The increasing water demands in irrigation highlight the necessity for a smart irrigation system capable of conserving approximately 80% of water usage. This study presents a model which optimizes the water usage averaging 3 to 4 liters per day, saving approximately 66% of water per day by automating the irrigation process, thereby reducing the need for continuous supervision. The system enhances water conservation by adjusting water delivery to plants and gardens based on their specific needs, making it suitable for agricultural fields, lawns, and parks. In addition to addressing seasonal crop demand, power availability is also crucial. Using batteries in PV systems increases costs, requires storage space, and raises environmental concerns. The proposed solution utilizes a hybrid model of maximum power point tracking (MPPT) approach, combining perturb and observe (P & O) with ANN algorithms, to enhance the energy extracted from a stand-alone PV panel up to 95%. This method optimizes the performance of the water pump and control circuitry, ensuring maximum energy utilization. A simulation model of the system was implemented to determine the most economically optimal design.