Transforming Greenhouse Horticulture Using Artificial Intelligence and Digital Twin

温室 农业工程 工程类 业务 农业科学 生物技术 计算机科学 园艺 环境科学 生物
作者
Kapil Joshi,Ashulekha Gupta,Amar Jeet Rawat,Rajiv Kumar,Omdeep Gupta
标识
DOI:10.1109/iq-cchess56596.2023.10391310
摘要

In todays, to cope with the problems caused by the rising worldwide need for basic foodstuffs, it is vital to discover ecologically friendly solutions. Vegetable crops may be grown all year long, regardless of the climate or season, thanks to horticulture. The production process for horticulture may be categorized as an unstructured & extremely complicated system that is influenced by the climate, environment, pests, disease, herbicides, nutrients, pricing, & combinations of these numerous aspects. Digital twins might be seen as the beginning of a new era in data-driven & intelligent greenhouse horticulture. The study of the article is about the advancement of horticulture via the application of reducing technologies, especially digital technology. The purpose of this article is to offer, with the need for technology, the vital information that producers may utilize to harvest a range of crops to reap the most rewards. This study describes the outcomes of structured use of the Digital Twin application throughout greenhouse horticulture, as Artificial Intelligence applies to learn approaches throughout its applications to proclaim the best cost-effective & maximal benefit for the agriculturist. Based on the analysis, the article identifies challenges and suggests a few vital recommendations for future work. The findings of this study on the efficiency of concept in the growth of concentrated fruits and vegetables are examined.
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