進階搜尋


   電子論文尚未授權公開,紙本請查館藏目錄
(※如查詢不到或館藏狀況顯示「閉架不公開」,表示該本論文不在書庫,無法取用。)
系統識別號 U0026-0608202014075400
論文名稱(中文) 研發低成本輕量化水質測量系統應用於無人機水庫水質監測
論文名稱(英文) Development of a low-cost, lightweight water quality measurement system equipped on Unmanned Aerial Vehicle (UAV) platform for reservoir water quality monitoring
校院名稱 成功大學
系所名稱(中) 環境工程學系
系所名稱(英) Department of Environmental Engineering
學年度 108
學期 2
出版年 109
研究生(中文) 林郁竣
研究生(英文) Yu-Chun Lin
學號 P56071141
學位類別 碩士
語文別 中文
論文頁數 139頁
口試委員 指導教授-張智華
口試委員-林財富
口試委員-陳起鳳
口試委員-朱宏杰
中文關鍵字 低成本  輕量化  水質測量系統  無人機  水庫水質監測  沙奇深度  沙奇盤  水質地圖 
英文關鍵字 Low cost  Light weight  Water quality measurement system  UAV  Reservoir water quality monitoring 
學科別分類
中文摘要 台灣水庫面臨水量不足及水質惡化的問題,導致水庫的有效容積量逐年降低及優氧化,因此政府制訂環境水體水質監測計畫,其中的水庫水質分為人供採樣回實驗室分析及現場觀測兩個部分,不過隨著科技的進步,感測器及物聯網的技術逐漸成熟,無人機操作門檻也降低許多,水庫管理單位可以運用全自動高頻監測技術(Automatic High Frequency Monitoring ,AHFM)結合高機動性的無人機規劃即時且全面的水質監測網路,但市面上商業化的全自動高頻監測系統,動輒數十萬到上百萬,體積及重量也十分龐大,不適合直接搭載於無人機。同時本研究回顧可運用於全自動高頻監測技術的水質項目,發現沙奇深度(Secchi depth)沒有可以直接量測的感測器,因此本研究預計開發兩款可直接搭載於無人機的水質感測器,第一個是低成本輕量化的水質測量系統,簡稱WQMS,第二個是低成本取代沙奇盤測量沙奇深度的感測器,簡稱為KdUINO,將兩款水質感測器搭載於無人機應用於水庫水質監測。
本研究設計WQMS的預計量測水溫、導電度、溶氧及pH等水質項目,從市面上購買所需的水質感測器及零件,以Arduino控制板整合硬體,以C++程式語言編譯WQMS的程式碼,並於七股漁塭中以商業化多參數水質測量設備EXO2測試WQMS的穩定性及準確性;KdUINO的設計架構是參考(Bardaji et al., 2016)開發的低成本測量水中光衰減係數(Kd)的光度計,在澄清湖水庫同時測量Kd與SD,根據SD物理模式建立兩者的關係式,最後應用無人機搭載WQMS與KdUINO光度計在澄清湖水庫隨機挑選採樣點測量水質,以空間內差法(Spline with Barrier)建立現地測量的水質地圖,與最近日期的澄清湖水質監測站水質比較,另外也利用Sentinel-2A衛星拍攝的影像以海洋演算法建立Kd、SD水質圖與現地量測的水質圖比較,由於KdUINO的Kd與衛星遙測的Kd尺度不同必須建立關係式,才可以進行比較。
本研究開發的WQMS的成本為新台幣15,228元,重量為1公斤,遠低於市售的多參數水質測量設備,在七股測試WQMS的穩定性及準確性的結果,可以知道導電度及水溫感測器的穩定性低,測量結果產生誤差,pH及溶氧感測器的穩定性較佳。本研究研發的KdUINO光度計成本為新台幣3100元,重量約2公斤,由於市面上沒有相似的產品無法比較;從實驗的結果來看,根據SD物理模式所推估Kd與SD的關係式,發現兩者具有顯著的相關性,但這個關係式有使用範圍限制;以WQMS測量水質所建立的水質圖,與最近日期的澄清湖水質監測站水質資料相比,雖然導電度及水溫感測器長時間測量水質的穩定性差,但短時間測量水質的穩定性較佳,結果顯示四種水質參數建立的水質圖皆為合理;以KdUINO測量Kd建立Kd、SD的水質圖,也清楚反映澄清湖水庫的實際情況,Sentinel-2A衛星遙測建立的Kd、SD水質圖比較結果,發現KdUINO測量到的Kd超過測量極限將不再變化,因此使用相似的Sigmoid函數建立衛星遙測Kd與KdUINO Kd的關係式,結果顯示兩者具有顯著的相關性,轉換式同樣有使用範圍限制,KdUINO Kd經過轉換式轉換建立的水質圖與衛星遙測的Kd水質圖具有相同的趨勢,同樣的結果也發現在KdUINO SD水質圖與衛星遙測SD水質圖,雖然在湖心的SD有顯著的差異,但其他區域的SD兩者之間有相同的趨勢。
從WQMS的測試結果知道,DFRobot公司所生產的導電度及水溫感測器較為不穩定,建議可以使用品質較好的廠牌,不過導電度及水溫感測器短時間測量水質建立成水質圖的結果是合理的;KdUINO光度計測量的Kd與現地量測的SD及衛星遙測的Kd具有高度的正相關性,建立的Kd水質圖與衛星遙測的水質圖也有相同的趨勢,表示KdUINO是可以取代沙奇盤測量SD的感測器。
