Title : UAV-integrated aerial intelligence for smart agriculture
Abstract:
The purpose of this study is to identify the benefits of aerial intelligence for increasing yields. This developing system aims to enhance the crop yield and to transform the traditional approach into a real-time data-driven approach which also gives support to a sustainable system. It explores the aerial intelligence roles in smart agriculture sector and identifies the key antecedents that influences the crop productivity. The research uses a systematic literature review approach for reviewing and analyzing the relevant literature on the UAV integrated Aerial Intelligence for smart agriculture from the Scopus database. The study findings explore that UAV-integrated aerial intelligence significantly enhances crop yield estimation, disease detection, and efficient resources. UAV imagery is applied with neural network models (e.g., YOLOv8, CNNs, U-Net) which gives more precise prediction and detection. The study identifies key antecedents like task-specific UAV and sensor selection, real-time analytics, swarm-based monitoring, and integration into decision-support systems. A comparative analysis confirms UAVs outperform traditional platforms with respect to various parameters like flexibility, accuracy, cost-efficiency, and real-time data delivery. The research is limited to Open-access, English-language, published literature between the years from 2022 to 2025 from only the Scopus database. The study has proposed framework of UAVs-integrated aerial intelligence in smart agriculture for sustainability goals. It’s aligned with the UN-SDGs (2,12,13) and addressing the real-world agricultural problems like resource optimization, enhancing yields, climate adaptability. Study provide insights to researchers, stakeholders, and policymakers aims to promote the smarting the agriculture sector.
Keywords: UAV (Unmanned Aerial Vehicle), Aerial Intelligence, Smart Agriculture, Drones, Sustainability Development Goals
