Edge computing in environmental science: automated intelligent robotic platform for water quality assessment
This paper introduces a novel intelligent robotic platform designed to expedite and enhance the process of water quality assessment and bottom relief analysis in reservoirs. The platform, equipped with an array of sensors and actuators, is capable of conducting comprehensive studies over larger are...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Academy of Cognitive and Natural Sciences
2023-11-01
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| Series: | Journal of Edge Computing |
| Subjects: | |
| Online Access: | https://acnsci.org/journal/index.php/jec/article/view/633 |
| _version_ | 1797361817136136192 |
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| author | Andrii G. Tkachuk Mariia S. Hrynevych Tetiana A. Vakaliuk Oksana A. Chernysh Mykhailo G. Medvediev |
| author_facet | Andrii G. Tkachuk Mariia S. Hrynevych Tetiana A. Vakaliuk Oksana A. Chernysh Mykhailo G. Medvediev |
| author_sort | Andrii G. Tkachuk |
| collection | DOAJ |
| description |
This paper introduces a novel intelligent robotic platform designed to expedite and enhance the process of water quality assessment and bottom relief analysis in reservoirs. The platform, equipped with an array of sensors and actuators, is capable of conducting comprehensive studies over larger areas of the reservoir, thereby overcoming the limitations of traditional water analysis methods. The platform’s advanced design includes a control board, servo motors, a brushless motor, a radio module, a GPS module, and a motor speed controller, all housed within a robust casing. The paper presents a functional diagram of the platform and discusses the results of a system study conducted on a reservoir. The study aimed to verify the system’s operation, evaluate the effectiveness of the research conducted, and calibrate water quality sensors. The platform utilizes an ultrasonic sensor for depth measurement and sensors for water acidity and temperature. The results of the monitoring system experiments led to the creation of a detailed map of the reservoir’s bottom area and provided valuable insights into water quality.
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| first_indexed | 2024-03-08T15:59:49Z |
| format | Article |
| id | doaj.art-b767504e37ca46f785250f0f2dad4fe1 |
| institution | Directory Open Access Journal |
| issn | 2837-181X |
| language | English |
| last_indexed | 2024-03-08T15:59:49Z |
| publishDate | 2023-11-01 |
| publisher | Academy of Cognitive and Natural Sciences |
| record_format | Article |
| series | Journal of Edge Computing |
| spelling | doaj.art-b767504e37ca46f785250f0f2dad4fe12024-01-08T12:04:57ZengAcademy of Cognitive and Natural SciencesJournal of Edge Computing2837-181X2023-11-012210.55056/jec.633Edge computing in environmental science: automated intelligent robotic platform for water quality assessmentAndrii G. Tkachuk0Mariia S. Hrynevych1Tetiana A. Vakaliuk2Oksana A. Chernysh3Mykhailo G. Medvediev4Zhytomyr Polytechnic State University Zhytomyr Polytechnic State University Zhytomyr Polytechnic State University Zhytomyr Polytechnic State University ADA University This paper introduces a novel intelligent robotic platform designed to expedite and enhance the process of water quality assessment and bottom relief analysis in reservoirs. The platform, equipped with an array of sensors and actuators, is capable of conducting comprehensive studies over larger areas of the reservoir, thereby overcoming the limitations of traditional water analysis methods. The platform’s advanced design includes a control board, servo motors, a brushless motor, a radio module, a GPS module, and a motor speed controller, all housed within a robust casing. The paper presents a functional diagram of the platform and discusses the results of a system study conducted on a reservoir. The study aimed to verify the system’s operation, evaluate the effectiveness of the research conducted, and calibrate water quality sensors. The platform utilizes an ultrasonic sensor for depth measurement and sensors for water acidity and temperature. The results of the monitoring system experiments led to the creation of a detailed map of the reservoir’s bottom area and provided valuable insights into water quality. https://acnsci.org/journal/index.php/jec/article/view/633edge computingenvironmental scienceintelligent robotic platformwater quality assessmentreservoir bottom topographyultrasonic sensor |
| spellingShingle | Andrii G. Tkachuk Mariia S. Hrynevych Tetiana A. Vakaliuk Oksana A. Chernysh Mykhailo G. Medvediev Edge computing in environmental science: automated intelligent robotic platform for water quality assessment Journal of Edge Computing edge computing environmental science intelligent robotic platform water quality assessment reservoir bottom topography ultrasonic sensor |
| title | Edge computing in environmental science: automated intelligent robotic platform for water quality assessment |
| title_full | Edge computing in environmental science: automated intelligent robotic platform for water quality assessment |
| title_fullStr | Edge computing in environmental science: automated intelligent robotic platform for water quality assessment |
| title_full_unstemmed | Edge computing in environmental science: automated intelligent robotic platform for water quality assessment |
| title_short | Edge computing in environmental science: automated intelligent robotic platform for water quality assessment |
| title_sort | edge computing in environmental science automated intelligent robotic platform for water quality assessment |
| topic | edge computing environmental science intelligent robotic platform water quality assessment reservoir bottom topography ultrasonic sensor |
| url | https://acnsci.org/journal/index.php/jec/article/view/633 |
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