英文摘要 This study is expected to develop two water quality sensors. The first is a low-cost lightweight water quality measurement system (WQMS), which is used to measure water temperature, dissolved oxygen (DO), conductivity, pH, and the second is to replace Secchi disk measures Secchi depth of the sensor (KdUINO), and WQMS and KdUINO are equipped on the UAV platform to monitor the water quality of the reservoir.In this study, we tested the stability and accuracy of WQMS in Qigu. The relationship between Kdand SD is established based on Secchi depth physical model. Use the UAV to carry WQMS and KdUINO to measure the water quality of the reservoirn and use Arc GIS to establish the water quality map, compare Kd water quality map with the satellite remote sensing Kd water quality map. The results show that the conductivity of WQMS and the stability of the water temperature sensor are poor. It is recommended to use other brands, But the accuracy used to build the water quality map is reasonable. The Kd measured by KdUINO has a good correlation with the SD and Kd of the satellite remote sensing. It means that KdUINO can be used as a sensor to replace the Secchi disk to measure Secchi depth.
論文目次 摘要 I
致謝 VI
目錄 VIII
表目錄 XII
圖目錄 XIV
第 1 章 前言 1
1.1 研究動機 1
1.2 研究目的 2
1.2.1 研發低成本輕量化水質測量系統 2
1.2.2 開發替代沙奇盤測量沙奇深度之微型感測器(KdUINO) 3
1.2.3 應用無人機搭載WQMS與KdUINO建立水質圖 3
1.3 論文架構 3
第 2 章 文獻回顧 6
2.1 水庫水質監測 6
2.1.1 水庫水質監測目的 6
2.1.2 水庫水質例行監測項目 7
2.2 低成本輕量化水質測量系統 10
2.2.1 水庫水質全自動高頻監測技術 10
2.2.2 水質感測器 17
2.2.3 Arduino開源硬體 23
2.2.4 物聯網技術(IoT) 27
2.3 替代沙奇盤測量透明度之微型感測器 32
2.3.1 沙奇盤(Secchi disk) 32
2.3.2 透明度物理模式發展及應用 33
2.4 應用無人機於環境水體監測 36
2.4.1 無人機應用於水質監測 36
2.4.2 無人機應用於採集水樣 37
2.5 利用空間內插建立水質圖 40
第 3 章 研究方法 42
3.1 研發低成本輕量化水質測量系統(WQMS) 42
3.1.1 WQMS系統架構 42
3.1.2 水質感測器模組 43
3.1.3 控制模組 45
3.1.4 無線傳輸通訊模組及供電模組 46
3.1.5 防水裝置 47
3.1.6 WQMS程式架構及無線傳輸設定 48
3.2 WQMS-穩定性及準確性 51
3.2.1 系統測試環境 51
3.2.2 系統測試方法 52
3.2.3 分析方法 53
3.3 測量沙奇深度感測器開發(KdUINO) 55
3.3.1 水中光衰減係數(Kd)的定義及標準測量方法 55
3.3.2 KdUINO光度計設計架構 56
3.3.3 建立沙奇深度與水中光衰減係數(Kd)的關係 59
3.4 無人機吊掛技術 62
3.4.1 無人機選擇 62
3.4.2 無人機吊掛KdUINO光度計與WQMS概念 63
3.5 應用無人機搭載WQMS與KdUINO建立水質圖 65
3.5.1 研究區域 65
3.5.2 實驗方法 70
3.5.3 點測值空間內插法 71
3.5.4 水質內插圖之誤差分析 71
3.6 遙測影像水質圖建立 72
3.6.1 影像前處理 73
3.6.2 遙測影像水質演算法 73
3.6.3 遙測影像水質圖建立 74
第 4 章 結果與討論 75
4.1 研發低成本輕量化水質測量系統(WQMS) 75
4.1.1 WQMS 75
4.1.2 整合無人機與WQMS及KdUINO之方法 81
4.2 WQMS穩定性及準確性測試 87
4.2.1 趨勢圖比較 87
4.2.2 成對T檢定分析結果 90
4.3 測量透明度感測器開發(KdUINO) 92
4.3.1 KdUINO 92
