Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba
El agua potable es un derecho humano, se constituye como la base de la salud y la vida de los seres vivos. No obstante, debido a la variedad de factores tales como minería, explotación de petróleo, contaminación fecal, entre otros, a la falta de monitoreo y al desconocimiento de la calidad de la mis...
- Autores:
-
Carriazo Regino, Yulieth Paola
- Tipo de recurso:
- Fecha de publicación:
- 2021
- Institución:
- Universidad Autónoma de Bucaramanga - UNAB
- Repositorio:
- Repositorio UNAB
- Idioma:
- spa
- OAI Identifier:
- oai:repository.unab.edu.co:20.500.12749/15481
- Acceso en línea:
- http://hdl.handle.net/20.500.12749/15481
- Palabra clave:
- Systems engineer
Software development
IOT
Monitoring
Water quality
Real time
Drinking water
Public health
Water resources
Environmental monitoring
Desarrollo de Software
Ingeniería de sistemas
Agua potable
Salud pública
Recursos hídricos
Vigilancia ambiental
Internet
Monitoreo
Calidad del agua
Tiempo real
- Rights
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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| dc.title.spa.fl_str_mv |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| dc.title.translated.spa.fl_str_mv |
IOT-based water quality monitoring system, using data analytical techniques to detect anomalies, in the aqueducts executed by the departmental water plan (PDA) of Córdoba |
| title |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| spellingShingle |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba Systems engineer Software development IOT Monitoring Water quality Real time Drinking water Public health Water resources Environmental monitoring Desarrollo de Software Ingeniería de sistemas Agua potable Salud pública Recursos hídricos Vigilancia ambiental Internet Monitoreo Calidad del agua Tiempo real |
| title_short |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| title_full |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| title_fullStr |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| title_full_unstemmed |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| title_sort |
Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de Córdoba |
| dc.creator.fl_str_mv |
Carriazo Regino, Yulieth Paola |
| dc.contributor.advisor.none.fl_str_mv |
Roa Prada, Sebastián Diaz Claros, Alfredo |
| dc.contributor.author.none.fl_str_mv |
Carriazo Regino, Yulieth Paola |
| dc.contributor.cvlac.spa.fl_str_mv |
Roa Prada, Sebastián [0000295523] |
| dc.contributor.googlescholar.spa.fl_str_mv |
Roa Prada, Sebastián [es&oi=ao] |
| dc.contributor.orcid.spa.fl_str_mv |
Roa Prada, Sebastián [0000-0002-1079-9798] |
| dc.contributor.researchgate.spa.fl_str_mv |
Roa Prada, Sebastián [Sebastian-Roa-Prada] |
| dc.subject.keywords.spa.fl_str_mv |
Systems engineer Software development IOT Monitoring Water quality Real time Drinking water Public health Water resources Environmental monitoring |
| topic |
Systems engineer Software development IOT Monitoring Water quality Real time Drinking water Public health Water resources Environmental monitoring Desarrollo de Software Ingeniería de sistemas Agua potable Salud pública Recursos hídricos Vigilancia ambiental Internet Monitoreo Calidad del agua Tiempo real |
| dc.subject.lemb.spa.fl_str_mv |
Desarrollo de Software Ingeniería de sistemas Agua potable Salud pública Recursos hídricos Vigilancia ambiental Internet |
| dc.subject.proposal.spa.fl_str_mv |
Monitoreo Calidad del agua Tiempo real |
| description |
El agua potable es un derecho humano, se constituye como la base de la salud y la vida de los seres vivos. No obstante, debido a la variedad de factores tales como minería, explotación de petróleo, contaminación fecal, entre otros, a la falta de monitoreo y al desconocimiento de la calidad de la misma, puede conducir a enfermedades infecciosas que afectan a las personas, entre ellos los más vulnerables (niños y ancianos), como también, la falta de sistemas que permitan detectar en tiempo real los parámetros de calidad del agua fuera de los rangos establecidos, impide una toma de decisiones asertiva que permita garantizar una distribución de un agua apta para consumo humano a las diferentes zonas de cobertura entre ellas las rurales y de difícil acceso. Como resultado, fue desarrollado un sistema de monitoreo basado en IoT para la adquisición de datos a través de medidores especializados que permitan la captura de variables en tiempo real y mediante modelos de analíticas descriptiva contribuir en la detección de anomalías en los parámetros fisicoquímicos del agua para consumo humano. La metodología para realizar la investigación corresponde a un esquema de investigación conocido como Modelo Integral para el Profesional en Ingeniería, que aplica actividades de documentación, diseño y desarrollo, validación y evaluación experimental. Los resultados entre el método convencional para medición de la calidad del agua para consumo humano en zonas de difícil acceso y el dispositivo basado en IoT para este trabajo, muestran fiabilidad de las medidas realizadas ya que presentan un error relativo promedio inferior al 5%. Se puede concluir con esta investigación, que el prototipo podría usarse para informar a los usuarios sobre anomalías de los datos de los parámetros de calidad del agua potable en tiempo real, posibilitando a futuro la creación de una base de datos que se pueda comparar con futuras mediciones en cada sitio en el campo y desarrollar algoritmos predictivos que con la información obtenida puedan estimar la prevención de la salud de las personas. |
| publishDate |
2021 |
| dc.date.issued.none.fl_str_mv |
2021-09-01 |
| dc.date.accessioned.none.fl_str_mv |
2022-02-08T20:23:18Z |
| dc.date.available.none.fl_str_mv |
2022-02-08T20:23:18Z |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/masterThesis |
