With the rapid rise of low-altitude economy, the food logistics by Unmanned Aerial Vehicles (UAVs) has shown broad prospects for development, and national and local governments have provided strong policy guarantees for delivery by UAVs. The work aims to provide technical reference for cultivating new growth of low-altitude economy. By integrating advanced sensors and machine learning algorithms, the food logistics by UAVs could monitor the changes of various parameters and surrounding environment in flight in real time to ensure safety and reliability. The focus was placed on the application of machine learning algorithm and sensor monitoring data fusion technology. By deeply integrating these two technologies, the UAVs would be able to perceive food quality more comprehensively, make intelligent decisions, optimize flight routes, and cope with emergencies. The data fusion of machine learning and sensor monitoring significantly improves the delivery efficiency of UAVs, reduces the cost, and provides more consumers with convenient delivery services that are not restricted by ground traffic.