A Narrative Review on Smart Sensors and IoT Solutions for Sustainable Agriculture and Aquaculture Practices

Liwei Liu, Winton Cheng and Hsin-Wei Kuo ()
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Liwei Liu: Exhibition Division, National Science and Technology Museum, Kaohsiung 807412, Taiwan
Winton Cheng: Department of Aquaculture, National Pingtung University of Science and Technology, Pingtung 912301, Taiwan
Hsin-Wei Kuo: Department of Aquaculture, National Pingtung University of Science and Technology, Pingtung 912301, Taiwan

Sustainability, 2025, vol. 17, issue 12, 1-36

Abstract: The integration of smart sensor networks and Internet of Things (IoT) technologies has emerged as a key strategy for enhancing productivity and sustainability in agriculture and aquaculture under increasing climate and resource pressures. This review consolidates empirical findings on the performance of sensor-driven systems in optimizing the management of water, nutrients, and energy. Studies have demonstrated that IoT-based irrigation systems can reduce water use by up to 50% without compromising yields, while precision nutrient monitoring enables a 20–40% reduction in fertilizer inputs. In aquaculture, real-time monitoring and automated interventions have improved feed conversion ratios, reduced mortality by up to 40%, and increased yields by 15–50%. The integration of artificial intelligence (AI) into IoT frameworks further enhances predictive capabilities and operational responsiveness. Despite these benefits, widespread adoption remains constrained by high infrastructure costs, limited sensor robustness, and fragmented policy support. This paper provides a comprehensive evaluation of current technologies, adoption barriers, and strategic directions for advancing scalable, sustainable, and data-driven food production systems.

Keywords: climate resilience; technology adoption; digital transformation; precision monitoring; smart farming; artificial intelligence (AI); environmental stewardship; farm management; edge computing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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