| dc.type.local.spa.fl_str_mv |
Tesis |
| dc.type.redcol.none.fl_str_mv |
http://purl.org/redcol/resource_type/TM |
| dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12749/15481 |
| dc.identifier.instname.spa.fl_str_mv |
instname:Universidad Autónoma de Bucaramanga - UNAB |
| dc.identifier.reponame.spa.fl_str_mv |
reponame:Repositorio Institucional UNAB |
| dc.identifier.repourl.spa.fl_str_mv |
repourl:https://repository.unab.edu.co |
| url |
http://hdl.handle.net/20.500.12749/15481 |
| identifier_str_mv |
instname:Universidad Autónoma de Bucaramanga - UNAB reponame:Repositorio Institucional UNAB repourl:https://repository.unab.edu.co |
| dc.language.iso.spa.fl_str_mv |
spa |
| language |
spa |
| dc.relation.references.spa.fl_str_mv |
Ahrend, U., Aleksy, M., Berning, M., Gebhardt, J., Mendoza, F., & Schulz, D. (2021). Sensors as the Basis for Digitalization: New Approaches in Instrumentation, IoT-concepts, and 5G. Internet of Things, 100406. https://doi.org/https://doi.org/10.1016/j.iot.2021.100406 Akhter, F., Siddiquei, H. R., Alahi, M. E. E., & Mukhopadhyay, S. C. (2021). Design and Development of an IoT-enabled Portable Phosphate Detection System in Water for Smart Agriculture. Sensors and Actuators A: Physical, 112861. https://doi.org/https://doi.org/10.1016/j.sna.2021.112861 Al-Turjman, F. (2020). The Cloud in Iot-Enabled Spaces. In CRC Press. Alahi, M. E. E., Mukhopadhyay, S. C., & Burkitt, L. (2018). Imprinted polymer coated impedimetric nitrate sensor for real- time water quality monitoring. Sensors and Actuators B: Chemical, 259, 753–761. https://doi.org/10.1016/j.snb.2017.12.104 Albano, M., Ferreira, L. L., Pinho, L. M., & Alkhawaja, A. R. (2015). Computer Standards & Interfaces Message-oriented middleware for smart grids. Computer Standards & Interfaces, 38, 133–143. https://doi.org/10.1016/j.csi.2014.08.002 Alcaldía de Bogota. (2021). Documentos para Agua: Agua Para el Consumo Humano. Algore, M. (2021). Machine Learning With Python: The Definitive Tool to Improve Your Python Programming and Deep Learning to Take You to The Next Level of Coding and Algorithms Optimization. Alley, E. R. (2006). Water Quality Control Handbook. In Environment (Second). McGraw Hill. https://doi.org/10.1036/0071467602 Amato, A., Cozzolino, G., Maisto, A., & Pelosi, S. (2021). Monitoring Airplanes Faults Through Business Intelligence Tools (pp. 224–234). https://doi.org/10.1007/978-3-030-61105-7_22 Arévalo-Gómez, M. Á., Carrillo-Zambrano, E., Herrera-Quintero, L. F., & Chavarriaga, J. (2018). Water wells monitoring solution in rural zones using IoT approaches and cloud-based real-time databases. Proceedings of the Euro American Conference on Telematics and Information Systems - EATIS ’18, 1–5. https://doi.org/10.1145/3293614.3293659 Arévalo Junco, A. D. (2019). Prototipo de un sistema de monitoreo de calidad del agua subterránea en instalaciones de captación de una localidad rural del municipio de Tibaná-Boyacá. Universidad Piloto de Colombia. Aspin, A. (2020). Pro Power BI Desktop. Apress. https://doi.org/10.1007/978-14842-5763-0 Aznil Ab Aziz, M., Abas, M. F., Anwar Abu Bashri, M. K., Saad, N. M., & Ariff, M. H. (2019). Evaluating IoT based passive water catchment monitoring system data acquisition and analysis. Bulletin of Electrical Engineering and Informatics, 8(4). https://doi.org/10.11591/eei.v8i4.1583 Badii, M., Guillen, A., Rodríguez, C., Lugo, O., Aguilar, J., & Acuña, M. (2015). Pérdida de Biodiversidad: Causas y Efectos Biodiversity Loss: Causes and Factors. Daena: International Journal of Good Conscience, 10(2), 156–174 Bagali, M. U., & Thangadurai, N. (2021). NavIC/GNSS receiver based integrated transport monitoring system using embedded system. Materials Today: Proceedings, xxxx. https://doi.org/10.1016/j.matpr.2020.11.080 Bahadori, A., & Smith,Bahadori, A., & Smith, S. T. (2016). A. In Dictionary of Environmental Engineering and Wastewater Treatment (pp. 1–37). Springer International Publishing. https://doi.org/10.1007/978-3-319-26261-1_1 Baird, R. B., Rice, E. W., & Posavec, S. (2017). Standard Methods For The Examination Of Water And Wastewater 23th. In Amer Public Health Assn Balachandar, S., & Chinnaiyan, R. (2020). Reliable pharma cold chain monitoring and analytics through Internet of Things Edge. In Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach (pp. 133–161). Elsevier. https://doi.org/10.1016/B978-0-12-819593-2.00005-4 Bastião Silva, L. A., Costa, C., & Oliveira, J. L. (2013). A common API for delivering services over multi-vendor cloud resources. Journal of Systems and Software, 86(9), 2309–2317. https://doi.org/10.1016/j.jss.2013.04.037 Bastidas, S. E. C., & Plata, R. A. D. (2020). Sistema IoT con UAV y GPR para Identificar Zonas Con Aguas Subterráneas en el Departamento de la GuajiraColombia. Encuentro Internacional de Educación En Ingeniería Beigi, N. K., Partov, B., & Farokhi, S. (2018). Real-time cloud robotics in practical smart city applications. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2017-Octob, 1–5. https://doi.org/10.1109/PIMRC.2017.8292655 Boehm, B. (2004). Balancing Agility and Discipline: A Guide for the Perplexed. https://doi.org/10.1007/978-3-540-24675-6_1 Boeker, M., Vach, W., & Motschall, E. (2013). Google Scholar as replacement for systematic literature searches: Good relative recall and precision are not enough. BMC Medical Research Methodology, 13(1). https://doi.org/10.1186/1471-2288-13-131 Boyd, C. E. (2020). Water Quality. Springer International Publishing. https://doi.org/10.1007/978-3-030-23335-8 Burbano Ordoñez, C. Y., & others. (2017). Implementación de una red de sensores inalámbricos LPWAN mediante módulos LoRa para el monitoreo de la calidad del agua en 2 ríos. Universidad Distrital Francisco José de Caldas. Burgos Galeano, C. A., Lafont Álvarez, K., & Estrada Palencia, P. A. (2018). Análisis comparativo de indicadores de la calidad del agua del rio Sinú municipio de Montería, Córdoba. Modum, 55–64. Caballero-Flores, R. (2019). Análisis de errores en las medidas. https://digibuo.uniovi.es/dspace/bitstream/handle/10651/52857/ANÁLISIS DE ERRORES EN LA MEDIDA_RCF.pdf?sequence=1 Caho-Rodríguez, C. A., & López-Barrera, E. A. (2017). Determinación del Índice de Calidad de Agua para el sector occidental del humedal Torca-Guaymaral empleando las metodologías UWQI y CWQI. Producción + Limpia, 12(2), 35– 49. https://doi.org/10.22507/pml.v12n Camacho Botero, L. A. (2020). La paradoja de la disponibilidad de agua de mala calidad en el sector rural colombiano. Revista de Ingeniería, 49(49), 38–51. https://doi.org/10.16924/revinge.49.6 Cao, H., Guo, Z., Wang, S., Cheng, H., & Zhan, C. (2020). Intelligent wide-area water quality monitoring and analysis system exploiting unmanned surface vehicles and ensemble learning. Water (Switzerland), 12(3). https://doi.org/10.3390/w12030681 Carminati, M., Turolla, A., Mezzera, L., Di Mauro, M., Tizzoni, M., Pani, G., Zanetto, F., Foschi, J., & Antonelli, M. (2020). A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems. Sensors, 20(4), 1125. https://doi.org/10.3390/s20041125 Carrasco Mantilla, W. (2016). Estado del arte del agua y saneamiento rural en Colombia. Revista de Ingeniería, 0(44), 46. https://doi.org/10.16924/riua.v0i44.923 CEPAL. (2013). Agua para el Siglo XXI para América del Sur. Journal of Chemical Information and Modeling, 53(9), 1689–1699. Chang, J. F. (2006). Business Process Management Systems. Strategy and Implementation. Taylor & Francis Group Chen, G., & Kotz, D. (2000). A Survey of Context-Aware Mobile Computing Research. Time, 3755(TR2000-381), 1–16. https://doi.org/10.1.1.140.3131 Chin Roemer, R., & Borchardt, R. (2015). Meaningful Metrics: A 21st Century Librarian’s Guide to Bibliometrics, Altmetrics, and Research Impact. Association of College and Research Libraries Climent, E., Pelegri-Sebastia, J., Sogorb, T., Talens, J., & Chilo, J. (2017). Development of the MOOSY4 eNose IoT for Sulphur-Based VOC Water Pollution Detection. Sensors, 17(8), 1917. https://doi.org/10.3390/s17081917 Coetzee, L., & Eksteen, J. (2011). The Internet of Things - promise for the future? An introduction. In In IST-Africa Conference Proceedings. IEEE. Conagua. (2010). Capítulo 3. Usos del Agua. Estadísticas Del Agua En México, Edición 2010, 61–76 Copeland, D. B. (2017). Rails, Angular, Postgres, and Bootstrap: Powerful, Effective, Efficient, Full-Stack Web Development Cordeiro, L., Mar, C., Valentin, E., Cruz, F., Patrick, D., Barreto, R., & Lucena, V. (2008). An agile development methodology applied to embedded control software under stringent hardware constraints. ACM SIGSOFT Software Engineering Notes, 33(1), 1. https://doi.org/10.1145/1344452.1344459 Cotruvo, J. A. (2018). Drinking water quality and contaminants guidebook. Taylor & Francis Cressie, N., & Wikle, C. K. (2011). Statistics for Spatio-Temporal Data. John Wiley and Sons CVS. (2020). Cobertura geográfica Departamento de Córdoba. DANE. (2018). Censo Nacional de Población y censo nacional de vivienda Vivienda. DANE, Publicacion Para Todos, 66. https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-ypoblacion/censo-nacional-de-poblacion-y-vivenda-2018/cuantos-somos Darwish, M., & Ouda, A. (2015). Evaluation of an OAuth 2 . 0 Protocol Implementation for Web Server Applications. 2015 International Conference and Workshop on Computing and Communication (IEMCON), 2–5. De Bellis, N. (2009). Bibliometrics and Citation Analysis; from the Science Citation Index to Cybermetrics. The Scarecrow Press, Inc. De León-Peña, R., & Vargas-Lombardo, M. (2017). OpenID connect and digital identity security. Revista de Iniciación Científica, 3(2), 94–99 Díaz Porras, K. P. (2019). El oro azul y su gestión de pérdidas en Colombia. Módulo Arquitectura CUC, 23(1), 9–22. https://doi.org/10.17981/mod.arq.cuc.23.1.2019.01 Dow, C. (2020). Hands-On Edge Analytics with Azure IoT: Design and Develop IoT Applications with Edge Analytical Solutions Including Azure IoT Edge. Packt Publishing Ltd. Dürr, C., & Vie, J.-J. (2021). Competitive Programming in Python: 128 Algorithms to Develop your Coding Skills. In Cambridge University Press. https://doi.org/10.1017/9781108591928 Edmondson, V., Cerny, M., Lim, M., Gledson, B., Lockley, S., & Woodward, J. (2018). A smart sewer asset information model to enable an ‘Internet of Things’ for operational wastewater management. Automation in Construction, 91, 193–205. https://doi.org/10.1016/j.autcon.2018.03.003 Ehrenmueller-Jensen, M. (2020). Self-Service AI with Power BI Desktop. In SelfService AI with Power BI Desktop. Apress. https://doi.org/10.1007/978-1-48426231-3 Emerson, S., Choi, Y. K., Hwang, D. Y., Kim, K. S., & Kim, K. H. (2015). An OAuth based authentication mechanism for IoT networks. International Conference on ICT Convergence 2015: Innovations Toward the IoT, 5G, and Smart Media Era, ICTC 2015, 1072–1074. https://doi.org/10.1109/ICTC.2015.7354740 Escobar Roberto, L. A., & Gutierrez Ramirez, N. (2020). Implementación de un sistema electrónico de monitoreo de la calidad del agua para un estanque piscícola. Universidad Distrital Francisco José de Caldas Espake, P. (2015). Learning Heroku Postgres. Packt Publishing Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37–54. Foro Económico Mundial. (2019). Informe de riesgos mundiales 2019 14.a edición. García, S., Luengo, J., & Herrera, F. (2015). Data Preprocessing in Data Mining. In Intelligent Systems Reference Library (Vol. 72). Springer International Publishing. https://doi.org/10.1007/978-3-319-10247-4 Geetha, S., & Gouthami, S. (2016). Internet of things enabled real time water quality monitoring system. Smart Water, 2(1), 1. https://doi.org/10.1186/s40713-017-0005-y Gingras, Y. (2016). Bibliometrics and Research Evaluation: Uses and Abuses (History and Foundations of Information Science). The MIT Press. Global Water. (2019). Water Quality. In Instrumentation Resource Book (pp. 54– 101). http://www.globalw.com/downloads/Catalog/WaterQuality.pdf Gorchev, H. G., & Ozolins, G. (1984). WHO guidelines for drinking- water quality. WHO Chronicle, 38(3), 104–108. Goyal, H. R., Ghanshala, K. K., & Sharma, S. (2021a). Flash flood risk management modeling in indian cities using IoT based reinforcement learning. