Data aggregation

Data aggregation refers to the process of collecting, combining, and systematically analyzing information from various sources. In building automation, it enables the central analysis of sensor data, providing precise insights into the condition and usage of a building. By intelligently combining such data, communication and control processes can be optimized to reduce energy consumption, enhance operational safety, and improve user comfort.

Technologically, data aggregation is achieved through interconnected smart building components like sensors and actuators. These IoT devices continuously collect information on parameters such as temperature, air quality, lighting, or occupancy and transmit it to central monitoring units via technologies like Bluetooth Low Energy (BLE). Self-healing mesh networks ensure stable and reliable data transmission. The aggregated signals are analyzed on central platforms to enable automated decisions and adjustments in real time.

The applications of data aggregation are diverse: In office buildings, automated systems use occupancy and motion data to switch off unused rooms, allocate workspaces flexibly, and adjust lighting to match needs. In industrial and logistics buildings, aggregation helps control storage conditions—like temperature or humidity—to create optimal environments for the safe storage of sensitive goods. In facility management, aggregated data enables the early detection of anomalies, precise planning of maintenance activities, and sustainable resource management.

Additionally, data aggregation through IoT technologies lays the foundation for detailed analysis and forecasting. Combining real-time measurements with historical data allows informed decisions that both lower operating costs and support sustainable building concepts. Cloud-based platforms offer businesses the advantage of accessing building data anytime and from anywhere, enabling continuous process optimization.

The aggregation of sensor data is an essential foundation for the efficient management of interconnected systems. The structured analysis of real-time and historical data helps businesses boost operational efficiency, reduce energy consumption, and create pleasant living and working environments.