4.3.2 現地Kd與SD轉換關係式之建立 95
4.3.3 KdUINO量測值與Sentinel-2A Kd產品之比較 98
4.4 以無人機搭載WQMS與KdUINO建立水質分佈圖 105
4.4.1 WQMS點測值內插建立水質分佈圖 105
4.4.1.1 溶氧分佈圖及誤差分析 106
4.4.1.2 導電度分佈圖及誤差分析 108
4.4.1.3 水溫分佈圖及誤差分析 110
4.4.1.4 酸鹼值分佈圖及誤差分析 111
4.4.2 KdUINO點測值內插建立SD分佈圖 113
第 5 章 結論與建議 116
5.1 結論 116
5.2 建議 118
第 6 章 參考文獻 120
附錄 130
參考文獻 Aaruththiran, M. (2019). Smartphone-based Real-Time Water Quality Monitoring System. The University of Nottingham,
Adhikary, S.K., Ahmed, C.A., & Saha, G.C. (2013). Mapping of shallow groundwater quality using GIS: a study from a small catchment in Northwestern Region of Bangladesh. Paper presented at the International Conference On Engineering Research, Innovation and Education.
Alcântara, E.H., Stech, J.L., Lorenzzetti, J.A., Bonnet, M.P., Casamitjana, X., Assireu, A.T., & de Moraes Novo, E.M.L. (2010). Remote sensing of water surface temperature and heat flux over a tropical hydroelectric reservoir. Remote Sensing of Environment, 114(11), 2651-2665.
Anzalone, G.C., Glover, A.G., & Pearce, J.M. (2013). Open-source colorimeter. Sensors, 13(4), 5338-5346. Retrieved from https://res.mdpi.com/d_attachment/sensors/sensors-13-05338/article_deploy/sensors-13-05338.pdf
ArcGIS. (2020). Spline with Barriers principle. Retrieved from https://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/spline-with-barriers.htm
Arruda, J.A., Marzolf, G.R., & Faulk, R.T. (1983). The role of suspended sediments in the nutrition of zooplankton in turbid reservoirs. Ecology, 64(5), 1225-1235.
Arslan, H. (2012). Spatial and temporal mapping of groundwater salinity using ordinary kriging and indicator kriging: The case of Bafra Plain, Turkey. Agricultural water management, 113, 57-63.
AtlasScientific. (2020). Water quality sensor catalog. Retrieved from https://atlas-scientific.com/kits/
Badamasi, Y.A. (2014). The working principle of an Arduino. Paper presented at the 2014 11th international conference on electronics, computer and computation (ICECCO).
Bardaji, R., Sanchez, A.M., Simon, C., Wernand, M.R., & Piera, J. (2016). Estimating the Underwater Diffuse Attenuation Coefficient with a Low-Cost Instrument: The KdUINO DIY Buoy. Sensors (Basel), 16(3). doi:10.3390/s16030373
Cao, W., Hu, J., & Yu, X. (2009). A study on temperature interpolation methods based on GIS. Paper presented at the 2009 17th International Conference on Geoinformatics.
