Rocher, J.; Aldegheishem, A.; Alrajeh, N.; Lloret, J. (2022). Develop an Optical Sensor to Detect Pollution Incidents in Sewerage. IEEE Sensors Journal. 22(24):24449-24457. https://doi.org/10.1109/JSEN.2022.3219931
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/197251
Title:
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Develop an Optical Sensor to Detect Pollution Incidents in Sewerage
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Author:
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Rocher, Javier
Aldegheishem, Abdulaziz
Alrajeh, Nabil
Lloret, Jaime
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UPV Unit:
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Universitat Politècnica de València. Departamento de Tecnología de Alimentos - Departament de Tecnologia d'Aliments
Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia
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Issued date:
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Abstract:
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[EN] Cities are big consumers of energy and big producers of pollution. In the past years, the concept of smart cities has been applied to reduce the release of pollutants and to reduce energy consumption. In this article, ...[+]
[EN] Cities are big consumers of energy and big producers of pollution. In the past years, the concept of smart cities has been applied to reduce the release of pollutants and to reduce energy consumption. In this article, we present a wireless sensor network (WSN) based on solid sensor nodes to detect illicit discharges in sewerage. The solid sensor is an optical sensor that uses infrared light to determine the pollutant concentration in water. At 0 degrees, a photoreceptor receives infrared LED (IR LED) light and allows the current passage. This provokes a reduction of the internal resistance of the photoreceptor that can be measured. First, we tested different intensities of powered LEDs and resistances in the voltage divider. Once the best combinations had been selected, we calibrated our sensor. Our result suggested that the relative error of our prototype is 3.4% in the range of 200-5000 mg/L.
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Subjects:
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Arduino
,
Healthy living in smart cities
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LED
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LoRaWAN
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Smart cities
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Solid sensor
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Turbidity
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Wireless sensor network (WSN)
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Copyrigths:
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Cerrado |
Source:
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IEEE Sensors Journal. (issn:
1530-437X
)
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DOI:
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10.1109/JSEN.2022.3219931
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Publisher:
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Institute of Electrical and Electronics Engineers
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Publisher version:
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https://doi.org/10.1109/JSEN.2022.3219931
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Project ID:
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114467RR-C33/ES/RED HETEROGENEA INTELIGENTE DE SENSORES INALAMBRICOS PARA MONITORIZAR Y ESTIMAR EL CONTENIDO DE RESINA DE CISTUS LADANIFER/
info:eu-repo/grantAgreement/GV INNOV.UNI.CIENCIA//THINKINAZUL%2F2021%2F002//Red de Sensores y big data para la observacion del entorno marino (SALVADOR)/
info:eu-repo/grantAgreement/MECD//FPU16%2F05540/ES/FPU16%2F05540/
info:eu-repo/grantAgreement/KSU//RSP-2021%2F295//Researchers Supporting Project/
info:eu-repo/grantAgreement/MICINN//PRTR-C17.I1/
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Thanks:
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This work was supported in part by the Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia, under Grant RSP-2021/295; in part by the Ministerio de Educacion, Cultura y Deporte through the "Ayudas ...[+]
This work was supported in part by the Researchers Supporting Project, King Saud University, Riyadh, Saudi Arabia, under Grant RSP-2021/295; in part by the Ministerio de Educacion, Cultura y Deporte through the "Ayudas para contratacion predoctoral de Formacion de Profesorado Universi-tario (FPU) (Convocatoria 2016)" under Grant FPU16/05540; in part by the "Ministerio de Ciencia e Innovacion (MCIN)" under Project PID2020-114467RR-C33; in part by the "Ministerio de Agricultura, Pesca y Alimentacion" through the Project GO TECNOGAR; and in part by the ThinkInAzul Program by MCIN through the European Union NextGenerationEU under Grant PRTR-C17.I1 and the Generalitat Valenciana under Grant THINKINAZUL/2021/002.
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Type:
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Artículo
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