LAPSE:2023.3203v1
Published Article

LAPSE:2023.3203v1
Design of an Artificial Intelligence of Things Based Indoor Planting Model for Mentha Spicata
February 22, 2023
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.
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.
Record ID
Keywords
Artificial Intelligence of Things, case-based reasoning, edible mint, mint extract
Subject
Suggested Citation
Ku HH, Liu CH, Wang WC. Design of an Artificial Intelligence of Things Based Indoor Planting Model for Mentha Spicata. (2023). LAPSE:2023.3203v1
Author Affiliations
Ku HH: Institute of Food Safety and Risk Management, National Taiwan Ocean University, Keelung City 202301, Taiwan [ORCID]
Liu CH: Institute of Food Safety and Risk Management, National Taiwan Ocean University, Keelung City 202301, Taiwan
Wang WC: College of Innovation and Entrepreneurship Education, Yango University, Fuzhou 350015, China [ORCID]
Liu CH: Institute of Food Safety and Risk Management, National Taiwan Ocean University, Keelung City 202301, Taiwan
Wang WC: College of Innovation and Entrepreneurship Education, Yango University, Fuzhou 350015, China [ORCID]
Journal Name
Processes
Volume
10
Issue
1
First Page
116
Year
2022
Publication Date
2022-01-07
ISSN
2227-9717
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Original Submission
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PII: pr10010116, Publication Type: Journal Article
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LAPSE:2023.3203v1
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https://doi.org/10.3390/pr10010116
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[v1] (Original Submission)
Feb 22, 2023
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Feb 22, 2023
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