Application of AI-Based Enabling UAV Sensing System in Precision Agriculture

This paper mainly introduces the application of AI-enabled UAV sensing system in precision agriculture. The drone sensing system realizes real-time monitoring of crop status, pests and diseases, and land conditions through sensors and cameras installed on the drone. The application of AI technology in UAV perception system mainly includes image processing and recognition, navigation and positioning, and decision and support. These technologies enable drones to acquire farmland data efficiently and accurately, providing strong support for precision agriculture <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</sup>. The project experiments use drones equipped with different sensors to collect data in different crop planting areas. In the process of UAV flight, the crop data is collected by sensors, including image data, spectral data, height data, etc. Preprocessing the collected data, including data cleaning, format conversion, and removal of outliers, to ensure the accuracy and reliability of the data; AI algorithms are used to analyze and identify the data and extract useful information, such as crop growth conditions, diseases and pests. Through field testing and data collection, we conducted an in-depth analysis of the application effects of AI -based enabled drone perception systems in precision agriculture. The experiments show that: in terms of crop recognition, the AI-enabled UAV perception system shows remarkable recognition ability; In terms of pest detection, AI-enabled drone sensing systems have also shown strong capabilities<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</sup>. Ai-based enabled UAV perception system has significant advantages in precision agriculture. In future research, we need to further optimize algorithms, improve equipment performance, and strengthen data collection and processing capabilities to overcome these limitations and challenges, and promote the wide application of AI-based UAV perception system in precision agriculture.