Multi-Sensor Measurement and Data Fusion
Zheng Liu, Xiao George, Huan Liu, Hanbing Wei
Abstract
There is a growing demand for a reliable and comprehensive measurement of critical quantities in modern industry. As any individual sensor or measurement does not reflect the overall properties of the object, the use of multiple sensors becomes essential. The industrial Internet of Things finds a diverse range of applications. Accordingly, the ability to handle multi-sensor measurement data is very important. Data fusion, also known as information fusion, can produce more consistent, accurate, and reliable information by integrating the data from multiple sources. Instead of achieving only low-level outputs, data fusion facilitates the information flow from raw data to high-level understanding and insights, which serve as the evidence for industry decision-making. This paper presents a big picture of multi-sensor measurement and data fusion.