Cayan, D.R., Das, T., Pierce, D.W., Barnett, T.P., Tyree, M., & Gershunov, A. (2010). Future dryness in the southwest US and the hydrology of the early 21st century drought. Proceedings of the National Academy of Sciences, 107(50), 21271-21276.
Childs, P.R., Greenwood, J., & Long, C. (2000). Review of temperature measurement. Review of scientific instruments, 71(8), 2959-2978.
Davies‐Colley, R.J. (1988). Measuring water clarity with a black disk. Limnology and oceanography, 33(4), 616-623.
Davis, J.C. (1975). Minimal dissolved oxygen requirements of aquatic life with emphasis on Canadian species: a review. Journal of the Fisheries Board of Canada, 32(12), 2295-2332.
de Carvalho Silva, J., Rodrigues, J.J., Alberti, A.M., Solic, P., & Aquino, A.L. (2017). LoRaWAN—A low power WAN protocol for Internet of Things: A review and opportunities. Paper presented at the 2017 2nd International Multidisciplinary Conference on Computer and Energy Science (SpliTech).
DFRobot. (2020). PH_meter SKU SEN0161. Retrieved from https://wiki.dfrobot.com/PH_meter_SKU__SEN0161_
DJI大疆創新. (2020). DJI Matrice 600 Pro. Retrieved from https://store.dji.com/zh-tw/product/matrice-600-pro
Doi, H., Akamatsu, Y., Watanabe, Y., Goto, M., Inui, R., Katano, I., Nagano, M., Takahara, T., & Minamoto, T. (2017). Water sampling for environmental DNA surveys by using an unmanned aerial vehicle. Limnology and Oceanography: Methods, 15(11), 939-944.
Dunbabin, M., Grinham, A., & Udy, J. (2009). An autonomous surface vehicle for water quality monitoring. Paper presented at the Australasian Conference on Robotics and Automation (ACRA).
Duntley, S. (1952). The visibility of submerged objects, Visibility Laboratory. Final Report, 31, 685-730.
Elijah, O., Rahman, T., Yeen, H., Leow, C., Sarijari, M., Aris, A., Salleh, J., & Han, C. (2018). Application of UAV and Low Power Wide Area Communication Technology for Monitoring of River Water Quality. Paper presented at the 2018 2nd International Conference on Smart Sensors and Application (ICSSA).
Elumalai, V., Brindha, K., Sithole, B., & Lakshmanan, E. (2017). Spatial interpolation methods and geostatistics for mapping groundwater contamination in a coastal area. Environmental Science and Pollution Research, 24(12), 11601-11617. Retrieved from https://link.springer.com/content/pdf/10.1007/s11356-017-8681-6.pdf
Frank, C., Schroeder, F., & Petersen, W. (2010). FerryBox: Using automated water measurement systems to monitor water quality: Perspectives for the Yangtze river and Three Gorges Dam. Journal of Earth Science, 21(6), 861-869.
Gallegos, C.L., Werdell, P.J., & McClain, C.R. (2011). Long‐term changes in light scattering in Chesapeake Bay inferred from Secchi depth, light attenuation, and remote sensing measurements. Journal of Geophysical Research: Oceans, 116(C7).
Gharbia, A.S., Gharbia, S.S., Abushbak, T., Wafi, H., Aish, A., Zelenakova, M., & Pilla, F. (2016). Groundwater quality evaluation using GIS based geostatistical algorithms. Journal of Geoscience and Environment Protection, 4(2), 89-103.
González-García, C., Condado, S.G., García-García, M.J., & Werenitzky, D. (2013). Analysis of seasonal variations in the quality of water in a reservoir using GIS techniques. Desalination and Water Treatment, 51(13-15), 2609-2616.
Guhathakurta, P., Sreejith, O., & Menon, P. (2011). Impact of climate change on extreme rainfall events and flood risk in India. Journal of earth system science, 120(3), 359.
iThome. (2020). 物聯網技術大剖析. Retrieved from https://www.ithome.com.tw/news/90461
Kadhem, A.J. (2013). Assessment of water quality in Tigris River-Iraq by using GIS mapping. Natural Resources, 2013.
Kadlec, R.H. (1999). Chemical, physical and biological cycles in treatment wetlands. Water Science and Technology, 40(3), 37.
