Citation

Razak, Siti Fatimah Abdul and Yogarayan, Sumendra and Lim, Ke Yin and Ismail, Sharifah Noor Masidayu Sayed and Ullah, Arif (2025) Revolutionising Agriculture with AI. The Smart Life Revolution. pp. 64-82. ISSN 9781003509196

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Abstract

Farming practices are no longer the same with the adoption of artificial intelligence (AI) and smart agriculture. The increasing trend of AI adoption in agriculture practices which are coupled with advanced technologies has innovated traditional practices with the aims of enhancing productivity, securing food supplies and environment sustainability. The introduction of digital twins offers a comprehensive platform to monitor the actual farm and its related entities. A digital twin is essentially a virtual representation of a physical system, constantly updated with real-time data to mirror its real-world counterpart. It integrates data sources from in-field sensing devices, weather or climate patterns, machine performance, harvesting records, soil conditions, etc. The integration of data into a single system provides opportunities for better analytics. By utilising AI techniques and approaches, the quality of the analytics can be enhanced further. This chapter presents the potential of AI-powered digital twins in agriculture by focusing on the architecture, benefits and challenges. The real-time feedback from the virtual system shall empower farmers to make data-driven decisions for the actual farming needs such as crop management, irrigation scheduling, weed or pest control and resource allocation, ultimately leading to improved yields, resource efficiency and sustainability.

Item Type:	Article
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD1401-2210 Agriculture
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	30 Jun 2025 08:28
Last Modified:	30 Jun 2025 08:28
URII:	http://shdl.mmu.edu.my/id/eprint/14184

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