|Title:||Design of an Artificial Intelligence of Things Based Indoor Planting Model for Mentha Spicata||Authors:||Ku, Hao-Hsiang
|Keywords:||Artificial Intelligence of Things;edible mint;mint extract;case-based reasoning||Issue Date:||1-Jan-2022||Publisher:||MDPI||Journal Volume:||10||Journal Issue:||1||Source:||PROCESSES||Abstract:||
In recent years, many large-scale plantings have become refined small-scale or home plantings. The rapid progress of agriculture technologies and information techniques enables people to control the growth of agricultural products well. Hence, this study proposes an Artificial Intelligence of Things (AIoT) based Plant Pot Design for planting edible mint in an office setting, which is called APPD. APPD is composed of intelligent gardens and a cloud-based service platform. An intelligent garden is deployed an Arduino with multiple sensors to monitor and control plant pots of the edible mint, Mentha spicata. The cloud-based service platform provides a Case-Based Reasoning (CBR) inference engine with a database for adjustment influence factors. This study discusses eight growing statuses of Mentha spicata with different illumination, photometric exposure, and moisture content, designed for an office environment. Evaluation results indicate that Mentha spicata with 16 h red-blue lighting and 50% moisture content makes a maximum 5% mint extract of the total weight of the mint leaves. Finally, APPD can be a reference model for researchers and engineers.
|Appears in Collections:||食品安全與風險管理研究所|
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