Kageyama, Y., Takahashi, J., Nishida, M., Kobori, B., & Nagamoto, D. (2016). Analysis of water quality in Miharu dam reservoir, Japan, using UAV data. IEEJ Transactions on Electrical and Electronic Engineering, 11, S183-S185.
Kelley, C.D., Krolick, A., Brunner, L., Burklund, A., Kahn, D., Ball, W.P., & Weber-Shirk, M. (2014). An affordable open-source turbidimeter. Sensors, 14(4), 7142-7155. Retrieved from https://res.mdpi.com/d_attachment/sensors/sensors-14-07142/article_deploy/sensors-14-07142.pdf
Koparan, C., & Koc, A.B. (2016). Unmanned Aerial Vehicle (UAV) assisted water sampling. Paper presented at the 2016 ASABE annual international meeting.
Koparan, C., Koc, A.B., Privette, C.V., & Sawyer, C.B. (2018). In situ water quality measurements using an unmanned aerial vehicle (UAV) system. Water, 10(3), 264.
Lambrou, T.P., Anastasiou, C.C., Panayiotou, C.G., & Polycarpou, M.M. (2014). A low-cost sensor network for real-time monitoring and contamination detection in drinking water distribution systems. IEEE sensors journal, 14(8), 2765-2772.
Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440.
Lee, J., Lee, S., Yu, S., & Rhew, D. (2016). Relationships between water quality parameters in rivers and lakes: BOD 5, COD, NBOPs, and TOC. Environmental monitoring and assessment, 188(4), 252.
Lee, Z., Carder, K.L., & Arnone, R.A. (2002). Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. Applied optics, 41(27), 5755-5772.
Leeuw, T., Boss, E.S., & Wright, D.L. (2013). In situ measurements of phytoplankton fluorescence using low cost electronics. Sensors, 13(6), 7872-7883. Retrieved from https://res.mdpi.com/d_attachment/sensors/sensors-13-07872/article_deploy/sensors-13-07872.pdf
Li, C.K. (1989). pH glass electrode and its mechanism. In: ACS Publications.
Logan, B., & Taffs, K.H. (2013). Relationship between diatoms and water quality (TN, TP) in sub-tropical east Australian estuaries. Journal of Paleolimnology, 50(1), 123-137.
Marcé, R., George, G., Buscarinu, P., Deidda, M., Dunalska, J., de Eyto, E., Flaim, G., Grossart, H.-P., Istvanovics, V., & Lenhardt, M. (2016). Automatic high frequency monitoring for improved lake and reservoir management. Environmental science & technology, 50(20), 10780-10794.
Moses, W.J., Gitelson, A.A., Berdnikov, S., & Povazhnyy, V. (2009). Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data—successes and challenges. Environmental research letters, 4(4), 045005.
muRata. (2020). LoRa (LoRaWAN) Module. Retrieved from https://www.murata.com/zh-cn/products/connectivitymodule/lpwa/lora
Nag, A., & Mukhopadhyay, S.C. (2014). Smart Home: Recognition of activities of elderly for 24/7; Coverage issues. Paper presented at the Proceedings of the 2014 international conference on sensing technology, Liverpool, UK.
Nas, B., & Berktay, A. (2010). Groundwater quality mapping in urban groundwater using GIS. Environmental monitoring and assessment, 160(1-4), 215-227.
Oke, A., Sangodoyin, A., Ogedengbe, K., & Omodele, T. (2013). Mapping of river waterquality using inverse distance weighted interpolation in Ogun-Osun river basin, Nigeria. Acta Geographica Debrecina Landscape & Environment, 7(2), 48-62.
Palattella, M.R., Accettura, N., Grieco, L.A., Boggia, G., Dohler, M., & Engel, T. (2013). On optimal scheduling in duty-cycled industrial IoT applications using IEEE802. 15.4 e TSCH. IEEE Sensors Journal, 13(10), 3655-3666.
Poursafar, N., Alahi, M.E.E., & Mukhopadhyay, S. (2017). Long-range wireless technologies for IoT applications: A review. Paper presented at the 2017 Eleventh International Conference on Sensing Technology (ICST).
