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Total control over beehives or automatization processesWith stunning dashboards, insightful data analysis and live streams of the cameras, the bee colony can be monitored around the…
Using data for bee-friendly farmingHow swarm intelligence and decentral networking can make farming more sustainable.
Process optimization through ARUsing augmented reality for projecting a virtual hive or industrial processes.
Digital twinning is a key to mastering processesBy creating a digital twin all aspects of merely any process can be accessed, monitored, and controlled … easily and…
AI assisted object detection to optimize quality controlFrom detecting moving objects to documenting and analyzing their patterns in an automated environment.
The challenges for an IoT data infrastructure are manifold. Processing large amounts of data, even in different data formats and communication protocols, requires a scalable and flexible data infrastructure. Data from different sources must be collected and integrated into a unified system. This may also require a distributed data infrastructure to process and analyze data at the edge of the network.
Overall, the data infrastructure at the IT/OT interface is a critical component of modern industrial systems, enabling companies to collect, analyze and process data from a variety of sources to optimize operations, reduce costs and increase efficiency. The data infrastructure is also of great importance in a smart beehive. As part of a joint project, several project groups have set themselves the goal of jointly setting up such a structure. The entire process is being considered – from the storage of sensor data in the cloud, data analysis via a virtual twin to data visualization via a software app.