This study presents the design and implementation of a Computer Numerical Control (CNC)-based automated tracking and irrigation system aimed at enhancing agricultural sustainability. The system integrates a two-axis (X-Y) CNC platform with environmental sensors to monitor soil moisture and plant health, enabling precise, targeted irrigation. Three optimized trajectories N-pattern, vertical straight-line pattern and flipped L-pattern were developed to dynamically adapt to soil moisture data, balancing comprehensive coverage, operational efficiency (±0.08 cm repeatability for vertical pattern), and water conservation (40% savings for flipped L-pattern). A lead screw mechanism ensures high positional accuracy (±0.2 cm) and repeatability (<0.1 cm), while minimizing water waste. Field tests demonstrated the system’s effectiveness in identifying and irrigating water-deficient plants, with soil moisture sensors showing a mean error of ±2% compared to manual readings. This approach offers significant potential for resource-efficient agriculture, particularly in arid regions like Bahrain, by reducing labor and optimizing water usage through adaptive trajectory selection. Future work will focus on enhancing adaptive control for improved trajectory tracking and water management.