The conventional method of measuring seed spacing effectively determines the seed distribution profile. However, it remains labor-intensive, time-consuming, costly, and inefficient. To address these limitations, this study proposes the development of a real-time seed control system aimed at improving the efficiency and accuracy of the seeding process by regulating seed distribution during planting. A mathematical model of the seeding process for inline seeders was established, integrating operational parameters of the seeder, including the effect of tractor speed. The effectiveness of the control system was evaluated using various performance indices: standard error (SE), coefficient of variation (CV), missing seed index (M), multiple seed index (D), and feed quality index (A). Experimental results showed a significant reduction in seed spacing variation, with an 11% decrease in the coefficient of variation (CV), a reduction of 0.9 in mean seed spacing, a decrease of 1.4 in the missing seed index (M), and a reduction of 0.8 in the multiple seed index (D). Additionally, the feed quality index (A) improved by 16%. Importantly, the system maintained consistent performance across varying tractor speeds, demonstrating its robustness and adaptability. The results show a good agreement between the distances measured in the field and those obtained by the sensors, with absolute errors ranging from 0.08 cm to 0.32 cm and relative errors between 3.16% and 6.12%. These results confirm the effectiveness of the system in improving seeding precision and uniformity, highlighting its potential to increase agricultural productivity and efficiency.