{"title":"校准低成本雨量计传感器,使其应用于物联网(IoT)基础设施,从而实现环境监测网络的密集化","authors":"Robert Krüger, Pierre Karrasch, Anette Eltner","doi":"10.5194/gi-13-163-2024","DOIUrl":null,"url":null,"abstract":"Abstract. Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in their spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT)-enabled low-cost sensor systems have offered a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, 20 sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden (Dresden University of Technology). Furthermore, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration.","PeriodicalId":48742,"journal":{"name":"Geoscientific Instrumentation Methods and Data Systems","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Calibrating low-cost rain gauge sensors for their applications in Internet of Things (IoT) infrastructures to densify environmental monitoring networks\",\"authors\":\"Robert Krüger, Pierre Karrasch, Anette Eltner\",\"doi\":\"10.5194/gi-13-163-2024\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in their spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT)-enabled low-cost sensor systems have offered a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, 20 sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden (Dresden University of Technology). Furthermore, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration.\",\"PeriodicalId\":48742,\"journal\":{\"name\":\"Geoscientific Instrumentation Methods and Data Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoscientific Instrumentation Methods and Data Systems\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.5194/gi-13-163-2024\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoscientific Instrumentation Methods and Data Systems","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/gi-13-163-2024","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Calibrating low-cost rain gauge sensors for their applications in Internet of Things (IoT) infrastructures to densify environmental monitoring networks
Abstract. Environmental observations are crucial for understanding the state of the environment. However, current observation networks are limited in their spatial and temporal resolution due to high costs. For many applications, data acquisition with a higher resolution would be desirable. Recently, Internet of Things (IoT)-enabled low-cost sensor systems have offered a solution to this problem. While low-cost sensors may have lower quality than sensors in official measuring networks, they can still provide valuable data. This study describes the requirements for such a low-cost sensor system, presents two implementations, and evaluates the quality of the factory calibration for a widely used low-cost precipitation sensor. Here, 20 sensors have been tested for an 8-month period against three reference instruments at the meteorological site of the TU Dresden (Dresden University of Technology). Furthermore, the factory calibration of 66 rain gauges has been evaluated in the lab. Results show that the used sensor falls short for the desired out-of-the-box use case. Nevertheless, it could be shown that the accuracy could be improved by further calibration.
期刊介绍:
Geoscientific Instrumentation, Methods and Data Systems (GI) is an open-access interdisciplinary electronic journal for swift publication of original articles and short communications in the area of geoscientific instruments. It covers three main areas: (i) atmospheric and geospace sciences, (ii) earth science, and (iii) ocean science. A unique feature of the journal is the emphasis on synergy between science and technology that facilitates advances in GI. These advances include but are not limited to the following:
concepts, design, and description of instrumentation and data systems;
retrieval techniques of scientific products from measurements;
calibration and data quality assessment;
uncertainty in measurements;
newly developed and planned research platforms and community instrumentation capabilities;
major national and international field campaigns and observational research programs;
new observational strategies to address societal needs in areas such as monitoring climate change and preventing natural disasters;
networking of instruments for enhancing high temporal and spatial resolution of observations.
GI has an innovative two-stage publication process involving the scientific discussion forum Geoscientific Instrumentation, Methods and Data Systems Discussions (GID), which has been designed to do the following:
foster scientific discussion;
maximize the effectiveness and transparency of scientific quality assurance;
enable rapid publication;
make scientific publications freely accessible.