Low voltage user power internet of things monitoring system based on LoRa wireless technology
Abstract The operational efficiency of the current smart grid system is seriously affected by the stability of the operating system, and Internet of Things technology has good applicability in power grid information perception. This study uses LoRa technology to construct a monitoring system for the...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Energy Informatics |
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| Online Access: | https://doi.org/10.1186/s42162-025-00472-1 |
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| author | Xiao Wang Wei Zhao Xixian Niu |
| author_facet | Xiao Wang Wei Zhao Xixian Niu |
| author_sort | Xiao Wang |
| collection | DOAJ |
| description | Abstract The operational efficiency of the current smart grid system is seriously affected by the stability of the operating system, and Internet of Things technology has good applicability in power grid information perception. This study uses LoRa technology to construct a monitoring system for the electric energy Internet of Things. Additionally, an optimization model based on a particle swarm optimization algorithm and backpropagation neural network for optimizing base station positioning and channel quality evaluation is proposed. In addition, a multi-channel adaptive frequency hopping technology has been developed. The experimental results showed that the adaptive frequency hopping technology of the system could complete frequency switching within 2 min, which was more efficient than the traditional sampling and statistical technology that took 4 min. In terms of coverage, the research method had a coverage radius of 25 km, which was superior to other communication technologies such as NB IoT and ZigBee. In terms of data transmission success rate, the research method achieved 98.11%, significantly higher than Sigfox’s 90.02%. In addition, the system had a latency of only 150ms and low power consumption. In summary, the PSO-BP LoRa model proposed in the study has high application value in smart grids and industrial environments, providing technical support for wide-area, low-power, and high-stability Internet of Things monitoring systems. |
| format | Article |
| id | doaj-art-b1adb259d3c24f81ba6b5713c2191b36 |
| institution | Kabale University |
| issn | 2520-8942 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj-art-b1adb259d3c24f81ba6b5713c2191b362025-02-02T12:44:41ZengSpringerOpenEnergy Informatics2520-89422025-01-018111910.1186/s42162-025-00472-1Low voltage user power internet of things monitoring system based on LoRa wireless technologyXiao Wang0Wei Zhao1Xixian Niu2Xuchang Vocational Technical CollegeShijiazhuang Information Engineering Vocational CollegeHebei Youth Administrative Cadres CollegeAbstract The operational efficiency of the current smart grid system is seriously affected by the stability of the operating system, and Internet of Things technology has good applicability in power grid information perception. This study uses LoRa technology to construct a monitoring system for the electric energy Internet of Things. Additionally, an optimization model based on a particle swarm optimization algorithm and backpropagation neural network for optimizing base station positioning and channel quality evaluation is proposed. In addition, a multi-channel adaptive frequency hopping technology has been developed. The experimental results showed that the adaptive frequency hopping technology of the system could complete frequency switching within 2 min, which was more efficient than the traditional sampling and statistical technology that took 4 min. In terms of coverage, the research method had a coverage radius of 25 km, which was superior to other communication technologies such as NB IoT and ZigBee. In terms of data transmission success rate, the research method achieved 98.11%, significantly higher than Sigfox’s 90.02%. In addition, the system had a latency of only 150ms and low power consumption. In summary, the PSO-BP LoRa model proposed in the study has high application value in smart grids and industrial environments, providing technical support for wide-area, low-power, and high-stability Internet of Things monitoring systems.https://doi.org/10.1186/s42162-025-00472-1BP neural networkInternet of thingsLoRaPSO algorithm |
| spellingShingle | Xiao Wang Wei Zhao Xixian Niu Low voltage user power internet of things monitoring system based on LoRa wireless technology Energy Informatics BP neural network Internet of things LoRa PSO algorithm |
| title | Low voltage user power internet of things monitoring system based on LoRa wireless technology |
| title_full | Low voltage user power internet of things monitoring system based on LoRa wireless technology |
| title_fullStr | Low voltage user power internet of things monitoring system based on LoRa wireless technology |
| title_full_unstemmed | Low voltage user power internet of things monitoring system based on LoRa wireless technology |
| title_short | Low voltage user power internet of things monitoring system based on LoRa wireless technology |
| title_sort | low voltage user power internet of things monitoring system based on lora wireless technology |
| topic | BP neural network Internet of things LoRa PSO algorithm |
| url | https://doi.org/10.1186/s42162-025-00472-1 |
| work_keys_str_mv | AT xiaowang lowvoltageuserpowerinternetofthingsmonitoringsystembasedonlorawirelesstechnology AT weizhao lowvoltageuserpowerinternetofthingsmonitoringsystembasedonlorawirelesstechnology AT xixianniu lowvoltageuserpowerinternetofthingsmonitoringsystembasedonlorawirelesstechnology |