Drones in precision agriculture

This chapter addresses the synergy of drone-based aerial imaging and real-time data analytics for precision agriculture with a view to its revolutionary power in sustainable agriculture. With thermal, multispectral, and Red – Green – Blue imagery, drones record useful information that adds value to crop health, water stress, and the growth of pest or disease monitoring. Through machine learning models and vegetation indices such as normalized difference vegetation index (NDVI), the system enables early diagnosis and efficient decision-making. Through a close reading of the literature and comparison with conventional agriculture, it is clear that drone technology improves the accuracy of yield prediction and reduces the application of pesticides and irrigation expenditure. The solution involves a hybrid analytics platform based on convolutional neural networks, edge computing, and multiple regression models to deliver decision-ready data. Empirical results for various case studies of maize, rice, and wheat farms indicate enormous growth in crop yields and cost reductions. The chapter concludes that drones, integrated with smart analytics, are a scalable, eco-friendly, and inexpensive solution for agriculture in the future. The future potential involves growing-edge artificial intelligence (AI) capabilities, enhanced interoperability with Internet of Things (IoT) devices, and building autonomous swarms for large-scale deployment.