{"title":"Design and development of an innovative online modular device for both water and wastewater monitoring","authors":"Chen-Hua Chu, Yu-Xuan Lin, Chun-Kuo Liu","doi":"10.1117/12.2683680","DOIUrl":null,"url":null,"abstract":"With recent advancements in water-quality analytical technology and the increasing popularity of the Internet of Things (IoT), the market demand for compact and durable automated water-quality monitoring devices has grown substantially. However, the current existing online monitoring devices mostly featuring a single-light source to monitor turbidity and chemical oxygen demand (COD), two critical indicators of natural water bodies, which tend to be influenced by interfering substances that limits their ability to measure more complex water-quality parameters. To address these issues, a new modularized water-quality monitoring device equipped with multi-light sources (UV/VIS/NIR) has been designed and implemented. This device can measure the photo-intensity of scattering, transmission, as well as reference light simultaneously, and coupled with different water-quality prediction models to provide accurate estimates for tap water (Turbidity<2 NTU, relative error < 17.8%), environmental sample (Turbidity<400 NTU, relative error < 2.3%) and industrial wastewater (COD<300 mg/L, relative error < 17.6%). The study results suggest the new designed optical module can effectively monitor turbidity and COD in different water samples and provide alerts for water treatment in high concentration, thereby enabling automated water quality monitoring in future.","PeriodicalId":222517,"journal":{"name":"Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV","volume":"259 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2683680","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With recent advancements in water-quality analytical technology and the increasing popularity of the Internet of Things (IoT), the market demand for compact and durable automated water-quality monitoring devices has grown substantially. However, the current existing online monitoring devices mostly featuring a single-light source to monitor turbidity and chemical oxygen demand (COD), two critical indicators of natural water bodies, which tend to be influenced by interfering substances that limits their ability to measure more complex water-quality parameters. To address these issues, a new modularized water-quality monitoring device equipped with multi-light sources (UV/VIS/NIR) has been designed and implemented. This device can measure the photo-intensity of scattering, transmission, as well as reference light simultaneously, and coupled with different water-quality prediction models to provide accurate estimates for tap water (Turbidity<2 NTU, relative error < 17.8%), environmental sample (Turbidity<400 NTU, relative error < 2.3%) and industrial wastewater (COD<300 mg/L, relative error < 17.6%). The study results suggest the new designed optical module can effectively monitor turbidity and COD in different water samples and provide alerts for water treatment in high concentration, thereby enabling automated water quality monitoring in future.