| dc.contributor.author | Navarro, Juan Miguel | |
| dc.contributor.author | Abderrazak, El Aatik | |
| dc.contributor.author | Pita, Antonio | |
| dc.contributor.author | Martínez, Ramón | |
| dc.contributor.author | Vela, Nuria | |
| dc.date.accessioned | 2025-02-24T14:39:40Z | |
| dc.date.available | 2025-02-24T14:39:40Z | |
| dc.date.issued | 2024-12-16 | |
| dc.identifier.citation | Navarro, J. M., El Aatik, A., Pita, A., Martinez, R., & Vela, N. (2024). Evaluation of an IoT Device for Nitrate and Nitrite Long-Term Monitoring in Wastewater Treatment Plants. IEEE Sensors Journal. | es |
| dc.identifier.issn | 1530-437X | |
| dc.identifier.uri | http://hdl.handle.net/10952/9280 | |
| dc.description.abstract | Water pollution is an issue of global concern that requires continuous monitoring to maintain the integrity of surface and groundwater. This growing concern about environmental contamination has prompted the development and use of physical and chemical systems to control water quality in situ in most ecosystems, including wastewater treatment plants (WWTPs). In most water reuse projects, effluents must meet applicable water quality standards, regardless of whether they are discharged to surface or groundwater bodies, for irrigation or industrial reuse. In this article, an evaluation of the performance of the Internet-of-Things (IoT) device for long-term monitoring and detection of nitrate and nitrite in wastewater is presented. This device is integrated in the IoT system with these main components: an ion chromatography (IC) sensor to provide accurate data, together with mechanical elements for water sample acquisition and electronic circuits for the control of the whole monitoring process, a communication module to send real-time information, and a cloud software platform to store, analyze, and visualize the obtained water quality metrics. This evaluation was carried out by comparing traditional laboratory results with data captured by the remote device during a long-term measurement campaign at three WWTPs located in Murcia, Spain. The results show a satisfactory validation against standardized laboratory values, demonstrating the long-term measurement capability of the system. Specifically, the coefficient of determination of the regression between laboratory and device procedures reaches 96.7% on average in the three WWTPs for both nitrate and nitrite and influent and effluent streams | es |
| dc.language.iso | en | es |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.subject | Internet of Things (IoT) | es |
| dc.subject | Monitoring | es |
| dc.subject | Nitrate | es |
| dc.subject | Nitrite | es |
| dc.subject | Pollution | es |
| dc.subject | Wastewater | es |
| dc.title | Evaluation of the IoT Device for Nitrate and Nitrite Long-Term Monitoring in Wastewater Treatment Plants | es |
| dc.type | journal article | es |
| dc.rights.accessRights | open access | es |
| dc.relation.projectID | This work was supported in part by the Enhanced Portable Sensor for Water Quality Monitoring Moving to Genuinely Integrated Water Resource Management Project-ECOSENS AQUAMONITRIX-funded by the LIFE Program of the European Union under Contract LIFE17 ENV/IE/000237; and in part by the ThinkInAzul Project supported by the Ministerio de Ciencia, Innovación y Universidades with funding from European Union Next Generation EU under Grant PRTR-C17.I1 and from the Comunidad Autónoma de la Región de Murcia-Fundación Seneca | es |
| dc.journal.title | IEEE Sensors Journal | es |
| dc.volume.number | 25 | es |
| dc.identifier.essn | 1558-1748 | |
| dc.issue.number | 4 | es |
| dc.description.discipline | Ciencias Ambientales | es |
| dc.description.discipline | Ingeniería, Industria y Construcción | es |
| dc.identifier.doi | 10.1109/JSEN.2024.3512355 | es |
| dc.description.faculty | Escuela Politécnica | es |