Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/550596
Title: Novel Approaches for IoT Based Irrigation of Arable Land Using Machine Learning
Researcher: Pandey Prabhat (19ENG7ECE0013)
Guide(s): Agrawal Sudhir
Keywords: Engineering
Engineering and Technology
Engineering Electrical and Electronic
University: SAGE University, Indore
Completed Date: 2024
Abstract: How the technology is positively affecting our day to day life. These technologies are newlineenhancing our lifestyle and solve our day to day the complexities. The technology is newlinealso assisting us in various real world tasks such as farming. The farming is a complex newlineset of processes and how the technology and computational methods can help in newlinedecision making and their improvement is considered in this work. There are two key newlineobjectives are considered before initiation of the proposed work: newline(1) Develop a low cost method for automating the crop irrigation process. newline(2) Preserve the water for our future sustainability and better crop production. newlineInvestigation of the recently developed techniques for smart irrigation system and newlineplanning. The main focus of the review is to recover ML algorithms, sensors, IoT newlinedevices, datasets, and features. These facts may provide a road map to design and newlinedevelop a fully automated water irrigation system. newlineIntroduce a simulation model by using the ML algorithm and IoT technology to make newlineautomated irrigation system. This approach utilizes the sensor placement technique to newlinereduce the deployment cost, and also utilize the basic sensors to reduce the installation newlineand maintenance cost. In addition, the model is simulated on real wheat crop newlineadditionally the amount of possible water preservation has been investigated and newlinereported. newlineThis phase provide an improved irrigation system by extending the previously newlineintroduced model by incorporating the weather conditions in irrigation system newlineautomation. The weather conditions are highly influencing the soil moisture and newlinetemperature thus the crop water demand is also influencing with weather. Therefore, a newlinenew algorithm has been proposed for incorporating the weather conditions and sensor newlinereadings to accurately predict the possible water treatment plan for the given crop. newlineThe model is a general model and can be specified by tuning the internal system newlineparameters for incorporating the solution for a specific crop. newlineThe simulations has been implemented on python te
Pagination: 
URI: http://hdl.handle.net/10603/550596
Appears in Departments:Faculty of Engineering & Technology

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01_title.pdfAttached File291.08 kBAdobe PDFView/Open
02_prelim pages.pdf2.74 MBAdobe PDFView/Open
03_content.pdf419.12 kBAdobe PDFView/Open
04_abstract.pdf356.97 kBAdobe PDFView/Open
05_chapter 1.pdf612.57 kBAdobe PDFView/Open
06_chapter 2.pdf464.07 kBAdobe PDFView/Open
07_chapter 3.pdf880.87 kBAdobe PDFView/Open
08_chapter 4.pdf697.46 kBAdobe PDFView/Open
09_chapter 5.pdf1.83 MBAdobe PDFView/Open
10_annexures.pdf2.75 MBAdobe PDFView/Open
80_recommendation.pdf291.04 kBAdobe PDFView/Open
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