Paper
11 October 2023 Research on multi-source heterogeneous sensory data fusion methods for user feedback
Zhengxiong Mao, Tao Chuan, Jing Zhou, Wenwei Su, Yingjun He, Donghui Mei, Chenglin Li
Author Affiliations +
Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 1280003 (2023) https://doi.org/10.1117/12.3004586
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China
Abstract
The current multi-source heterogeneous sensory data fusion lacks the application of user feedback, resulting in low user satisfaction of the data fusion results. In this regard, a multi-source heterogeneous perceptual data fusion method for user feedback is proposed. A multi-source heterogeneous perceptual data storage model is built to complete the acquisition and storage of data. Uniform semantic annotation of the stored data. Obtain user relevance feedback. Based on the feedback information, the dynamic feedback fusion of multi-source heterogeneous perceptual data is completed. The experiments show that the average user satisfaction of the method is 0.9534, which is a significant improvement and has high practical application value.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhengxiong Mao, Tao Chuan, Jing Zhou, Wenwei Su, Yingjun He, Donghui Mei, and Chenglin Li "Research on multi-source heterogeneous sensory data fusion methods for user feedback", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 1280003 (11 October 2023); https://doi.org/10.1117/12.3004586
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KEYWORDS
Data fusion

Data modeling

Data storage

Sensors

Data acquisition

Classification systems

Design and modelling

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