Jiawei Zhang, Yonghao Xie, Mingze Yuan, Ming-Bao Li
{"title":"针对 WUSN 信号衰减特性的自调整参数模型","authors":"Jiawei Zhang, Yonghao Xie, Mingze Yuan, Ming-Bao Li","doi":"10.1139/cjss-2022-0105","DOIUrl":null,"url":null,"abstract":"Wireless Underground Sensor Network (WUSN) is gradually applied to smart agriculture for soil information collection and monitoring of crop growth environment. WUSN can avoid the inconvenience caused by tillage and other machine operation activities on farmland, and obtains multi-level and multi-dimensional parameters in the underground soil environment, which is crucial for soil moisture monitoring of crops. However, WUSN has no universally applicable transmission protocol standards in the field. Therefore, the research of different soil compositions on the placement of wireless sensor network nodes can provide scientific guidance to obtain soil moisture information of agricultural fields, it is important for the development of precision agriculture. In this paper, a low-power WUSN nodes was designed, based on modified Frisian transmission model and the complex refractive index Fresnel model, we proposed an adaptive optimization model, and also proposed an improved Genetic Algorithm, which is automatically adjust fusion parameter according to soil and distance factors, it made the prediction of signal attenuation under different soil components more accurately. We used the adaptive optimized model for signal prediction, comparing with the modified Friis prediction model and the complex refractive index Fresnel prediction model, the results shown that the proposed adaptive optimization model with automatic parameter is convenient to predict the signal attenuation, the adaptive optimization model made the prediction error stay really low. In order to compare with other sensors in the soil environment, the temperature of the distributed fiber optic temperature sensor was tested, which predicted by the adaptive model. The result shown that the adaptive model is more favorable to the prediction of signal attenuation in WUSN than distributed fiber optic temperature sensors.","PeriodicalId":9384,"journal":{"name":"Canadian Journal of Soil Science","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Self-adjusting Parametric Model for Attenuation Characteristics of WUSN Signal\",\"authors\":\"Jiawei Zhang, Yonghao Xie, Mingze Yuan, Ming-Bao Li\",\"doi\":\"10.1139/cjss-2022-0105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless Underground Sensor Network (WUSN) is gradually applied to smart agriculture for soil information collection and monitoring of crop growth environment. WUSN can avoid the inconvenience caused by tillage and other machine operation activities on farmland, and obtains multi-level and multi-dimensional parameters in the underground soil environment, which is crucial for soil moisture monitoring of crops. However, WUSN has no universally applicable transmission protocol standards in the field. Therefore, the research of different soil compositions on the placement of wireless sensor network nodes can provide scientific guidance to obtain soil moisture information of agricultural fields, it is important for the development of precision agriculture. In this paper, a low-power WUSN nodes was designed, based on modified Frisian transmission model and the complex refractive index Fresnel model, we proposed an adaptive optimization model, and also proposed an improved Genetic Algorithm, which is automatically adjust fusion parameter according to soil and distance factors, it made the prediction of signal attenuation under different soil components more accurately. We used the adaptive optimized model for signal prediction, comparing with the modified Friis prediction model and the complex refractive index Fresnel prediction model, the results shown that the proposed adaptive optimization model with automatic parameter is convenient to predict the signal attenuation, the adaptive optimization model made the prediction error stay really low. In order to compare with other sensors in the soil environment, the temperature of the distributed fiber optic temperature sensor was tested, which predicted by the adaptive model. The result shown that the adaptive model is more favorable to the prediction of signal attenuation in WUSN than distributed fiber optic temperature sensors.\",\"PeriodicalId\":9384,\"journal\":{\"name\":\"Canadian Journal of Soil Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2023-12-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Canadian Journal of Soil Science\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1139/cjss-2022-0105\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"SOIL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Soil Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1139/cjss-2022-0105","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
A Self-adjusting Parametric Model for Attenuation Characteristics of WUSN Signal
Wireless Underground Sensor Network (WUSN) is gradually applied to smart agriculture for soil information collection and monitoring of crop growth environment. WUSN can avoid the inconvenience caused by tillage and other machine operation activities on farmland, and obtains multi-level and multi-dimensional parameters in the underground soil environment, which is crucial for soil moisture monitoring of crops. However, WUSN has no universally applicable transmission protocol standards in the field. Therefore, the research of different soil compositions on the placement of wireless sensor network nodes can provide scientific guidance to obtain soil moisture information of agricultural fields, it is important for the development of precision agriculture. In this paper, a low-power WUSN nodes was designed, based on modified Frisian transmission model and the complex refractive index Fresnel model, we proposed an adaptive optimization model, and also proposed an improved Genetic Algorithm, which is automatically adjust fusion parameter according to soil and distance factors, it made the prediction of signal attenuation under different soil components more accurately. We used the adaptive optimized model for signal prediction, comparing with the modified Friis prediction model and the complex refractive index Fresnel prediction model, the results shown that the proposed adaptive optimization model with automatic parameter is convenient to predict the signal attenuation, the adaptive optimization model made the prediction error stay really low. In order to compare with other sensors in the soil environment, the temperature of the distributed fiber optic temperature sensor was tested, which predicted by the adaptive model. The result shown that the adaptive model is more favorable to the prediction of signal attenuation in WUSN than distributed fiber optic temperature sensors.
期刊介绍:
The Canadian Journal of Soil Science is an international peer-reviewed journal published in cooperation with the Canadian Society of Soil Science. The journal publishes original research on the use, management, structure and development of soils and draws from the disciplines of soil science, agrometeorology, ecology, agricultural engineering, environmental science, hydrology, forestry, geology, geography and climatology. Research is published in a number of topic sections including: agrometeorology; ecology, biological processes and plant interactions; composition and chemical processes; physical processes and interfaces; genesis, landscape processes and relationships; contamination and environmental stewardship; and management for agricultural, forestry and urban uses.