Multi-sensor data fusion system based on Apache Storm
Yan Liu, Shuai Zhao, Cheng Bo · 2017
With the development of Internet of Things and multi-sensor data fusion technology, traditional off-line data processing methods have been unable to deal with massive data, which leads to a loss in timeliness of data. As more and more well-known companies start to focus on real-time big data applications, some computing frameworks have developed rapidly, in which Apache Storm is the most representative open-source, distributed one due to its high reliability and good processing mode. In this paper, a multi-sensor data fusion system that combines classical data fusion algorithms with Storm architecture is proposed, to achieve real-time streaming data processing. Data fusion process is split into functional modules according to the feature of Storm. Extensive experiment results show that these algorithms can achieve better performance of data fusion in a short delay.