Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network
The inherent energy constraints of sensor nodes render energy efficiency optimization a critical challenge in wireless sensor network deployments. This study presents an innovative acoustic source localization framework incorporating a two-level data aggregation technology, specifically designed to...
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MDPI AG
2025-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/7/2247 |
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| author | Yuwu Feng Guohua Hu Lei Hong |
| author_facet | Yuwu Feng Guohua Hu Lei Hong |
| author_sort | Yuwu Feng |
| collection | DOAJ |
| description | The inherent energy constraints of sensor nodes render energy efficiency optimization a critical challenge in wireless sensor network deployments. This study presents an innovative acoustic source localization framework incorporating a two-level data aggregation technology, specifically designed to minimize energy expenditure while prolonging network lifetime. A mixed noise model is proposed to describe the characteristics of abnormal noise in real environments. Subsequently, the novel two-level data aggregation technology is proposed. The first level is implemented at individual sensors, where a large number of similar measurements may be collected. The second level data aggregation technology is performed at the cluster head nodes to eliminate the data redundancy between different sensor nodes. After the novel two-level data aggregation, most of the redundant data are eliminated and a significant amount of energy is saved. Then, a nonlinear iterative weighted least squares algorithm is applied to complete the final acoustic source location estimation based on the real remaining sensor measurements. Finally, through extensive simulation experiments, it was verified that the two-level data aggregation technology reduced energy consumption by at least 51% and 43%, respectively, and that the RMSE is less than 0.96. |
| format | Article |
| id | doaj-art-d65da4087b1745b39520f9b0a9380ff3 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-d65da4087b1745b39520f9b0a9380ff32025-08-20T02:15:46ZengMDPI AGSensors1424-82202025-04-01257224710.3390/s25072247Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor NetworkYuwu Feng0Guohua Hu1Lei Hong2College of Advanced Manufacturing Engineering, Hefei University, Hefei 230000, ChinaCollege of Advanced Manufacturing Engineering, Hefei University, Hefei 230000, ChinaCollege of Advanced Manufacturing Engineering, Hefei University, Hefei 230000, ChinaThe inherent energy constraints of sensor nodes render energy efficiency optimization a critical challenge in wireless sensor network deployments. This study presents an innovative acoustic source localization framework incorporating a two-level data aggregation technology, specifically designed to minimize energy expenditure while prolonging network lifetime. A mixed noise model is proposed to describe the characteristics of abnormal noise in real environments. Subsequently, the novel two-level data aggregation technology is proposed. The first level is implemented at individual sensors, where a large number of similar measurements may be collected. The second level data aggregation technology is performed at the cluster head nodes to eliminate the data redundancy between different sensor nodes. After the novel two-level data aggregation, most of the redundant data are eliminated and a significant amount of energy is saved. Then, a nonlinear iterative weighted least squares algorithm is applied to complete the final acoustic source location estimation based on the real remaining sensor measurements. Finally, through extensive simulation experiments, it was verified that the two-level data aggregation technology reduced energy consumption by at least 51% and 43%, respectively, and that the RMSE is less than 0.96.https://www.mdpi.com/1424-8220/25/7/2247wireless sensor networkacoustic source localizationmixed noise modeldata redundancydata aggregationenergy consumption |
| spellingShingle | Yuwu Feng Guohua Hu Lei Hong Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network Sensors wireless sensor network acoustic source localization mixed noise model data redundancy data aggregation energy consumption |
| title | Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network |
| title_full | Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network |
| title_fullStr | Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network |
| title_full_unstemmed | Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network |
| title_short | Acoustic Source Localization Based on the Two-Level Data Aggregation Technology in a Wireless Sensor Network |
| title_sort | acoustic source localization based on the two level data aggregation technology in a wireless sensor network |
| topic | wireless sensor network acoustic source localization mixed noise model data redundancy data aggregation energy consumption |
| url | https://www.mdpi.com/1424-8220/25/7/2247 |
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