Smart Farming Evolution: Integrating AI Precision Agriculture for Advanced Weed Management

Abstract

Muhammad Awais Arshad, Muhammad Huzaifa Mahmood, Muhammad Waseem Ishaq, Muhammad Usman Hayat, Saba Khan, Farwah Murtaza, Muhammad Umar, Babur Ali Akbar and Muhammad Jamshaid

The transformation from traditional farming to smart agriculture has been marked by significant advancements in precision agriculture weed management technologies. This review explores the historical development from Agriculture 1.0, characterized by manual labor rudimentary tools, to Agriculture 4.0, which integrates advanced technologies like artificial intelligence, remote sensing, robotics. Early agricultural eras saw the introduction of basic machinery tools, significantly reducing labor increasing productivity. The advent of Agriculture 3.0 brought communication technologies, software engineering, the Internet of Things (IoT), which further enhanced agricultural capabilities. The review highlights the critical role of precision agriculture in addressing global challenges such as food security sustainable farming practices. It discusses the economic environmental impacts of weeds, which significantly affect crop yields contribute to substantial financial losses worldwide. Various weed management strategies, including chemical, mechanical, biological methods, are evaluated. The paper emphasizes the shift towards eco-friendly non-conventional weed management practices to combat issues like herbicide resistance environmental pollution. Innovative technologies such as patch spot spraying, which utilize georeferenced weed maps real-time image analysis, are explored for their efficiency in reducing herbicide usage environmental impact. The integration of precision systems on tractors, utilizing sensors like RGB-cameras, multispectral cameras, LIDAR, demonstrates significant advancements in detecting managing weeds. Furthermore, the review addresses the role of unmanned aerial vehicles (UAVs) remote sensing in precision weed management, highlighting their potential to enhance monitoring application efficiency. The review concludes with a discussion on the future of weed management in precision agriculture, focusing on the importance of continuous innovation the development of sustainable practices to meet the growing global food demand.

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