Sensorintegration
Sensorintegration refers to the process of combining data from multiple sensors to create a coherent understanding of an environment or system. It is used to increase accuracy, reliability, and resilience in sensing applications across domains such as robotics, automotive systems, industrial automation, and smart infrastructures.
The practice entails data acquisition, synchronization, calibration, and fusion. Sensor data are often heterogeneous with different
Common fusion techniques range from low-level statistical fusion of raw measurements to mid-level feature fusion and
Applications include perception systems in autonomous vehicles, SLAM in robotics, condition monitoring in industry, and smart
Standards and interoperability efforts focus on data formats, timing conventions, and open interfaces. The field is