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2021.01.072 Goyal, H. R., Ghanshala, K. K., & Sharma, S. (2021b). Recommendation based rescue operation model for flood victim using smart IoT devices. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.12.959 Greenfeld, D. R., & Greenfeld, A. R. (2020). Django Crash Course. Greengard, S. (2015). The Internet of Things Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010 Gupta, A. (2013). Java EE 7 Essentials: Enterprise Developer Handbook (M. Loukides & M. Blanchette (eds.); First Edit). O’Reilly Media, Inc. https://doi.org/10.1007/978-1-4302-4426-4 Guzmán, B. L., Nava, G., & Díaz, P. (2015). La calidad del agua para consumo humano y su asociación con la morbimortalidad en Colombia, 2008-2012. Biomedica, 35(3), 177–190. https://doi.org/10.7705/biomedica.v35i0.2511 Hakim, W. L., Hasanah, L., Mulyanti, B., & Aminudin, A. (2019). Characterization of turbidity water sensor SEN0189 on the changes of total suspended solids in the water. Journal of Physics: Conference Series, 1280, 022064. https://doi.org/10.1088/1742-6596/1280/2/022064 Havinek, P. (2009). Risk Management of Water Supply and Sanitation Systems (P. Hlavinek, C. Popovska, J. Marsalek, I. Mahrikova, & T. Kukharchyk (eds.)). Springer Netherlands. https://doi.org/10.1007/978-90-481-2365-0 Hill, C. A., Biemer, P. P., Buskirk, T. D., Japec, L., Kirchner, A., Kolenikov, S., & Lyberg, L. E. (2021). Big Data Meets Survey Science: A Collection of Innovative Methods. In Wiley Series in Survey Methodology. Wiley Hlavinek, P. (2020). Management of Water Quality and Quantity (M. Zelenakova, P. Hlavínek, & A. M. Negm (eds.)). Springer International Publishing. https://doi.org/10.1007/978-3-030-18359-2 Hoyos Botero, C. (2000). Un modelo para investigación documental (Señal Editora (ed.)). Hu, Z., & Liu, L. (2018). Prediction of water pollution by nutrients based on eutrophication evaluation. Chemical Engineering Transactions, 71, 667–672. https://doi.org/10.3303/CET1871112 IGAC. (2017). Mapas Departamentales Físico Políticos. Instituto Geográfico Agustín Codazzi. Islam, M., Ashraf, F., Alam, T., Misran, N., & Mat, K. (2018). A Compact Ultrawideband Antenna Based on Hexagonal Split-Ring Resonator for pH Sensor Application. Sensors, 18(9), 2959. https://doi.org/10.3390/s18092959 James, S. (2016). An Introduction to Data Analysis using Aggregation Functions in R. In An Introduction to Data Analysis using Aggregation Functions in R. Springer International Publishing. https://doi.org/10.1007/978-3-319-46762-7 Jia, T., Zhao, X., Wang, Z., Gong, D., & Ding, G. (2016). Model Transformation and Data Migration from Relational Database to MongoDB. 2016 IEEE International Congress on Big Data (BigData Congress), 60–67. https://doi.org/10.1109/BigDataCongress.2016.16 John, V., & Liu, X. (2017). A Survey of Distributed Message Broker Queues Kachroud, M., Trolard, F., Kefi, M., Jebari, S., & Bourrié, G. (2019). Water quality indices: Challenges and application limits in the literature. Water (Switzerland), 11(2), 1–26. https://doi.org/10.3390/w11020361 Kaur, H., Singh, S. P., Bhatnagar, S., & Solanki, A. (2021). Chapter 10 - Intelligent Smart Home Energy Efficiency Model Using Artificial Intelligence and Internet of Things (G. Kaur, P. Tomar, & M. B. T.-A. I. to S. P. I. of T. I. Tanque (eds.); pp. 183–210). Academic Press. https://doi.org/https://doi.org/10.1016/B978-012-818576-6.00010-1 Kim, H. (2021). Software Engineering in IoT, Big Data, Cloud and Mobile Computing (H. Kim & R. Lee (eds.); Vol. 930). Springer International Publishing. https://doi.org/10.1007/978-3-030-64773- Kothari, N., Shreemali, J., Chakrabarti, P., & Poddar, S. (2021). Design and implementation of IoT sensor based drinking water quality measurement system. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.12.1142 Lai, C. S., Lai, L. L., & Lai, Q. H. (2021). Smart Grids and Big Data Analytics for Smart Cities. In Smart Grids and Big Data Analytics for Smart Cities. Springer International Publishing. https://doi.org/10.1007/978-3-030-52155-4 Larson, B. (2019). Data Analysis with Microsoft Power BI. McGraw-Hill Education. Lea, P. (2018). Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security. Packt Publishing Lea, P. (2020). IoT and Edge Computing for Architects. Lee, R. (2020). Big Data, Cloud Computing, and Data Science Engineering (R. Lee (ed.); Vol. 844). Springer International Publishing. https://doi.org/10.1007/9783-030-24405-7 Leke, C. A., & Marwala, T. (2019). Deep Learning and Missing Data in Engineering Systems (Vol. 48). Springer International Publishing. https://doi.org/10.1007/978-3-030-01180-2 Lima-Rodrigues, L. M. S., & Rodrigues, D. A. (2020). Agenda 2030. Quaestio - Revista de Estudos Em Educação, 22(3), 721–739. https://doi.org/10.22483/2177-5796.2020v22n3p721-739 Little, R. J. A., & Rubin, D. B. (2019). Statistical Analysis with Missing Data. In Wiley Series in Probability and Statistics. John Wiley & Sons Livelihoods & Natural Resource Man, International Water & Sanitation C, Centre for Economic and Social Stu, & Watershed Support Services & Activ. (2014). Sustainable Water and Sanitation Services. In Sustainable Water and Sanitation Services: The Life-Cycle Cost Approach to Planning and