Apples are one of the most important fruits worldwide, supporting millions of livelihoods and economies around the globe. However, apple orchards face critical challenges from diseases such as apple scab, fire blight, and powdery mildew, which significantly reduce fruit quality and yield. Farmers traditionally rely on widespread applications of pesticides across entire fields, which is costly, labor-intensive, and environmentally harmful. This project develops a new approach that combines drones (unmanned aerial vehicles, UAVs) and ground robots (unmanned ground vehicles, UGVs) with smart sensors and artificial intelligence (AI) to detect and treat diseases only where needed, using precise amounts of pesticides. The system aims to help farmers reduce chemical use, save labor, and improve economic longevity by identifying early signs of disease and applying treatments in a precise, targeted manner. By working with apple growers in diverse locations, the project also ensures that the technology is practical and accessible for real-world farming. This platform also supports workforce development educational and training activities in robotics and AI. This project addresses the critical challenge of efficiently detecting and controlling diseases in apple orchards, such as apple scab, fire blight, and powdery mildew, which significantly impact crop health and productivity. The research aims to develop a novel, integrated robotic platform combining UAVs and UGVs with advanced se