Leveraging IoT Technology to Revolutionize Irrigation Practices

Abstract: Agriculture is essential for the economic and social development of any nation. Water is a critical input in agriculture, and its efficient use is essential for sustainable agriculture. Underwatering can reduce crop yields and lead to plant mortality, while overwatering can waste water and cause root diseases. Therefore, it is important to irrigate crops optimally to maximize their output. This research proposes an automated irrigation system based on the Internet of Things (IoT) and machine learning. The system consists of three phases: (1) hardware assembly, including the installation of circuits and sensors; (2) software development; and (3) system testing. The proposed system has several advantages over traditional irrigation systems. First, it is automated, which reduces the need for manual labor. Second, it uses sensors to collect data on soil moisture and other environmental factors, which allows the system to irrigate crops more precisely. Third, the system uses machine learning to predict irrigation needs, which further improves irrigation efficiency. The proposed system has the potential to revolutionize irrigation practices and contribute to sustainable agriculture.

Keywords: IoT, KNN, SVM