Management. Routledge. https://doi.org/10.4324/9780203521670 Loucks, D. P., & van Beek, E. (2017). Water resource systems planning and management: An introduction to methods, models, and applications. In Water Resource Systems Planning and Management: An Introduction to Methods, Models, and Applications. https://doi.org/10.1007/978-3-319-44234-1 Ma, H., & Wang, J. (2021). The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. In J. MacIntyre, J. Zhao, & X. Ma (Eds.), Advances in Intelligent Systems and Computing (Vol. 1282). Springer International Publishing. https://doi.org/10.1007/978-3-03062743-0 Megargel, A., Shankararaman, V., & Walker, D. K. (2020). Software Engineering in the Era of Cloud Computing (M. Ramachandran & Z. Mahmood (eds.)). Springer International Publishing. https://doi.org/10.1007/978-3-030-33624-0 Melé, A. (2020). Django 3 By Example: Build powerful and reliable Python web applications from scratch (3th ed.). PACKT Publishing Melendez Gelvez, I., Quijano Parra, A., & Pardo Perez, E. (2015). Actividad genotóxica de aguas antes y despues de clorar en la planta de potabilización Empopamplona. Bistua Revista De La Facultad De Ciencias Basicas, 13(2), 12. https://doi.org/10.24054/01204211.v2.n2.2015.1795 Meneses, H. W. P., García, J. P. M., & Sánchez, M. E. L. (2018). AQUASMART, La Solución Mecatrónica al Manejo de Recursos Hídricos. Encuentro Internacional de Educación En Ingeniería. Micheli, G. De. (2020). Embedded, Cyber-Physical, and IoT Systems. In S. S. Bhattacharyya, M. Potkonjak, & S. Velipasalar (Eds.), Embedded, CyberPhysical, and IoT Systems. Springer International Publishing. https://doi.org/10.1007/978-3-030-16949-7 Decreto número 1575 de 2007, 14 (2007). Ministerio de la protección social, & Ministerio de Ambiente, V. y D. T. (2007). Resolución 2115/2007. Gaceta Oficial, 23. Minteer, A. (2017). Analytics for the Internet of Things (IoT): Intelligent analytics for your intelligent devices. Packt Publishing Mirzavand, R., Honari, M., Laribi, B., Khorshidi, B., Sadrzadeh, M., & Mousavi, P. (2018). An Unpowered Sensor Node for Real-Time Water Quality Assessment (Humic Acid Detection). Electronics, 7(10), 231. https://doi.org/10.3390/electronics710023 Mishra, V., Kumar, T., Bhalla, K., & Patil, M. M. (2018). SuJAL: Design and Development of IoT-Based Real-Time Lake Monitoring System. 2018 3rd International Conference on Circuits, Control, Communication and Computing (I4C), 1–4. https://doi.org/10.1109/CIMCA.2018.8739 Mitsa, T. (2010). Temporal Data Mining. Chapman and Hall/CRC. https://doi.org/10.1201/9781420089776 Molenberghs, G., Fitzmaurice, G., Kenward, M., Tsiatis, B., & Verbeke, G. (2015). Handbook of Missing Data Methodology. In G. Molenberghs, G. Fitzmaurice, M. G. Kenward, & A. Tsiatis (Eds.), Handbook of Missing Data Methodology. Chapman and Hall/CRC. https://doi.org/10.1201/b17622 Morales García, J., Peñuela Meneses, W., & Leyes Sánchez, M. (2018). Aquasmart, la solución mecatrónica al manejo de recursos hídricos. Encuentro Internacional de Educación En Ingeniería ACOFI, 1–7. Moreno Arboleda, F. J., Quintero Rendón, J. E., & Rueda Vásquez, R. (2016). Una comparación de rendimiento entre Oracle y MongoDB. Ciencia e Ingeniería Neogranadina, 26(1), 109. https://doi.org/10.18359/rcin.1669 Munirathinam, S. (2021). Drift Detection Analytics for IoT Sensors. Procedia Computer Science, 180, 903–912. https://doi.org/https://doi.org/10.1016/j.procs.2021.01.341 Musa, P., Sugeru, H., & Mufza, H. F. (2019). An intelligent applied Fuzzy Logic to prediction the Parts per Million (PPM) as hydroponic nutrition on the based Internet of Things (IoT). 2019 Fourth International Conference on Informatics and Computing (ICIC), 1–7. https://doi.org/10.1109/ICIC47613.2019.8985712 Naqvi, S., Yfantidou, S., & Zimányi, E. (2017). Advanced Databases. Time Series Databases and InfluxDB. In Universite libre de Bruxelles. Norris, D. J. (2020). Machine Learning with the Raspberry Pi: Experiments with Data and Computer Vision. Apress. https://doi.org/10.1007/978-1-4842-5174-4 Núñez-Blanco, Y., Ramírez-Cerpa, E., & Sánchez-Comas, A. (2020). Revisión de sistemas de telemetría en ríos: propuesta para el río Magdalena, Barranquilla, Colombia. Tecnología y Ciencias Del Agua, 11(5), 298–343. https://doi.org/10.24850/j-tyca-2020-05-08 Ojha, A. (2020). Sensors in Water Pollutants Monitoring: Role of Material (D. Pooja, P. Kumar, P. Singh, & S. Patil (eds.)). Springer Singapore. https://doi.org/10.1007/978-981-15-0671-0 OMS. (2006). Guidelines for drinking- water qualit OMS, O. M. D. L. S., & UNICEF, F. de las N. U. para la I. (2017). Progresos en materia de agua potable, saneamiento e higiene. In Organización Mundial de la Salud. Organización Mundial de La Salud. (2011). Guías para la calidad del agua de consumo humano. Organización Mundial de La Salud, 4, 608. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLOS Medicine, 18(3), e1003583. https://doi.org/10.1371/journal.pmed.1003583 Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., MayoWilson, E., McDonald, S., … McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ, 372, n160. https://doi.org/10.1136/bmj.n160 Parameswari, M., & Moses, M. B. (2018). Online measurement of water quality and reporting system using prominent rule controller based on aqua care-IOT. Design Automation for Embedded Systems, 22(1–2), 25–44. https://doi.org/10.1007/s10617-017-9187-7 Particle. (2020). Quick Start: ARGON. Particle.Io. Pilicita Garrido, A., Borja López, Y., & Gutiérrez Constante, G. (2020). Rendimiento de MariaDB y PostgreSQL. Revista Científica y Tecnológica UPSE, 7(2), 09– 16. https://doi.org/10.26423/rctu.v7i2.538 Poongodi, T., Rathee, A., Indrakumari, R., & Suresh, P. (2020). Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm. In S.