Agriculture serves as a fundamental pillar of Nigeria's economy. A significant portion of the available freshwater resources is allocated to agricultural activities. In Northern Nigeria, irrigation systems are essential. Over the years, farming practices have remained largely primitive, particularly in sub-Saharan Africa. This situation arises from a lack of advanced technological knowledge that could enhance agricultural practices. Various challenges hinder agricultural practices, including reliance on traditional farming methods, limited understanding of concepts and practices, policy issues, environmental concerns, and financial constraints. The purpose of this study was to optimize an IoT-based model for smart agriculture and irrigation water management. The study aimed to design, implement, test, and evaluate the performance of this optimized IoT-based model. The proposed system utilized the prototyping model as its methodology. The design was created using the Balsamiq application. The system is intended to feature a login page, a dashboard, a system use case diagram, an actuators page, a sensor page, and an application interface design. The Justinmind tool was employed to illustrate the flow of information within the system, encompassing data input and output, data storage, and all subprocesses through which the data traverses. The optimized IoT model was developed using four primary platforms: the ReactJS frontend application development platform, Amazon Web Services IoT Core for the backend, the Arduino development platform for sensor node creation, and the Python programming language for the actuator node based on the Raspberry Pi board. When compared to existing systems using the specified parameters, the optimized model demonstrates superior performance, particularly in terms of measurement accuracy, irrigation water management, operational modes, platform accessibility, real-time video capabilities, user-friendliness, and overall efficiency. The perform