Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model
Hydroponics has gained significant interest as a vital method for sustainable food production. Various research works have emphasized key factors in hydroponic cultivation, including nutrient composition, solution and air temperatures, humidity, light intensity, and other environmental factors. Howe...
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Tamkang University Press
2025-06-01
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| Series: | Journal of Applied Science and Engineering |
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| Online Access: | http://jase.tku.edu.tw/articles/jase-202602-29-02-0009 |
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| author | Tapanee Treeratanaporn Thongchai Phairoh |
| author_facet | Tapanee Treeratanaporn Thongchai Phairoh |
| author_sort | Tapanee Treeratanaporn |
| collection | DOAJ |
| description | Hydroponics has gained significant interest as a vital method for sustainable food production. Various research works have emphasized key factors in hydroponic cultivation, including nutrient composition, solution and air temperatures, humidity, light intensity, and other environmental factors. However, the optimal flow rate of the nutrient solution has received limited attention despite its potentially critical role in plant growth, such as leaf count, size, and height. This study investigates whether the flow rate affects plant growth and which flow rate is optimal. Basil was chosen as the experimental plant due to its widespread culinary use. The research employs IoT technology to automate hydroponic systems. Key hardware components consist of sensors, microcontrollers, and pumps, supported by software including Arduino IDE and an IoT platform for cloud-based data storage.
Experimental data collection, including key factors in hydroponics cultivation and plant growth, started from seed germination to harvest and was then analyzed using decision tree-based data analytics techniques. Results indicate that a nutrient solution flow rate has been identified as a key factor influencing plant growth. However, the interaction between flow rate and other environmental factors, such as temperature, light intensity, and pH levels, must also be carefully considered. A holistic approach that accounts for the interdependence of these factors is essential to fully understanding the mechanisms behind plant growth. This research can be a prototype for identifying optimal cultivation features and other factors across various plant types. |
| format | Article |
| id | doaj-art-6c6d6cd44c7044bdb852eb0fc2cc637b |
| institution | OA Journals |
| issn | 2708-9967 2708-9975 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Tamkang University Press |
| record_format | Article |
| series | Journal of Applied Science and Engineering |
| spelling | doaj-art-6c6d6cd44c7044bdb852eb0fc2cc637b2025-08-20T02:22:15ZengTamkang University PressJournal of Applied Science and Engineering2708-99672708-99752025-06-0129233734610.6180/jase.202602_29(2).0009Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree ModelTapanee Treeratanaporn0Thongchai Phairoh1Department of Electrical and Computer Engineering, Faculty of Engineering, King Mongkut’s University of Technology North Bangkok, Bangkok, 10800, ThailandDepartment of Applied Engineering Technology, College of Engineering and Technology, Virginia State University, 23806, USAHydroponics has gained significant interest as a vital method for sustainable food production. Various research works have emphasized key factors in hydroponic cultivation, including nutrient composition, solution and air temperatures, humidity, light intensity, and other environmental factors. However, the optimal flow rate of the nutrient solution has received limited attention despite its potentially critical role in plant growth, such as leaf count, size, and height. This study investigates whether the flow rate affects plant growth and which flow rate is optimal. Basil was chosen as the experimental plant due to its widespread culinary use. The research employs IoT technology to automate hydroponic systems. Key hardware components consist of sensors, microcontrollers, and pumps, supported by software including Arduino IDE and an IoT platform for cloud-based data storage. Experimental data collection, including key factors in hydroponics cultivation and plant growth, started from seed germination to harvest and was then analyzed using decision tree-based data analytics techniques. Results indicate that a nutrient solution flow rate has been identified as a key factor influencing plant growth. However, the interaction between flow rate and other environmental factors, such as temperature, light intensity, and pH levels, must also be carefully considered. A holistic approach that accounts for the interdependence of these factors is essential to fully understanding the mechanisms behind plant growth. This research can be a prototype for identifying optimal cultivation features and other factors across various plant types.http://jase.tku.edu.tw/articles/jase-202602-29-02-0009flow ratehydroponicsinternet of thingsmachine learningsolar system |
| spellingShingle | Tapanee Treeratanaporn Thongchai Phairoh Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model Journal of Applied Science and Engineering flow rate hydroponics internet of things machine learning solar system |
| title | Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model |
| title_full | Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model |
| title_fullStr | Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model |
| title_full_unstemmed | Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model |
| title_short | Investigating the Optimal Flow Rate for Hydroponic Plants Using IoT and the Decision Tree Model |
| title_sort | investigating the optimal flow rate for hydroponic plants using iot and the decision tree model |
| topic | flow rate hydroponics internet of things machine learning solar system |
| url | http://jase.tku.edu.tw/articles/jase-202602-29-02-0009 |
| work_keys_str_mv | AT tapaneetreeratanaporn investigatingtheoptimalflowrateforhydroponicplantsusingiotandthedecisiontreemodel AT thongchaiphairoh investigatingtheoptimalflowrateforhydroponicplantsusingiotandthedecisiontreemodel |