Issues in agricultural production intensify because of climate variations and diminishing resources together with an expanding global human count. Regular farming operations together with cloud-based farming solutions battle inefficiencies and high latency and suffer from limited connectivity when working in remote areas. This study puts forward flying-edge computing as an innovative UAV-based computing paradigm for enhanced smart agriculture by processing real-time data into decisions and collections. The proposed framework which unites UAVs and IoT technologies creates an efficient system for resource management while enhancing monitoring precision until it supports exact agricultural care in remote locations. Flying-edge computing removes network edge performance limitations because it calculates tasks on-site rather than through cloud or fog computing platforms while they depend on a stable Internet connection. The research evaluates UAV devices and conventional farming approaches through a thorough performance assessment which focuses on delays and data precision and processing speed together with system expansion capabilities. The research demonstrates how UAVs provide better solutions to instant agricultural issues thus leading farming toward data-oriented autonomous operations. This research adopts distributed flying-edge machines to initiate the next phase of precision agriculture which protects food systems from future operational threats.