Modern beekeeping is stressful for our bees. As a beekeeper, the bee colony must be inspected regularly. This involves opening and inspecting the hive. The bees perceive this process as an attack. Even hours later, you can see that the bees are still confused. Our experience in beekeeping and embedded systems has led us to the following project idea.
Our goal is to reduce interventions in the hive. The idea is to use sensors and data to determine when and where intervention is necessary. Within the framework of this project, we want to conduct basic research into suitable sensor types, the various sensor models, and the processing and presentation of the collected data in the context of goal achievement.
The central point for data collection, storage, and processing is a Raspberry Pi. This is suitable for connecting a wide variety of sensors. In the first phase, the focus is on the data acquisition infrastructure in order to evaluate the incoming data based on its quality. Building on this, we will conduct a test run in the next phase. We will test an empty hive with the sensors. In the next phase, we install the resulting prototypes in a beehive and collect data. At the same time, we use our beekeeping expertise to conduct manual inspections as a control and compare them. We use the insights gained from these inspections to evaluate the design of our prototypes.
Our project explores various aspects of data literacy. The focus is on data collection using sensors, data storage on the Raspberry Pi, processing and visualization using software we developed ourselves, and the analysis and evaluation of data quality.