Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling
With the advent of the big data era, water quality detection technology has rapidly advanced, transitioning from traditional manual testing to new real-time monitoring and system management. Currently, big data technology has been widely applied in various aspects of water quality monitoring, includ...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Pearl River
2024-10-01
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| Series: | Renmin Zhujiang |
| Subjects: | |
| Online Access: | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.10.010 |
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| author | ZHU Lijie HE Kai HUANG Sheng YIN Qidong DAI Chao |
| author_facet | ZHU Lijie HE Kai HUANG Sheng YIN Qidong DAI Chao |
| author_sort | ZHU Lijie |
| collection | DOAJ |
| description | With the advent of the big data era, water quality detection technology has rapidly advanced, transitioning from traditional manual testing to new real-time monitoring and system management. Currently, big data technology has been widely applied in various aspects of water quality monitoring, including data collection, real-time monitoring system, data storage and management, data analysis, and risk assessment. Wireless sensor networks and remote sensing have gradually become the mainstream technologies for data collection, while the further use of cloud platforms and various databases has enhanced the development of real-time water quality monitoring. Moreover, the hybrid storage of spatio-temporal big data has significantly improved data storage efficiency. In terms of water quality analysis and prediction, artificial intelligence techniques, such as machine learning and expert systems, have played a significant role. In the future, big data will further facilitate the development of water quality monitoring by integrating with such emerging technologies as the Internet of Things (IoT), upgrading equipment integration, and developing hybrid machine learning models. |
| format | Article |
| id | doaj-art-b059d24a1d494996ae0cc20201f41ba2 |
| institution | Kabale University |
| issn | 1001-9235 |
| language | zho |
| publishDate | 2024-10-01 |
| publisher | Editorial Office of Pearl River |
| record_format | Article |
| series | Renmin Zhujiang |
| spelling | doaj-art-b059d24a1d494996ae0cc20201f41ba22025-01-15T03:02:11ZzhoEditorial Office of Pearl RiverRenmin Zhujiang1001-92352024-10-01459910759019069Development and Prospect of Water Quality Monitoring Technology Driven by Data-model CouplingZHU LijieHE KaiHUANG ShengYIN QidongDAI ChaoWith the advent of the big data era, water quality detection technology has rapidly advanced, transitioning from traditional manual testing to new real-time monitoring and system management. Currently, big data technology has been widely applied in various aspects of water quality monitoring, including data collection, real-time monitoring system, data storage and management, data analysis, and risk assessment. Wireless sensor networks and remote sensing have gradually become the mainstream technologies for data collection, while the further use of cloud platforms and various databases has enhanced the development of real-time water quality monitoring. Moreover, the hybrid storage of spatio-temporal big data has significantly improved data storage efficiency. In terms of water quality analysis and prediction, artificial intelligence techniques, such as machine learning and expert systems, have played a significant role. In the future, big data will further facilitate the development of water quality monitoring by integrating with such emerging technologies as the Internet of Things (IoT), upgrading equipment integration, and developing hybrid machine learning models.http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.10.010water quality monitoringbig dataAI technologyInternet of Things (IoT) |
| spellingShingle | ZHU Lijie HE Kai HUANG Sheng YIN Qidong DAI Chao Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling Renmin Zhujiang water quality monitoring big data AI technology Internet of Things (IoT) |
| title | Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling |
| title_full | Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling |
| title_fullStr | Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling |
| title_full_unstemmed | Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling |
| title_short | Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling |
| title_sort | development and prospect of water quality monitoring technology driven by data model coupling |
| topic | water quality monitoring big data AI technology Internet of Things (IoT) |
| url | http://www.renminzhujiang.cn/thesisDetails#10.3969/j.issn.1001-9235.2024.10.010 |
| work_keys_str_mv | AT zhulijie developmentandprospectofwaterqualitymonitoringtechnologydrivenbydatamodelcoupling AT hekai developmentandprospectofwaterqualitymonitoringtechnologydrivenbydatamodelcoupling AT huangsheng developmentandprospectofwaterqualitymonitoringtechnologydrivenbydatamodelcoupling AT yinqidong developmentandprospectofwaterqualitymonitoringtechnologydrivenbydatamodelcoupling AT daichao developmentandprospectofwaterqualitymonitoringtechnologydrivenbydatamodelcoupling |