Interaction between machines is crucial in the digital changeover, and smart machines depend on smart sensors to observe conditions and surroundings. Miniaturization and increased computing power enable small and low-cost sensors to perform demanding signal processing, and to interact with other sensors and data sources to provide a good description of what they are observing. Sensors in networks (sensor fusion) increase both data quality and reliability, allowing for high density distributed monitoring and machine learning.
Wireless sensors are more easily mounted in existing production environments and in areas without any infrastructure. The installation cost is therefore far less compared to traditional measurement methods. Efficient signal processing and data transfer give a battery lifetime of many years, and adaptive measurement algorithms can provide high performance when needed and still maintain low average power consumption.