TRANSFORMING AGRICULTURE THROUGH ARTIFICIAL INTELLIGENCE: A TECHNICAL ANALYSIS
Keywords:
Agricultural Artificial Intelligence, Precision Farming, Smart Agriculture, Agricultural Robotics, Sustainable AgricultureAbstract
The integration of Artificial Intelligence in agriculture represents a transformative advancement in farming practices, offering unprecedented opportunities for optimization and sustainable food production. This technical article examines the implementation of AI technologies across the agricultural sector, encompassing machine learning systems, computer vision applications, IoT infrastructure, and robotics automation. The article investigates the technical architecture, integration methodologies, and real-world case studies from both large-scale and small-holder farming operations. Through comprehensive examination of implementation challenges, emerging technologies, and socioeconomic impacts, this article demonstrates how AI adoption is revolutionizing traditional farming practices while addressing critical issues of resource efficiency, environmental sustainability, and farm productivity. The article highlights the importance of accessible solutions for small-scale farmers and emphasizes the need for culturally contextualized implementation strategies to ensure widespread adoption and sustainable agricultural development.
References
Grand View Research "Artificial Intelligence In Agriculture Market Size, Share & Trends Analysis Report By Component (Hardware, Software, Service), By Technology, By Application, By Region, And Segment Forecasts, 2024 - 2030," Grand View Research.com. [Online]. Available: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-in-agriculture-market
Tanha Talaviya et al., "Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides," Artificial Intelligence in Agriculture. Volume 4, Pages 58-73, 2020. https://www.sciencedirect.com/science/article/pii/S258972172030012X
Pallab Bharman et al., "Deep Learning in Agriculture: A Review," Asian Journal of Computer Science And Information Technology 13(2):28-47, 2022. [Online]. Available: https://www.researchgate.net/publication/359243072_Deep_Learning_in_Agriculture_A_Review#:~:text=DL%20has%20been%20applied%20to,weed%20detection%2C%20and%20disease%20detection.
Ten Seng Teik et al., "Advancements in Agricultural Robotics and Automation in MARDI," vol. 99, 2024. [Online]. Available: https://www.researchgate.net/profile/Badaruzzaman-Mohamad-Noh-2/publication/385560776_Ingenieur_Vol_99_final_July-Sept_2024/links/672ae4e677b63d1220dcf5b7/Ingenieur-Vol-99-final-July-Sept-2024.pdf?origin=scientificContributions
Alok Mishra et al., "Quality attributes of software architecture in IoT-based agricultural systems," Smart Agricultural Technology, Volume 8, 100523, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S277237552400128X
Anis Ur Rehman et al., "Smart agriculture technology: An integrated framework of renewable energy resources, IoT-based energy management, and precision robotics," Cleaner Energy Systems, Volume 9, 100132, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2772783124000268
T. A. Manga, "An Examination of the Implementation of Artificial Intelligence in Agricultural Extension of Developing Nations: A Comprehensive Analysis," 2024. [Online]. Available: https://www.researchgate.net/publication/381112282_An_Examination_of_the_Implementation_of_Artificial_Intelligence_in_Agricultural_Extension_of_Developing_Nations_A_Comprehensive_Analysis
Mrutyunjay Padhiary et al., "Enhancing precision agriculture: A comprehensive review of machine learning and AI vision applications in all-terrain vehicle for farm automation," Smart Agricultural Technology, Volume 8, 100483. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2772375524000881#:~:text=AI%20vision%20systems%20are%20being,efficient%20(20%2D25%25).
H Mary Henrietta, "Artificial Intelligence in Agriculture: A Review of Current Applications and Future Trends," In book: Futuristic Trends in Agriculture Engineering & Food Sciences (pp.1-5)Publisher: IIP Series, 2024. [Online]. Available: https://www.researchgate.net/publication/379838184_ARTIFICIAL_INTELLIGENCE_IN_AGRICULTURE_A_REVIEW_OF_CURRENT_APPLICATIONS_AND_FUTURE_TRENDS
Chrysanthos Maraveas et al., "Harnessing quantum computing for smart agriculture: Empowering sustainable crop management and yield optimization," Computers and Electronics in Agriculture, Volume 218, March 2024, 108680, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0168169924000711
Mark Ryan, "The social and ethical impacts of artificial intelligence in agriculture: mapping the agricultural AI literature," AI & SOCIETY 38(6):3, 2022. [Online]. Available: https://www.researchgate.net/publication/357538787_The_social_and_ethical_impacts_of_artificial_intelligence_in_agriculture_mapping_the_agricultural_AI_literature
A.A. Mana et al., "Sustainable AI-based production agriculture: Exploring AI applications and implications in agricultural practices," Smart Agricultural Technology Volume 7, 100416, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2772375524000212
