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109年度雲林縣水質感測器合辦試驗應用計畫

 專案計畫編號
 經費年度 109年度
 計畫經費 1,010千元
 專案開始日期 2020/11/07
 專案結束日期 2021/05/06
 專案主持人 陳勝恭
 主辦單位 雲林縣環境保護局
 承辦人 陳品婕
 執行單位 能碩工程顧問股份有限公司
 專案分類 水質保護
 中文關鍵字 水質感測器、物聯網、環境監測
 英文關鍵字 Water quality sensor, Internet of Things (IoT), Environmental monitoring
 協同主持人
 共同主持人
 計畫聯絡人 鄭安雅
 計畫聯絡電話 --
 計畫聯絡信箱 --
 專案審查者
 專案審查時間
 專案核對者 第三課-沈家儀
 專案核對時間 2021/07/26

109年度雲林縣水質感測器合辦試驗應用計畫

 中文摘要 本計畫利用物聯網技術結合感測器微型化達到廣布智慧監控感測器,再藉由傳感設備將現場資訊傳至雲端系統,整合水質監測大數據進行分析並透過資訊系統即時進行污染預警工作,以減輕外來之水污染物對於河川水體環境的危害,整體降低影響層面,並以創新思維打造「數位智慧河川」,爰此特擬定「雲林縣109年水質感測物聯網合辦試驗計畫」進行推動及辦理。本計畫完成10台感測器安裝連線,應用於環境稽查1台,水質敏感區2台,污染排放熱點鑑定7台,並進行巡檢校正作業。計畫期間9台感測器因設備故障送回維修合計15次,送修原因包含溫度異常、設備斷訊、設備或pH無法校正及電池充電線接頭燒毀等。另外發生42起設備異常事件,包括:溫度異常、溶氧異常(常出現0)、數值不動、設備斷訊、設備傾斜懸空、被附近民眾拿起、擱淺、卡在石頭下、設備進水、設備被水生植物撐起…等。感測期間發現2起水質異常情形,包括雲林溪上游導電度偏高及惠來厝排水高溫,雲林溪上游確認為畜牧場放流口位置與許可申請之放流口位置不符,已違反水污染防治法第14條第一項進行裁處,惠來厝排水後續未再出現高溫現象,再持續觀察。依據巡檢校正成果分析,溶氧讀值明顯受生物膜生長包覆影響,相關係數(R2)顯示清洗及校正都能提升溶氧準確度,溶氧之R2清洗前為0.4824,但校正後可達0.9712,結果顯示溶氧需要藉由提升校正頻率提升其準確度;導電度清洗及校正前後R2>0.97,準確度高;pH讀值都在誤差範圍內,雖然R2顯示清洗及校正都能提升pH準確度,但相關性不明顯,校正後R2僅達0.8391。溫度無法進行校正,溫度數值呈現低誤差且高準確度,清洗前後R2>0.99。本計畫另加入以溫度為變數,進行多元線性迴歸分析pH清洗前相關性,結果顯示R2由0.46可提升到0.69。數據加值分析部分,整體數據接收率達88%,數據完整率達98%。計畫工作項目已達100%,符合契約相關規定要求。
 中文關鍵字 水質感測器、物聯網、環境監測

109年度雲林縣水質感測器合辦試驗應用計畫

 類型  檔名  說明
 期末報告  109年度雲林縣水質感測器合辦試驗應用計畫(全文).pdf(58.3MB)  期末報告(定稿)
最新版公開日期: 2021/7/27 上午 12:00:00

109 Yunlin County Water Quality Sensor Joint Test Application Project

  摘要 This project uses the Internet of Things (IoT) technology combined with the miniaturization of sensors to achieve a wide range of intelligent monitoring sensors, and then transmits on-site information to the cloud system through sensing equipment, integrates water quality monitoring big data for analysis, and conducts real-time data through the information system. Achieve real-time pollution warning work to reduce the harm of external water pollutants to the river water environment, reduce the overall impact level, and create an "intelligent river" with innovative thinking. The "109 Yunlin County Water Quality Sensor Joint Test Application Project" is specially formulated to promote and implement related work. During the project period, 9 sensors were sent back for repairs due to equipment failures for a total of 15 times. The reasons for the repairs include abnormal temperature, equipment interruption, equipment or pH cannot be calibrated, and battery charging cable connector burned out. In addition, 42 abnormal equipment events occurred, including: abnormal temperature, abnormal dissolved oxygen (often 0), constant values, equipment interruption, equipment tilted and suspended, being picked up by nearby residents, stranded, stuck under rocks, water in the equipment, equipment was propped up by aquatic plants...etc. During the monitoring period, two water quality abnormalities were discovered, including the high conductivity of the upper reaches of Yunlin Creek and the high temperature of Huilaicuo drainage. The upper reaches of Yunlin Creek were confirmed to be inconsistent with the location of the animal husbandry discharge outlet and the license application location, which violated Article 14 Paragraph 1 of the Water Pollution Prevention and Control Law and was punished. The Huilaicuo drainage did not show any high temperature afterwards, so continue to observe. According to the analysis of on-site inspection and calibration results, the dissolved oxygen value is obviously affected by the growth and coating of the biofilm on the electrode. The correlation coefficient (R2) shows that both cleaning and calibration can improve the accuracy of dissolved oxygen. The R2 of dissolved oxygen before cleaning is 0.4824, but it can reach 0.9712 after calibration. The results show that dissolved oxygen needs to increase its accuracy by increasing the calibration frequency. R2 >0.97 before and after the conductivity sensors cleaning and calibration, its accuracy is high. The pH value is within the error range. Although R2 shows that both cleaning and calibration can improve the pH accuracy, the correlation is not obvious. After calibration, R2 only reaches 0.8391. The temperature cannot be corrected, the temperature value shows low error and high accuracy, R2 >0.99 before and after cleaning. In addition, this plan uses temperature as a variable to perform multiple linear regression analysis of the pH value correlation before cleaning. R2 can be increased from 0.46 to 0.69. The overall data reception rate was 88%, and the data integrity rate was 98%. The work progress of the project has reached 100%, which meets the requirements of the contract.
  英文關鍵字 Water quality sensor, Internet of Things (IoT), Environmental monitoring

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