-L. Peng, S. Pal, & L. Huang (Eds.), Intelligent Systems Reference Library. Springer International Publishing. https://doi.org/10.1007/978-3-030-33596-0 Poza Luján, J. L. (2012). Proposed smart control distributed architecture based on service quality policies. Doctoral thesis. Universidad Politécnica de Valencia Prashanth, D. S., Patel, G., & Bharathi, B. (2017). Research and development of a mobile based women safety application with real-time database and datastream network. 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), 1–5. https://doi.org/10.1109/ICCPCT.2017.8074261 Programa de las Naciones Unidas para el Desarrollo. (2015). Objetivos de Desarrollo del Milenio. In Humanismo y Trabajo Social: Vols 5 (93-101). Puig, V., Ocampo-Martínez, C., Pérez, R., Cembrano, G., Quevedo, J., & Escobet, T. (Eds.). (2017). Real-time Monitoring and Operational Control of DrinkingWater Systems. Springer International Publishing. https://doi.org/10.1007/9783-319-50751-4 Quintana Fajardo, B. F., & Sarabia Caffroni, J. J. (2018). Arquitectura para el sistema de monitoreo de la calidad del agua de los caños y lagos internos del Distrito de Cartagena de Indias soportada en tecnologías de internet de las cosas. Universidad de Cartagena Rad, R. (2018). Power BI Service Content. In Pro Power BI Architecture (pp. 29– 57). Apress. https://doi.org/10.1007/978-1-4842-4015-1_3 Raghuvanshi, A., & Singh, U. K. (2020). Internet of Things for smart cities- security issues and challenges. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.10.849 Rajanna, R. R., Natarajan, S., & Vittal, P. R. (2018). An IoT Wi-Fi Connected Sensor For Real Time Heart Rate Variability Monitoring. 2018 3rd International Conference on Circuits, Control, Communication and Computing (I4C), 1–4. https://doi.org/10.1109/CIMCA.2018.8739323 Ratnaparkhi, S., Khan, S., Arya, C., Khapre, S., Singh, P., Diwakar, M., & Shankar, A. (2020). Smart agriculture sensors in IOT: A review. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.11.138 Ray, P. P., Dash, D., & De, D. (2019). Internet of things-based real-time model study on e-healthcare: Device, message service and dew computing. Computer Networks, 149, 226–239. https://doi.org/10.1016/j.comnet.2018.12.006 Asamblea General de las Naciones Unidas, Naciones Unidas 3 (2010). Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., & Koffel, J. B. (2021). PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Systematic Reviews, 10(1), 39. https://doi.org/10.1186/s13643-020-01542-z Rey Graña, C., & Ramil Diaz, M. (2011). Series temporales. Introduccion a La Estadistica Descriptiva. Segunda Edicion, 85–105. https://doi.org/10.4272/978-84-9745-167-3.ch4 Rojo-Nieto, E., & Montoto, T. (2017). Basuras marinas, plásticos y microplásticos orígenes, impactos y consecuencias de una amenaza global. Ecologistas en Acción Rondero, C., & Font, V. (2015). Articulación de la complejidad matemática de la media aritmética. Ensenanza de Las Ciencias, 33(2), 29–49. https://doi.org/10.5565/rev/ensciencias.1386 Ruiz, C. A., Salazar, D. M., & Rodríguez González, N. (2020). La prestación de los servicios de agua potable y saneamiento básico en Colombia análisis y prospectiva. In Investigaciones y productos CID Ruiz, C. A., Salazar, D. M., & Rodríguez, N. (2020). The provision of drinking water and basic sanitation services in Colombia: analysis and prospective. Documentos FCE-CID Escuela de Economía, 34, 1–86. www.fce.unal.edu.co/centro-editorial/documentos.html Ruiz Peláez, J. G., & Rodríguez Malagón, M. N. (2015). Población y muestra. Epidemiología Clínica: Investigación Clínica Aplicada, 62–66. Russo, C., Ramón, H., Alonso, N., Cicerchia, B., Esnaola, L., & Tessore, J. P. (2015). Tratamiento Masivo de Datos Utilizando Técnicas de Machine Learning Resumen Contexto Introducción. 131–134 Samaranayake, P., Ramanathan, K., & Laosirihongthong, T. (2017). Implementing industry 4.0 — A technological readiness perspective. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 529–533. https://doi.org/10.1109/IEEM.2017.8289947 Saravanan, K., Anusuya, E., Kumar, R., & Son, L. H. (2018). Real-time water quality monitoring using Internet of Things in SCADA. Environmental Monitoring and Assessment, 190(9). https://doi.org/10.1007/s10661-018-6914x Schwaber, K. (2004). Agile Project Management with Scrum (Vol. 7, Issue CMM). https://doi.org/10.1201/9781420084191-c2 Seamark, P., & Martens, T. (2019). Pro Dax with Power Bi: Business Intelligence with Powerpivot and SQL Server Analysis Services Tabular. Apress. https://doi.org/10.1007/978-1-4842-4897-3 Sebastian, A. (2020). Smart Systems and IoT: Innovations in Computing. In A. K. Somani, R. S. Shekhawat, A. Mundra, S. Srivastava, & V. K. Verma (Eds.), Smart Innovation, Systems and Technologies. Springer Singapore. https://doi.org/10.1007/978-981-13-8406-6 Serpanos, D., & Wolf, M. (2018). Internet-of-Things (IoT) Systems. In Internet-ofThings (IoT) Systems. Springer International Publishing. https://doi.org/10.1007/978-3-319-69715-4 Serrano Castaño, C. E. (2002). Modelo integral para el profesional en ingeniería (Universidad del Cauca (Ed.)). Shaw, P. (2013). Postgres Succinctly. In Syncfusion Inc Sierra, C. A. (2011). Calidad del Agua. Evaluación y diagnóstico. In Journal of Chemical Information and Modeling. https://repository.udem.edu.co/handle/11407/2568 Siow, E., Tiropanis, T., & Hall, W. (2018). Analytics for the Internet of Things. ACM Computing Surveys, 51(4), 1–36. https://doi.org/10.1145/3204947 Spandana, K., & Rao, V. R. S. (2018). Internet of Things (Iot) Based smart water quality monitoring system. International Journal of Engineering and Technology(UAE), 7(3), 259–262. https://doi.org/10.14419/ijet.v7i3.6.14985 Suresh, A., Nandagopal, M., Pethuru Raj, Neeba, E. A., & Lin, J.-W. (2020). Industrial IoT Application Architectures and Use Cases. Auerbach Publications. Suseendran, G., & Balaganesh, D. (2021). Smart cattle health monitoring system using IoT sensors. