Evaluating the impact of real-time NPK sensor integration on crop productivity insmart farming systems

This research examines the impact of integrating real-time NPK (Nitrogen, Phosphorus, Potassium) sensors within smart farming systems on crop productivity. A model-based approach was employed to design and implement a precision nutrient management system that combines sensor data acquisition, cloud analytics, and algorithm-driven decision-making for fertilizer application. The objective was to optimize nutrient delivery based on current soil conditions, crop type, and growth stage. Field experiments were conducted with wheat crops across two controlled plots: one managed using conventional methods and the other utilizing the proposed sensor-based system. The results emphasize that sensor-integrated precision farming significantly enhances input efficiency, minimizes environmental impact, and boosts economic returns. These findings support the broader adoption of NPK sensor technology in smart agriculture. Recommendations are made for integrating such systems into scalable agricultural models, particularly in regions experiencing high input costs or facing environmental sustainability challenges.