- 學位論文
應用於網紋洋香瓜設施之智慧節水灌溉及施肥物聯網系統
Smart water-saving irrigation and fertilization IoT system applied to reticulated cantaloupe facilities
摘要
學號：M11144002 論文名稱：應用於網紋洋香瓜設施之智慧節水灌溉及施肥物聯網系統 總頁數：67 學校名稱：國立屏東科技大學 畢業時間：2024年07月 研究生：韋慶介 學位別：碩士學位 系別：生物機電工程系研究所 指導教授：苗志銘 論文摘要： 本研究主要在研究網紋洋香瓜智慧灌溉物聯網系統的開發與應用。隨著農業智慧化的發展，物聯網技術被廣泛應用於農業生產中，以提高農作物的生產效率和品質。網紋洋香瓜為台灣重要的經濟作物之一，其生長每一階段過程中對水分的需求十分敏感。本研究設計了一套含物聯網技術的智慧灌溉系統，以解決網紋洋香瓜的灌溉管理問題。系統中包括感測器、數據收集、分析和控制模組，能夠即時監測土壤濕度、氣溫、光積量等環境參數，並根據深度學習之長短記憶網路(LSTM)法及光積值建立灌溉模型，以智慧灌溉策略進行智慧化調節水量。結果顯示，該智慧灌溉系統能夠有效地提高網紋洋香瓜生長效率，減少水資源的浪費，提高作物品質和產量。同時，該系統具有良好的可擴展性和穩定性，能夠應對不同規模農場的需求。本研究提出的網紋洋香瓜智慧灌溉物聯網系統，證明可較一般溫室種植方法節水25%，慣行農業方法更可達節水70%，肥料利用率可達9成，對於推動農業智慧化和可持續發展有相當大的效益。 關鍵字:物聯網(IOT)、深度學習(Deep Learning)、網紋洋香瓜(Cucumis melo L.)、光積值(Daily light integral, DLI)、長短記憶網路(LSTM)
並列摘要
Abstract Student ID: M11144002 Thesis Title: Smart water-saving irrigation and fertilization IoT system applied to reticulated cantaloupe facilities Total Pages: 67 Name of Institute：National Pingtung University of Science and Technology Name of Department：Department of Biomechatronics Engineering Date of Graduation： July 2024 Degree Conferred：Master Name of Student：Ching-Chieh Wei Advisor: Jr-Ming Miao The Contents of Abstract in this Thesis： This study mainly studies the development and application of the Internet of Things system for smart irrigation of reticulated cantaloupe. With the development of agricultural intelligence, IoT technology is widely used in agricultural production to improve the production efficiency and quality of crops. The cantaloupe is one of Taiwan's important economic crops and is very sensitive to water requirements at each stage of its growth. This study designed a smart irrigation system containing Internet of Things technology to solve the irrigation management problem of reticulated cantaloupe. The system includes sensors, data collection, analysis and control modules, which can real-time monitor environmental parameters such as soil moisture, temperature, and light accumulation, and establish irrigation based on the deep learning long short memory network (LSTM) method and light accumulation value. Model to intelligently regulate water volume using smart irrigation strategies. The results show that the smart irrigation system can effectively improve the growth efficiency of reticulated cantaloupe, reduce the waste of water resources, and improve crop quality and yield. At the same time, the system has good scalability and stability and can cope with the needs of farms of different sizes. The reticulated cantaloupe smart irrigation IoT system proposed in this study proves that it can save 25% of water compared with the general greenhouse planting method, and the conventional agricultural method can save 70% of water, and the fertilizer utilization rate can reach 90%, which is very important for promoting agriculture. Intelligent and sustainable development have considerable benefits. Keywords: Internet of Things (IOT), deep learning (Deep Learning), Cucumis melo L., daily light integral (DLI), long and short memory network (LSTM)