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2021.01.873 Sutradhar, B. C. (2013). ISS-2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers (B. C. Sutradhar (Ed.); Vol. 211). Springer New York. https://doi.org/10.1007/9781-4614-6871-4 Tanwar, S. (2020). Fog Data Analytics for IoT Applications: Next Generation Process Model with State of the Art Technologies (S. Tanwar (Ed.); Vol. 76). Springer Singapore. https://doi.org/10.1007/978-981-15-6044-6 The Government Office for Science. (2014). The IoT: making the most of the Second Digital Revolution. WordLink, 1–40. https://doi.org/GS/14/1230 Torres Pardo, J. C. (2017). Definition of a Reference Architecture for Information Systems in Ubiquitous Wireless Sensor Networks based on quality of service. Master’s Degree Option Work. Universidad Nacional de Colombia Tukey, J. W. (1962). The Future of Data Analysis. The annals of mathematical statistics. UNESCO. (2015). El Crecimiento Insostenible Y La Creciente Demanda Mundial De Agua. Wwdr, 12 UNESCO. (2019). Informe Mundial de las Naciones Unidas sobre el Desarrollo de los Recursos Hídricos 2019. No dejar a nadie atrás. In Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura UNESCO. (2020). Informe Mundial de las Naciones Unidas sobre el Desarrollo de los Recursos Hídricos 2020. In Agua y Cambio Climático Urrútia, G., & Bonfill, X. (2010). Declaración PRISMA: una propuesta para mejorar la publicación de revisiones sistemáticas y metaanálisis. Medicina Clínica, 135(11), 507–511. https://doi.org/10.1016/j.medcli.2010.01.015 van Eck, N. J., & Waltman, L. (2011). Text mining and visualization using VOSviewer. Text Mining and Visualization, 1–5. van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070. https://doi.org/10.1007/s11192-017-2300-7 Vélez, A., & Calvo, G. (1992). La investigación documental. Estado del arte y del conocimiento. Análisis de la investigación en la formación de investigadores. Universidad de la Sabana Viegas, V., Pereira, J. M. D., Girao, P., Postolache, O., & Salgado, R. (2018). IoT applied to Environmental Monitoring in Oysters’ Farms. 2018 International Symposium in Sensing and Instrumentation in IoT Era (ISSI), 1–5. https://doi.org/10.1109/ISSI.2018.8538136 Vikesland, P. J. (2018). Nanosensors for water quality monitoring. Nature Nanotechnology, 13(8), 651–660. https://doi.org/10.1038/s41565-018-0209-9 Viloria, A., Acuña, G. C., Alcázar Franco, D. J., Hernández-Palma, H., Fuentes, J. P., & Rambal, E. P. (2019). Integration of Data Mining Techniques to PostgreSQL Database Manager System. Procedia Computer Science, 155, 575–580. https://doi.org/10.1016/j.procs.2019.08.080 Wade, R. (2020). Advanced Analytics in Power BI with R and Python. Apress. https://doi.org/10.1007/978-1-4842-5829-3 Water-quality engineering in natural systems: fate and transport processes in the water environment. (2013). Choice Reviews Online, 50(12), 50-6781-50–6781. https://doi.org/10.5860/choice.50-6781 Weber, R. H., & Weber, R. (2010). Internet of Things. In Development. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-11710-7 Weiser, M. (1991). The computer for the 21st century. Scientific American (International Edition), 265(3), 66–75. https://doi.org/10.1038/scientificamerican0991-94 Wolf, W. H. W. H. (1994). Hardware-software co-design of embedded systems. Proceedings of the IEEE, 82(7), 967–989. https://doi.org/10.1109/5.293155 Wong, B. P., & Kerkez, B. (2016). Real-time environmental sensor data: An application to water quality using web services. Environmental Modelling & Software, 84, 505–517. https://doi.org/10.1016/j.envsoft.2016.07.020 World Health Organization. (2019). Safe water, better health. In Geneva: World Health Organization; 2019. Licence: CC BY-NC-SA 3.0 IGO Wortham, R. H. (2020). Transparency for Robots and Autonomous Systems. The Institution of Engineering and Technology Yanes, A. R., Martinez, P., & Ahmad, R. (2020). Towards automated aquaponics: A review on monitoring, IoT, and smart systems. Journal of Cleaner Production, 263, 121571. https://doi.org/https://doi.org/10.1016/j.jclepro.2020.121571 Zelenakova, M., Hlavínek, P., & Negm, A. M. (2020). Management of Water Quality and Quantity. Springer International Publishing. https://doi.org/10.1007/978-3-030-18359-2 Ziegler, A. (2014). In-situ Materials Characterization (A. Ziegler, H. Graafsma, X. F. Zhang, & J. W. M. Frenken (Eds.); Vol. 193). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-45152-2 Zimányi, E., Sakr, M., & Lesuisse, A. (2020). MobilityDB: A Mobility Database Based on PostgreSQL and PostGIS. ACM Transactions on Database Systems, 45(4), 1–42. https://doi.org/10.1145/3406534 Zou, Q., Xiong, Q., Li, Q., Yi, H., Yu, Y., & Wu, C. (2020). A water quality prediction method based on the multi-time scale bidirectional long short-term memory network. Environmental Science and Pollution Research, 27(14), 16853– 16864. https://doi.org/10.1007/s11356-020-08087-7 |
