Affiliation:
1. Handan Polytechnic College Handan China
Abstract
AbstractWith the rapid development of Internet of Things (IoT) technology, the number of sensors in IoT and the data collected from them are increasing. If these data are not managed and stored directly, it will occupy a large amount of storage space. Therefore, studying the data management mechanism of multi‐sensor fusion in IoT is of great significance. Multi‐sensor fusion has achieved a series of successes in the field of data management. Based on this, this article proposes a secure and controllable data management mechanism for multi‐sensor fusion in IoT, including a multi‐sensor fusion model, compression of data using linear regression algorithm, and data storage based on sorted string table algorithm. Then this article analyzes the effectiveness of the model proposed for multi‐sensor fusion data management. Through comparative experiments under different data sets, it is verified that the management mechanism has higher data fusion rate, lower data lossy compression rate and higher data lossless compression rate under different data sets. And it has high data storage security, large reconstruction probability, strong management controllability, and can significantly save storage space. It is a superior secure and controllable data management mechanism for multi‐sensor fusion in IoT.
Subject
Artificial Intelligence,Computer Networks and Communications,Information Systems,Software
Reference7 articles.
1. An overview of internet of things and its benefits[J];Lei J;Journal of Information Technology & Software Engineering,2021
2. An intelligent incentive mechanism for coverage of data collection in cognitive internet of things[J];Liu Y;Future Gener Comput Syst,2019
3. Achieving performability and reliability of data storage in the internet of things[J];Taheri N;Int J Eng Manuf(IJEM),2022
4. A method for stochastic optimization[C];Kinga D;Int Conf Learn Representations (ICLR),2015
5. Linear regression combined KNN algorithm to identify latent defects for imbalance data of ICs[J];Huang L;Microelectron J,2023
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