withstand load-shedding and intermittent connectivity, before syncing to a backend server. The backend structures incoming data around the open BEEP API standard, supporting future interoperability with the broader hive-monitoring research community, and evaluates each reading against beekeeper-configured thresholds to generate real-time alerts.

Beekeepers interact with the system through a web dashboard offering live and historical hive data, alert history, and hive management tools, with instant Telegram notifications ensuring critical alerts reach them wherever they are. The system also includes an AI-powered chat assistant for natural-language queries about hive status, and live weather integration to contextualise hive readings against current conditions.

Development has delivered a fully deployed sensor-to-dashboard pipeline, BEEP-compliant data handling, and secure authentication, with the system now operational and actively monitoring a live hive. HiveMind demonstrates that proactive, data-driven hive monitoring is achievable at low cost, even under unreliable power and connectivity.