AI-Powered Multi-Purpose Agricultural UAV for Precision Farming, Smart Crop Protection, and Real-Time Monitoring: A Comprehensive Review

Abstract: Agriculture is undergoing a major transformation with the adoption of intelligent technologies such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), remote sensing, and Unmanned Aerial Vehicles (UAVs). Traditional farming methods often require excessive labor, large quantities of pesticides, and continuous field monitoring, making agricultural operations time-consuming and inefficient. Precision agriculture has emerged as a modern solution to improve productivity, optimize resource utilization, and support sustainable farming practices [1], [3]. Among the various smart farming technologies, UAVs or agricultural drones have gained significant importance because of their capability to perform autonomous monitoring, crop analysis, precision spraying, and land surveying operations [12], [13].

This review paper presents a comprehensive study of an AI-powered multi-purpose agricultural UAV capable of performing fertilizer and pesticide spraying, crop health monitoring using AI-based image processing, fire detection and extinguishing, land surveying and GIS mapping, and animal/human detection for crop protection. The paper reviews recent advancements in UAV remote sensing technologies, multispectral and hyperspectral imaging systems, deep learning architectures, precision spraying mechanisms, and autonomous navigation systems used in precision agriculture [2], [21], [26].

Deep learning models such as Convolutional Neural Networks (CNNs), YOLO-based object detectors, Faster R-CNN, and Vision Transformers have significantly improved crop disease detection, object recognition, and aerial image analysis [18], [23], [27]. Remote sensing technologies including RGB imaging, thermal imaging, multispectral sensing, hyperspectral sensing, and LiDAR enable accurate vegetation monitoring, disease diagnosis, and terrain mapping [4], [24], [25]. Precision spraying systems integrated with AI-assisted decision-making improve spraying efficiency and reduce pesticide wastage [14], [29].

The review concludes that AI-powered multi-purpose agricultural UAVs provide an intelligent, efficient, and sustainable solution for next-generation smart farming applications. Continuous advancements in AI, sensor technologies, and autonomous UAV systems are expected to further revolutionize modern agriculture [13], [35].

Keywords: Precision Agriculture, UAV, Agricultural Drone, Artificial Intelligence, Machine Learning, Deep Learning, Remote Sensing, Smart Farming, Crop Disease Detection, YOLO, CNN, GIS, Precision Spraying.