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Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
Xue-Bo Jin1, Shuli Sun2, Hong Wei3
1School of Computer Information and Engineering, Beijing Technology and Business University, Beijing 100048, China. jinxuebo@btbu.edu.cn.
Sensors (Basel, Switzerland)
|April 12, 2018
Summary
Multi-sensor information fusion integrates diverse data for accurate object representation, enhancing insights beyond single sensors. This technique is crucial for improving productivity and driving innovation in emerging applications.
Area of Science:
- Sensor technology and data science.
- Information engineering and artificial intelligence.
Background:
- Information fusion combines data from multiple sensors for a more accurate understanding of real-world objects.
- It addresses challenges of data redundancy and varied acquisition times, improving data utility.
- The technique has been pivotal in sensor research since the 1970s.
Discussion:
- Data fusion offers significant advantages over single-sensor approaches, increasing information value.
- Applications in manufacturing and process control demonstrate fusion's potential for productivity gains via digitization.
- This special issue focuses on novel solutions for multi-sensor information fusion in new application domains.
Key Insights:
- Integrating data from multiple sensors yields superior, consistent, and accurate object representations.
- Strategic sensor data combination maximizes information profit compared to individual sensor outputs.
- Digitization through data fusion enhances operational efficiency and business value.
Outlook:
- Exploring innovative fusion techniques for emerging application areas is essential.
- Development and adoption of advanced multi-sensor fusion are key for future technological advancements.
- Continued research will drive the application of information fusion across diverse industries.
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