IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 426 10.51583/IJLTEMAS.2026.150900081 Autonomous Farming System Soilless Indoor Smart Farming: A Review of Developments and Emerging Technologies in Fuzzy based Self-Optimising Nutrient Management Moh T.S.Y. Electrical Engineering Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Tiong M.C. Electrical Engineering Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Ting A.C.H. Electrical Engineering Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Wong L.A. Electrical Engineering Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Ahmad M.A.A. Electrical Engineering Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Koh C.C. Food Technology Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia Hii S.L. Food Technology Programme School of Engineering & Technology, University of Technology Sarawak, Sibu, Sarawak, Malaysia Malaysia 15 9 2051 2074 27 09 2026 02 10 2026 14 10 2026 Autonomous Farming System Smart Farming Fuzzy Logic Control Nutrient Control Self Optimizing Control Abstract

Soilless indoor smart farming has emerged as a promising approach to controlled-environment agriculture, offering improved resource efficiency and year-round crop production. This review examines the development of intelligent nutrient management through the integration of Internet of Things (IoT) technologies, artificial intelligence, data analytics, and automated control systems in hydroponic cultivation. Particular emphasis is placed on self-optimising nutrient management, which enables nutrient delivery to adapt to changing crop requirements throughout different growth stages. The review highlights the transition from conventional fixed and manually adjusted nutrient strategies to closed-loop control systems that integrate continuous real time nutrient, environmental, and plant growth information back to the system for further regulation. Although intelligent technologies offer opportunities to reduce nutrient wastage and improve resource utilisation, the nonlinear and time varying nature of nutrient uptake and plant growth presents significant control challenges. The review further highlights the importance of growth aware control strategies that integrate plant indicators with nutrient and environmental sensing to support adaptive and autonomous soilless farming systems.

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