review · International Journal of Advanced Computer Science and Applications
Emerging technologies such as artificial intelligence, cloud computing, and the Internet of Things offer significant potential when paired with unmanned aerial vehicles in precision agriculture. These aerial platforms enable real-time collection of high-resolution crop imagery, supporting quicker decisions, reduced operational expenses, and higher agricultural yields. However, the adoption of these aerial tools is constrained by hurdles in technology selection and field deployment, especially regarding data acquisition and image processing. Because the use of these systems in farming remains relatively new, clear and standardised operational workflows are lacking. A comprehensive review examines recent agricultural deployments, exploring vehicle categories, collection techniques, and image processing approaches. Evaluating the specific benefits and constraints of each tool aims to assist in the establishment of standard workflows, thereby easing the broader integration and practical adoption of aerial technologies across agricultural operations.
Modern agriculture requires precise management to boost food production while controlling expenses. Combining aerial imagery with digital tools allows farmers to monitor crops accurately and intervene where necessary. Clarifying the capabilities and limits of different drone technologies helps overcome practical bottlenecks, smoothing the transition towards reliable, standardised, and data-driven farming methods.
The findings could inform technology developers, agricultural service providers, and farm operators seeking to choose suitable drone hardware and imaging software. Because this work is an analytical review rather than a tested product, it sits at an early informational stage. It supports commercialisation by highlighting technical limits and laying groundwork for standardised operational workflows, which are necessary before precision farming tools can achieve widespread market adoption.
AI-generated from the published abstract. Always read the original work before citing.
On one hand, the emergence of cutting-edge technologies like AI, Cloud Computing, and IoT holds immense potential in Smart Farming and Precision Agriculture. These technologies enable real-time data collection, including high-resolution crop imagery, using Unmanned Aerial Vehicles (UAVs). Leveraging these advancements can revolutionize agriculture by facilitating faster decision-making, cost reduction, and increased yields. Such progress aligns with precision agriculture principles, optimizing practices for the right locations, times, and quantities. On the other hand, integrating UAVs in Smart Farming faces obstacles related to technology selection and deployment, particularly in data acquisition and image processing. The relative novelty of UAV utilization in Precision Agriculture contributes to the lack of standardized workflows. Consequently, the widespread adoption and implementation of UAV technologies in farming practices are hindered. This paper addresses these challenges by conducting a comprehensive review of recent UAV applications in Precision Agriculture. It explores common applications, UAV types, data acquisition techniques, and image processing methods to provide a clear understanding of each technology’s advantages and limitations. By gaining insights into the advantages and challenges associated with UAV-based applications in Precision Agriculture, this study aims to contribute to the development of standardized workflows and improve the adoption of UAV technologies.
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DOI: 10.14569/ijacsa.2023.01406123
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