Preisendorfer, R.W. (1986). SECCHI DISK SCIENCE - VISUAL OPTICS OF NATURAL-WATERS. Limnology and Oceanography, 31(5), 909-926. doi:10.4319/lo.1986.31.5.0909
Qin, J.J., Oo, M.H., Kekre, K.A., Knops, F., & Miller, P. (2006). Impact of coagulation pH on enhanced removal of natural organic matter in treatment of reservoir water. Separation and Purification Technology, 49(3), 295-298.
Qu, T., Lei, S., Wang, Z., Nie, D., Chen, X., & Huang, G.Q. (2016). IoT-based real-time production logistics synchronization system under smart cloud manufacturing. The International Journal of Advanced Manufacturing Technology, 84(1-4), 147-164.
Quilumba, F.L., Lee, W.-J., Huang, H., Wang, D.Y., & Szabados, R.L. (2014). Using smart meter data to improve the accuracy of intraday load forecasting considering customer behavior similarities. IEEE Transactions on Smart Grid, 6(2), 911-918.
Ramos, P.M., Pereira, J.D., Ramos, H.M.G., & Ribeiro, A.L. (2008). A four-terminal water-quality-monitoring conductivity sensor. IEEE Transactions on Instrumentation and Measurement, 57(3), 577-583.
Rixen, T., Baum, A., Sepryani, H., Pohlmann, T., Jose, C., & Samiaji, J. (2010). Dissolved oxygen and its response to eutrophication in a tropical black water river. Journal of environmental management, 91(8), 1730-1737.
Rode, M., Wade, A.J., Cohen, M.J., Hensley, R.T., Bowes, M.J., Kirchner, J.W., Arhonditsis, G.B., Jordan, P., Kronvang, B., & Halliday, S.J. (2016). Sensors in the stream: the high-frequency wave of the present. In: ACS Publications.
Schwarzbach, M., Laiacker, M., Mulero-Pázmány, M., & Kondak, K. (2014). Remote water sampling using flying robots. Paper presented at the 2014 International Conference on Unmanned Aircraft Systems (ICUAS).
SigFox. (2020). SigFox無線傳輸網路架構. Retrieved from https://www.sigfox.com/en/what-sigfox/technology
Simpson, G., & Wu, Y.H. (2014). Accuracy and effort of interpolation and sampling: can GIS help lower field costs? ISPRS International Journal of Geo-Information, 3(4), 1317-1333.
Siregar, B., Menen, K., Efendi, S., Andayani, U., & Fahmi, F. (2017). Monitoring quality standard of waste water using wireless sensor network technology for smart environment. Paper presented at the 2017 International Conference on ICT For Smart Society (ICISS).
Srivastava, P.K., Pandey, P.C., Petropoulos, G.P., Kourgialas, N.N., Pandey, V., & Singh, U. (2019). GIS and remote sensing aided information for soil moisture estimation: A comparative study of interpolation techniques. Resources, 8(2), 70.
Su, T.C. (2015). Multispectral sensors carried on unmanned aerial vehicle (UAV) for trophic state mapping of the small reservoir in Kinmen, Taiwan. Paper presented at the 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Swan, M. (2015). Connected car: quantified self becomes quantified car. Journal of Sensor and Actuator Networks, 4(1), 2-29.
Terada, A., Morita, Y., Hashimoto, T., Mori, T., Ohba, T., Yaguchi, M., & Kanda, W. (2018). Water sampling using a drone at Yugama crater lake, Kusatsu-Shirane volcano, Japan. Earth, Planets and Space, 70(1), 1-9.
Thingspeak. (2020). Retrieved from https://thingspeak.com/
Vanhellemont, Q., & Ruddick, K. (2014). Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sensing of Environment, 145, 105-115.
Wang, X., Li, J., Chen, J., Cui, L., Li, W., Gao, X., & Liu, Z. (2020). Water quality criteria of total ammonia nitrogen (TAN) and un-ionized ammonia (NH3-N) and their ecological risk in the Liao River, China. Chemosphere, 243, 125328.
Wang, Y.-P.E., Lin, X., Adhikary, A., Grovlen, A., Sui, Y., Blankenship, Y., Bergman, J., & Razaghi, H.S. (2017). A primer on 3GPP narrowband Internet of Things. IEEE Communications Magazine, 55(3), 117-123.
