RETRACTED ARTICLE: Fault location measurement of sensor nodes based on fuzzy control algorithm
The sensor nodes are devices with extra capabilities of sensing, communicating and processing of the recorded data. The sensor-based wireless and IoT-enabled networks can contribute a precarious part of army command, defense control, defense communications, computerized based intelligence and survei...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Jg. 27; H. 2; S. 1189 - 1199 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.01.2023
Springer Nature B.V |
| Schlagworte: | |
| ISSN: | 1432-7643, 1433-7479 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | The sensor nodes are devices with extra capabilities of sensing, communicating and processing of the recorded data. The sensor-based wireless and IoT-enabled networks can contribute a precarious part of army command, defense control, defense communications, computerized based intelligence and surveillance, and above all the targeting systems. Examples of defense applications include monitoring of own army forces and enemy forces; monitoring of ammunition, monitoring of equipment, targeting at certain regions; and nuclear as well as biotechnology-based attack detection. With the advent of AI and latest technologies, a technical paradigm shift can be seen in monitoring the faults in sensor nodes that are capable to collect the data and entire decisions are inferred on the basis of this data. By deploying sensors in critical areas, all the movements can be followed in detail. Hence, instant fault location measurement of sensor nodes with the least complex approaches is the need of the hour. Therefore, a novel soft computing-based approach is proposed in this paper for measuring the fault in locations of sensor-based networks using fuzzy logic and neural networks with high accuracy. The proposed technique allows lower consumption of energy while locating the faults. The results demonstrate the superior performance of the proposed fault location scheme with respect to the network node loss, measurement error, and measurement time taken for detecting faults in locations of sensor nodes. The proposed fuzzy and neural network-based method outperforms the existing benchmarked techniques considered for comparative study. |
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| Bibliographie: | ObjectType-Correction/Retraction-1 SourceType-Scholarly Journals-1 content type line 14 |
| ISSN: | 1432-7643 1433-7479 |
| DOI: | 10.1007/s00500-021-06145-x |