Smart Irrigation: Enhancing Agricultural Efficiency with IoT-Connected Drones and Machine Learning

Water conservation and sustainable farming in agriculture depend heavily on effective irrigation. Water waste and less-than-ideal crop yields result from traditional irrigation systems’ reliance on set schedules and crude sensor-based techniques, which make them frequently inaccurate and unable to adjust to shifting crop and soil conditions. The study proposes a sophisticated system that combines Internet of Things-connected drones for accurate irrigation and real-time monitoring. IoT sensors send data to a central system that uses machine learning algorithms for dynamic irrigation planning, tracking soil moisture and environmental conditions continually. These plans are carried out by drones fitted with thermal and multispectral cameras, guaranteeing targeted water distribution. The results show notable improvements: operational expenses were reduced by 20%, crop yields increased by up to 20%, and water use efficiency increased by 20%. The novel strategy improves agricultural productivity and sustainability while simultaneously addressing the shortcomings of existing systems.