Design of Water Quality Monitoring System in Shaanxi Section of Weihe River Basin Based on the Internet of Things
Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country’s strategic requirements for water resources and water ecological protection. This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet...
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| Veröffentlicht in: | Computational intelligence and neuroscience 2022-07, Vol.2022, p.3543937-7 |
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| creator | Dang, Tianjiao Liu, Jifa |
| description | Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country’s strategic requirements for water resources and water ecological protection. This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet of Things technology to develop water quality monitoring sensors, so as to realize the construction of low-cost, high-reliability water quality monitoring demonstration applications. First of all, we established the design of the water quality collection terminal, designed the low-power water quality sensor node, supported the Internet of Things protocol and the collection of various water quality parameters, and used networking for data transmission. Secondly, we use the ant colony algorithm-based system clustering model to obtain a cluster map of water quality monitoring tasks in a certain section of the Weihe River Basin. We take the task clustering graph as an example for analysis, optimize the monitoring model through the ant colony algorithm, and obtain the weight of the optimization index. The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance. |
| doi_str_mv | 10.1155/2022/3543937 |
| format | Article |
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This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet of Things technology to develop water quality monitoring sensors, so as to realize the construction of low-cost, high-reliability water quality monitoring demonstration applications. First of all, we established the design of the water quality collection terminal, designed the low-power water quality sensor node, supported the Internet of Things protocol and the collection of various water quality parameters, and used networking for data transmission. Secondly, we use the ant colony algorithm-based system clustering model to obtain a cluster map of water quality monitoring tasks in a certain section of the Weihe River Basin. We take the task clustering graph as an example for analysis, optimize the monitoring model through the ant colony algorithm, and obtain the weight of the optimization index. The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2022/3543937</identifier><identifier>PMID: 35909849</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Agricultural production ; Algorithms ; Analysis ; Ant colony optimization ; Aquatic resources ; Chemical oxygen demand ; China ; Clustering ; Data mining ; Data transmission ; Economic development ; Environmental monitoring ; Environmental Monitoring - methods ; Hydrology ; Internet ; Internet of Things ; Monitoring ; Monitoring systems ; Pilot Projects ; Reproducibility of Results ; River basins ; Rivers ; Sensors ; Water area ; Water pollution ; Water Quality ; Water resources</subject><ispartof>Computational intelligence and neuroscience, 2022-07, Vol.2022, p.3543937-7</ispartof><rights>Copyright © 2022 Tianjiao Dang and Jifa Liu.</rights><rights>COPYRIGHT 2022 John Wiley & Sons, Inc.</rights><rights>Copyright © 2022 Tianjiao Dang and Jifa Liu. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2022 Tianjiao Dang and Jifa Liu. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-2240de523990ba9f09b14ab2309cc36adff106616a528eed193fb139770fba513</citedby><cites>FETCH-LOGICAL-c476t-2240de523990ba9f09b14ab2309cc36adff106616a528eed193fb139770fba513</cites><orcidid>0000-0001-5027-3427</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9334113/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9334113/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,883,27907,27908,53774,53776</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35909849$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Khan, Rahim</contributor><contributor>Rahim Khan</contributor><creatorcontrib>Dang, Tianjiao</creatorcontrib><creatorcontrib>Liu, Jifa</creatorcontrib><title>Design of Water Quality Monitoring System in Shaanxi Section of Weihe River Basin Based on the Internet of Things</title><title>Computational intelligence and neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><description>Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country’s strategic requirements for water resources and water ecological protection. This paper takes the Shaanxi section of the Weihe River Basin as a pilot project and aims to use the Internet of Things technology to develop water quality monitoring sensors, so as to realize the construction of low-cost, high-reliability water quality monitoring demonstration applications. First of all, we established the design of the water quality collection terminal, designed the low-power water quality sensor node, supported the Internet of Things protocol and the collection of various water quality parameters, and used networking for data transmission. Secondly, we use the ant colony algorithm-based system clustering model to obtain a cluster map of water quality monitoring tasks in a certain section of the Weihe River Basin. We take the task clustering graph as an example for analysis, optimize the monitoring model through the ant colony algorithm, and obtain the weight of the optimization index. The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance.</description><subject>Agricultural production</subject><subject>Algorithms</subject><subject>Analysis</subject><subject>Ant colony optimization</subject><subject>Aquatic resources</subject><subject>Chemical oxygen demand</subject><subject>China</subject><subject>Clustering</subject><subject>Data mining</subject><subject>Data transmission</subject><subject>Economic development</subject><subject>Environmental monitoring</subject><subject>Environmental Monitoring - methods</subject><subject>Hydrology</subject><subject>Internet</subject><subject>Internet of Things</subject><subject>Monitoring</subject><subject>Monitoring systems</subject><subject>Pilot Projects</subject><subject>Reproducibility of Results</subject><subject>River basins</subject><subject>Rivers</subject><subject>Sensors</subject><subject>Water area</subject><subject>Water pollution</subject><subject>Water 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Khan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Design of Water Quality Monitoring System in Shaanxi Section of Weihe River Basin Based on the Internet of Things</atitle><jtitle>Computational intelligence and neuroscience</jtitle><addtitle>Comput Intell Neurosci</addtitle><date>2022-07-21</date><risdate>2022</risdate><volume>2022</volume><spage>3543937</spage><epage>7</epage><pages>3543937-7</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>Monitoring environmental water quality in an efficient, cheap, and sustainable way can better serve the country’s strategic requirements for water resources and water ecological protection. 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The weight of the scheduled task limit of the monitoring point becomes larger, so the release of the monitoring task mainly affects the limit of the scheduled task of the monitoring point. Through the above work, we designed and implemented a set of online water quality monitoring system based on the Internet of Things and data mining technology. The system can provide reference for large-scale water resource protection and water environment governance.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>35909849</pmid><doi>10.1155/2022/3543937</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-5027-3427</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Agricultural production Algorithms Analysis Ant colony optimization Aquatic resources Chemical oxygen demand China Clustering Data mining Data transmission Economic development Environmental monitoring Environmental Monitoring - methods Hydrology Internet Internet of Things Monitoring Monitoring systems Pilot Projects Reproducibility of Results River basins Rivers Sensors Water area Water pollution Water Quality Water resources |
| title | Design of Water Quality Monitoring System in Shaanxi Section of Weihe River Basin Based on the Internet of Things |
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