Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies
Eutrophication is the excessive growth of algae in water bodies that causes biodiversity loss, reducing water quality and attractiveness to people. This is an important problem in water bodies. In this paper, we propose a low-cost sensor to monitor eutrophication in concentrations between 0 to 200 m...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/8/3913 |
| _version_ | 1797603531591516160 |
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| author | Javier Rocher Jose M. Jimenez Jesus Tomas Jaime Lloret |
| author_facet | Javier Rocher Jose M. Jimenez Jesus Tomas Jaime Lloret |
| author_sort | Javier Rocher |
| collection | DOAJ |
| description | Eutrophication is the excessive growth of algae in water bodies that causes biodiversity loss, reducing water quality and attractiveness to people. This is an important problem in water bodies. In this paper, we propose a low-cost sensor to monitor eutrophication in concentrations between 0 to 200 mg/L and in different mixtures of sediment and algae (0, 20, 40, 60, 80, and 100% algae, the rest are sediment). We use two light sources (infrared and RGB LED) and two photoreceptors at 90° and 180° of the light sources. The system has a microcontroller (M5stacks) that powers the light sources and obtains the signal received by the photoreceptors. In addition, the microcontroller is responsible for sending information and generating alerts. Our results show that the use of infrared light at 90° can determine the turbidity with an error of 7.45% in NTU readings higher than 2.73 NTUs, and the use of infrared light at 180° can measure the solid concentration with an error of 11.40%. According to the determination of the % of algae, the use of a neural network has a precision of 89.3% in the classification, and the determination of the mg/L of algae in water has an error of 17.95%. |
| first_indexed | 2024-03-11T04:33:27Z |
| format | Article |
| id | doaj.art-d70d0f3b615a418b85bac54fcb4610d9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T04:33:27Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d70d0f3b615a418b85bac54fcb4610d92023-11-17T21:16:24ZengMDPI AGSensors1424-82202023-04-01238391310.3390/s23083913Low-Cost Turbidity Sensor to Determine Eutrophication in Water BodiesJavier Rocher0Jose M. Jimenez1Jesus Tomas2Jaime Lloret3Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paraninf, 1 Grao de Gandia, 46730 Valencia, SpainInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paraninf, 1 Grao de Gandia, 46730 Valencia, SpainInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paraninf, 1 Grao de Gandia, 46730 Valencia, SpainInstituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, C/Paraninf, 1 Grao de Gandia, 46730 Valencia, SpainEutrophication is the excessive growth of algae in water bodies that causes biodiversity loss, reducing water quality and attractiveness to people. This is an important problem in water bodies. In this paper, we propose a low-cost sensor to monitor eutrophication in concentrations between 0 to 200 mg/L and in different mixtures of sediment and algae (0, 20, 40, 60, 80, and 100% algae, the rest are sediment). We use two light sources (infrared and RGB LED) and two photoreceptors at 90° and 180° of the light sources. The system has a microcontroller (M5stacks) that powers the light sources and obtains the signal received by the photoreceptors. In addition, the microcontroller is responsible for sending information and generating alerts. Our results show that the use of infrared light at 90° can determine the turbidity with an error of 7.45% in NTU readings higher than 2.73 NTUs, and the use of infrared light at 180° can measure the solid concentration with an error of 11.40%. According to the determination of the % of algae, the use of a neural network has a precision of 89.3% in the classification, and the determination of the mg/L of algae in water has an error of 17.95%.https://www.mdpi.com/1424-8220/23/8/3913solidsarduinoRGB LEDinfrared LEDenvironmental pollution |
| spellingShingle | Javier Rocher Jose M. Jimenez Jesus Tomas Jaime Lloret Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies Sensors solids arduino RGB LED infrared LED environmental pollution |
| title | Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies |
| title_full | Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies |
| title_fullStr | Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies |
| title_full_unstemmed | Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies |
| title_short | Low-Cost Turbidity Sensor to Determine Eutrophication in Water Bodies |
| title_sort | low cost turbidity sensor to determine eutrophication in water bodies |
| topic | solids arduino RGB LED infrared LED environmental pollution |
| url | https://www.mdpi.com/1424-8220/23/8/3913 |
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