Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers
This paper addresses the difficulty of balancing a real-time response and low power consumption in intelligent manhole cover application scenarios. It proposes a method to distinguish normal and abnormal events by segmenting the boundary at which the acceleration of the intelligent manhole cover dev...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-04-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/12/8/1926 |
| _version_ | 1797605627057405952 |
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| author | Jiahu Guo Kai Wang Jianquan Sun Youcheng Jia |
| author_facet | Jiahu Guo Kai Wang Jianquan Sun Youcheng Jia |
| author_sort | Jiahu Guo |
| collection | DOAJ |
| description | This paper addresses the difficulty of balancing a real-time response and low power consumption in intelligent manhole cover application scenarios. It proposes a method to distinguish normal and abnormal events by segmenting the boundary at which the acceleration of the intelligent manhole cover deviates from a set threshold and lasts for a certain period, based on the difference in the intelligent manhole cover’s vibration patterns when a normal event and an abnormal event occur. This paper uses the autonomous data fusion of digital output motion sensor data to implement a pattern recognition algorithm for the above-mentioned pattern, which reduces the MCU computing and working time and the overall power consumption of the system while meeting real-time response requirements. The test results demonstrate that the method has a high rate of anomaly recognition accuracy. The method ensures the system’s real-time response capability, and the actual low power consumption test demonstrates that the device can operate continuously for 9.5 years. The low power consumption index exceeds the requirements of the existing national standard, thereby resolving the issue that it is challenging to balance intelligent manhole cover abnormality recognition and low power consumption. |
| first_indexed | 2024-03-11T05:03:45Z |
| format | Article |
| id | doaj.art-1cc6dd1ed92d4dc1a4355da7be528108 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T05:03:45Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-1cc6dd1ed92d4dc1a4355da7be5281082023-11-17T19:02:51ZengMDPI AGElectronics2079-92922023-04-01128192610.3390/electronics12081926Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole CoversJiahu Guo0Kai Wang1Jianquan Sun2Youcheng Jia3School of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, ChinaSchool of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, ChinaHuanzhong District Power Supply Branch, State Grid Xining Power Supply Company, Xining 810001, ChinaHuanzhong District Power Supply Branch, State Grid Xining Power Supply Company, Xining 810001, ChinaThis paper addresses the difficulty of balancing a real-time response and low power consumption in intelligent manhole cover application scenarios. It proposes a method to distinguish normal and abnormal events by segmenting the boundary at which the acceleration of the intelligent manhole cover deviates from a set threshold and lasts for a certain period, based on the difference in the intelligent manhole cover’s vibration patterns when a normal event and an abnormal event occur. This paper uses the autonomous data fusion of digital output motion sensor data to implement a pattern recognition algorithm for the above-mentioned pattern, which reduces the MCU computing and working time and the overall power consumption of the system while meeting real-time response requirements. The test results demonstrate that the method has a high rate of anomaly recognition accuracy. The method ensures the system’s real-time response capability, and the actual low power consumption test demonstrates that the device can operate continuously for 9.5 years. The low power consumption index exceeds the requirements of the existing national standard, thereby resolving the issue that it is challenging to balance intelligent manhole cover abnormality recognition and low power consumption.https://www.mdpi.com/2079-9292/12/8/1926low power consumptionInternet of Thingsintelligent manhole coverattitude solving |
| spellingShingle | Jiahu Guo Kai Wang Jianquan Sun Youcheng Jia Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers Electronics low power consumption Internet of Things intelligent manhole cover attitude solving |
| title | Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers |
| title_full | Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers |
| title_fullStr | Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers |
| title_full_unstemmed | Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers |
| title_short | Research and Implementation of Low-Power Anomaly Recognition Method for Intelligent Manhole Covers |
| title_sort | research and implementation of low power anomaly recognition method for intelligent manhole covers |
| topic | low power consumption Internet of Things intelligent manhole cover attitude solving |
| url | https://www.mdpi.com/2079-9292/12/8/1926 |
| work_keys_str_mv | AT jiahuguo researchandimplementationoflowpoweranomalyrecognitionmethodforintelligentmanholecovers AT kaiwang researchandimplementationoflowpoweranomalyrecognitionmethodforintelligentmanholecovers AT jianquansun researchandimplementationoflowpoweranomalyrecognitionmethodforintelligentmanholecovers AT youchengjia researchandimplementationoflowpoweranomalyrecognitionmethodforintelligentmanholecovers |