AI‐enhanced soil management and smart farming. (30th October 2021)

• Record Type: Journal Article
• Authors: Chen, Qianyu; Li, Lanyu; Chong, Clive; Wang, Xiaonan
• Is Part Of: Soil use and management. Volume 38:Number 1(2022)
• Page Start: 7
• Page End: 13
• Publication Date: 2021-10-30
• Subjects: agriculture -- artificial intelligence -- machine learning -- multiponics vertical farming -- soil management; Soil management -- Periodicals; 631.4
• DOI: 10.1111/sum.12771
• Languages: English
• ISSNs: 0266-0032

Abstract

Abstract: Soil and crop management are facing challenges, in particular an increasing pressure to feed a growing population and improve food safety. Smart farming assists in dealing with these issues by incorporating information and communication technologies into farming practice. The Multiponics Vertical Farming (MVF) system is a very promising concept in smart farming that saves space, transportation cost and delivery time. Complicated systems and messy data can be processed by advanced technologies to achieve greater accuracy and efficiency in modelling and computing. For dynamic and complex problems, Artificial Intelligence (AI) provides rapid evaluation and aids in designing effective solutions. This study discusses how AI is adopted in soil management and MVF for tasks including classification, detection and forecasting. Three categories of AI and machine learning techniques, Support Vector Machine (SVM), Decision Tree (DT) and Neural Network (NN)‐based models, that are widely used will be presented. Future perspectives on urban farming are also discussed.