Wittkampf, M., Chemnitius, G.-C., Cammann, K., Rospert, M., & Mokwa, W. (1997). Silicon thin film sensor for measurement of dissolved oxygen. Sensors and Actuators B: Chemical, 43(1-3), 40-44.
Wu, T., Zhu, G., Zhu, M., Xu, H., Zhang, Y., & Qin, B. (2020). Use of conductivity to indicate long-term changes in pollution processes in Lake Taihu, a large shallow lake. Environmental Science and Pollution Research, 1-10.
Xie, Y.F., Chen, T.B., Lei, M., Yang, J., Guo, Q.J., Song, B., & Zhou, X.Y. (2011). Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis. Chemosphere, 82(3), 468-476.
YSI. (2020a). Retrieved from https://www.ysi.com/EXO2
YSI. (2020b). YSI EXO2用戶手冊. Retrieved from https://www.ysi.com/File%20Library/Documents/Manuals/EXO_User_Manual-Rev-C-Chinese.pdf
Zeng, C., Richardson, M., & King, D.J. (2017). The impacts of environmental variables on water reflectance measured using a lightweight unmanned aerial vehicle (UAV)-based spectrometer system. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 217-230.
中文百科. (2020). 玻璃電極 glass electrode. Retrieved from https://www.newton.com.tw/wiki/%E7%8E%BB%E7%92%83%E9%9B%BB%E6%A5%B5
台灣智能感測科技有限公司. (2020a). Retrieved from https://www.taiwansensor.com.tw/
台灣智能感測科技有限公司. (2020b). Arduino UNO R3. Retrieved from https://www.taiwansensor.com.tw/product/arduino-uno-r3-%E7%BE%A9%E5%A4%A7%E5%88%A9%E5%8E%9F%E8%A3%9D-arduino-uno-rev33-%E9%96%8B%E7%99%BC%E6%9D%BF-made-in-italy/
台灣銀行. (2020). 2020/06/30美金即期匯率. Retrieved from https://rate.bot.com.tw/xrt/quote/2020-06/USD
行政院環境保護署. 全國環境水質監測資訊網. Retrieved from https://wq.epa.gov.tw/Code/Business/ItemMethod.aspx
行政院環境保護署. (2020a). 水中光強度檢測方法. Retrieved from https://www.epa.gov.tw/DisplayFile.aspx?FileID=839939AF0B090707
行政院環境保護署. (2020b). 河川、湖泊及水庫水質採樣通則. Retrieved from https://www.epa.gov.tw/DisplayFile.aspx?FileID=3AB5782E1D6714B5
行政院環境保護署. (2020c). 環境檢驗品管分析執行指引. Retrieved from https://www.epa.gov.tw/DisplayFile.aspx?FileID=65C2FEE8420DED4E&P=a91335e2-370e-4177-a351-71d0d39ba813
每日頭條. (2020). 溶解氧傳感器的工作原理及基本概念. Retrieved from https://kknews.cc/zh-tw/news/knqlep8.html
林衍廷, & 張智華. (2020). 臺灣南部水庫水質監測點代表性檢討及以無人機輔助遠端取樣之研究.
研發互助社群. (2019). 防水型DS18b20溫度感測器測量原理. Retrieved from https://cocdig.com/docs/show-post-19271.html
楊善博, & 張智華. (2017). Integrating evolutionary optimization and ocean color semi-analytical model for mapping Secchi disk depth of inland water from high resolution multispectral satellite data.
瑞欣監視器. Retrieved from https://shopee.tw/product/5889933/238550624?v=4c3&smtt=0.0.5&fbclid=IwAR1iWXPhOa3xx74JjDFUkfwIBFdjCfbyCRHpGEPj4H9XPAQCWSoezn7B4jI
維基百科. (2020). 電導率. Retrieved from https://zh.wikipedia.org/wiki/%E7%94%B5%E5%AF%BC%E7%8E%87_(%E7%94%B5%E8%A7%A3%E8%B4%A8)
劉彥良. (2019). 微型氣體感測器之效能比對與校正方法建立之研究. (碩士). 國立交通大學, 新竹市. Retrieved from https://hdl.handle.net/11296/a3x89a
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2025-01-01起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2025-01-01起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw