Unveiling the potential of sustainable agriculture: A comprehensive survey on the advancement of AI and sensory data for smart greenhouses

被引:0
作者
Al-Qudah, Rabia [1 ]
Almuhajri, Mrouj [2 ]
Suen, Ching Y. [3 ]
机构
[1] Abu Dhabi Univ, Coll Engn, Abu Dhabi, U Arab Emirates
[2] Saudi Elect Univ, Comp & Informat Coll, Riyadh, Saudi Arabia
[3] Concordia Univ, CENPARMI, Comp Sci & Software Engn, Montreal, PQ, Canada
关键词
Smart greenhouse; Climate control; Artificial intelligence; Sensory data; Internet of Things; MONITORING-SYSTEM; IOT; MANAGEMENT; FRAMEWORK; DESIGN;
D O I
10.1016/j.compag.2024.109721
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The intersection of Artificial Intelligence (AI) and the Internet of Things (IoT) has propelled the agricultural industry into a new era of efficiency and sustainability. Among the diverse applications of AI and IoT in agriculture, Smart Greenhouses (SGHs) are particularly notable for their transformative potential in revolutionizing crop cultivation practices. Moreover, the adoption of SGH technologies has significant implications for agricultural sustainability and environmental conservation. By minimizing resource waste and reducing reliance on chemical inputs, SGHs mitigate the environmental impact of traditional farming practices. The aim of this comprehensive survey is evaluating the state-of-the-art literature on SGH development using AI and sensory data. In addition, this survey is one of the first to bridge the gap between academic research and industrial applications of AI-powered SGHs, offering a holistic view of the field's progress and future prospects. This work also critically examines the technical level of the surveyed works and their alignment with the current AI trends. This comprehensive survey follows a well-defined review protocol and inclusion criteria. A total of 88 studies, industrial projects, related datasets from different research sources, namely, IEEE, SpringerLink and Science Direct were included in the review. The survey critically assesses both academic and industrial SGH projects, identifying key research gaps and the lag in adopting recent AI innovations.
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页数:25
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