Browsing by Author "Bashandy, Abdalla Taha"

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    “IOT smart irrigation based machine learning system” A
    (MSA, 2022) Bashandy, Abdalla Taha
    Smart Agricultural Systems have advanced rapidly in recent decades. Demonstrate the importance of agriculture over the world. Irrigation systems in the past relied on mills to water the land using traditional ways without knowing the proper quantities of these crops. These outdated systems are a major source of water waste, resulting in the destruction of some crops due to a lack of sufficient water. However, recent technology advancements have resulted in unique irrigation systems that do not require the farmer to intervene in the irrigation process. Smart systems have demonstrated their ability to regulate crop irrigation. It also assists to reduce irrigation water waste. Furthermore, it will try to reduce the number of staff, resulting in cost savings. In this study, we attempt to address irrigation issues such as farmer errors and excessive water consumption. These inaccuracies have an impact on trees, and their fungus may have an impact on the whole water supply. The project's expected outcomes are to make the irrigation system easier to use and understand by constructing and developing the entire automatic irrigation system, as well as to improve crop production by decreasing overwatering from saturated soil. It can prevent irrigation on the wrong day, to switch engine ON or OFF by using the irrigation system, the controller will operate to switch the engine, so no need for employers, to reduce operational errors caused by employees as much as possible, and to conserve water from waste.