A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture
To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generall...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/19/8875 |
| _version_ | 1797516864305233920 |
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| author | Jesus David Chaux David Sanchez-Londono Giacomo Barbieri |
| author_facet | Jesus David Chaux David Sanchez-Londono Giacomo Barbieri |
| author_sort | Jesus David Chaux |
| collection | DOAJ |
| description | To ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. In this context, Digital Twin (DT) may constitute a fundamental tool to reach the optimization of the productivity, intended as the ratio between production and resource consumption. For this reason, a DT Architecture for CEA systems is introduced within this work and applied to a case study for its validation. The proposed architecture is potentially able to optimize productivity since it utilizes simulation software that enables the optimization of: (i) Climate control strategies related to the control of the crop microclimate; (ii) treatments related to crop management. Due to the importance of food security in the worldwide landscape, the authors hope that this work may impulse the investigation of strategies for improving the productivity of CEA systems. |
| first_indexed | 2024-03-10T07:06:50Z |
| format | Article |
| id | doaj.art-8529b024c412464da3977e8cd31bf22d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T07:06:50Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8529b024c412464da3977e8cd31bf22d2023-11-22T15:44:18ZengMDPI AGApplied Sciences2076-34172021-09-011119887510.3390/app11198875A Digital Twin Architecture to Optimize Productivity within Controlled Environment AgricultureJesus David Chaux0David Sanchez-Londono1Giacomo Barbieri2Department of Mechanical Engineering, Universidad de los Andes, Bogotá 111711, ColombiaDepartment of Mechanical Engineering, Universidad de los Andes, Bogotá 111711, ColombiaDepartment of Mechanical Engineering, Universidad de los Andes, Bogotá 111711, ColombiaTo ensure food security, agricultural production systems should innovate in the direction of increasing production while reducing utilized resources. Due to the higher level of automation with respect to traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. In this context, Digital Twin (DT) may constitute a fundamental tool to reach the optimization of the productivity, intended as the ratio between production and resource consumption. For this reason, a DT Architecture for CEA systems is introduced within this work and applied to a case study for its validation. The proposed architecture is potentially able to optimize productivity since it utilizes simulation software that enables the optimization of: (i) Climate control strategies related to the control of the crop microclimate; (ii) treatments related to crop management. Due to the importance of food security in the worldwide landscape, the authors hope that this work may impulse the investigation of strategies for improving the productivity of CEA systems.https://www.mdpi.com/2076-3417/11/19/8875controlled environment agriculturedigital twinproductivityarchitectureoptimization |
| spellingShingle | Jesus David Chaux David Sanchez-Londono Giacomo Barbieri A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture Applied Sciences controlled environment agriculture digital twin productivity architecture optimization |
| title | A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture |
| title_full | A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture |
| title_fullStr | A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture |
| title_full_unstemmed | A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture |
| title_short | A Digital Twin Architecture to Optimize Productivity within Controlled Environment Agriculture |
| title_sort | digital twin architecture to optimize productivity within controlled environment agriculture |
| topic | controlled environment agriculture digital twin productivity architecture optimization |
| url | https://www.mdpi.com/2076-3417/11/19/8875 |
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