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Roa Prada, Sebastiándd399662-c4ef-4825-81c2-4d5982b995c7-1Diaz Claros, Alfredob4a93c90-9bc8-4949-9b72-3483aaeeeb65-1Carriazo Regino, Yulieth Paola28f67858-a3ee-44c3-a11d-74f712975082-1Roa Prada, Sebastián [0000295523]Roa Prada, Sebastián [es&oi=ao]Roa Prada, Sebastián [0000-0002-1079-9798]Roa Prada, Sebastián [Sebastian-Roa-Prada]ColombiaUNAB Campus Bucaramanga2022-02-08T20:23:18Z2022-02-08T20:23:18Z2021-09-01http://hdl.handle.net/20.500.12749/15481instname:Universidad Autónoma de Bucaramanga - UNABreponame:Repositorio Institucional UNABrepourl:https://repository.unab.edu.coEl agua potable es un derecho humano, se constituye como la base de la salud y la vida de los seres vivos. No obstante, debido a la variedad de factores tales como minería, explotación de petróleo, contaminación fecal, entre otros, a la falta de monitoreo y al desconocimiento de la calidad de la misma, puede conducir a enfermedades infecciosas que afectan a las personas, entre ellos los más vulnerables (niños y ancianos), como también, la falta de sistemas que permitan detectar en tiempo real los parámetros de calidad del agua fuera de los rangos establecidos, impide una toma de decisiones asertiva que permita garantizar una distribución de un agua apta para consumo humano a las diferentes zonas de cobertura entre ellas las rurales y de difícil acceso. Como resultado, fue desarrollado un sistema de monitoreo basado en IoT para la adquisición de datos a través de medidores especializados que permitan la captura de variables en tiempo real y mediante modelos de analíticas descriptiva contribuir en la detección de anomalías en los parámetros fisicoquímicos del agua para consumo humano. La metodología para realizar la investigación corresponde a un esquema de investigación conocido como Modelo Integral para el Profesional en Ingeniería, que aplica actividades de documentación, diseño y desarrollo, validación y evaluación experimental. Los resultados entre el método convencional para medición de la calidad del agua para consumo humano en zonas de difícil acceso y el dispositivo basado en IoT para este trabajo, muestran fiabilidad de las medidas realizadas ya que presentan un error relativo promedio inferior al 5%. Se puede concluir con esta investigación, que el prototipo podría usarse para informar a los usuarios sobre anomalías de los datos de los parámetros de calidad del agua potable en tiempo real, posibilitando a futuro la creación de una base de datos que se pueda comparar con futuras mediciones en cada sitio en el campo y desarrollar algoritmos predictivos que con la información obtenida puedan estimar la prevención de la salud de las personas.INTRODUCCIÓN ................................................................................................... 22 1. BASES PRELIMINARES DE LA INVESTIGACIÓN ...................................... 24 1.1. PLANTEAMIENTO DEL PROBLEMA ............................................................ 24 1.1.1. Pregunta de Investigación ........................................................................... 27 1.2. JUSTIFICACIÓN ......................................................................................... 27 1.3. OBJETIVOS ................................................................................................ 28 1.3.1. Objetivo General ...................................................................................... 28 1.3.2. Objetivos Específicos .............................................................................. 29 1.4. CONTEXTO DE LA INVESTIGACIÓN ........................................................ 29 1.4.1. Antecedentes ............................................................................................... 30 2. REVISIÓN DE LA LITERATURA ................................................................... 39 2.1 AGUA POTABLE ............................................................................................. 39 2.2. CALIDAD DEL AGUA ..................................................................................... 40 2.2.1. Problemas en la calidad del agua ................................................................ 44 2.2.2. Parámetros de Calidad del Agua Potable .................................................... 45 2.2.3. Control y Vigilancia ...................................................................................... 50 2.3. INTERNET DE LAS COSAS (IOT) .................................................................. 53 2.4. MEDIDORES .................................................................................................. 54 2.4.1. Sensor de Temperatura DS18B20 ............................................................... 56 2.4.2. Sensor de pH SKU SEN0161 ...................................................................... 57 2.4.3. Sensor de Turbidez SKU SEN0189 ............................................................. 59 2.4.4. Sensor de conductividad eléctrica analógica ............................................... 60 2.4.5. Sensor analógico TDS ................................................................................. 62 2.5. COMPUTACIÓN EN LA NUBE (CLOUD COMPUTING) ................................ 64 2.6. ANÁLISIS DE DATOS PARA GESTIÓN DE LA INFRAESTRUCTURA DE IOT ............................................................................................................... 64 2.6.1. Análisis Descriptivo ...................................................................................... 67 2.6.2. Preprocesamiento y calidad de datos .......................................................... 68 2.7. POWER BI ...................................................................................................... 70 2.8. PUBNUB ......................................................................................................... 72 3. METODOLOGÍA ................................................................................................ 73 3.1. INTRODUCCIÓN ............................................................................................ 73 3.2. ALCANCE DE LA INVESTIGACIÓN .......................................................... 75 3.3. HIPÓTESIS ................................................................................................. 76 3.4. DISEÑO ...................................................................................................... 76 3.5. POBLACIÓN Y MUESTRA ......................................................................... 77 3.6. VARIABLES ............................................................................................... 80 3.7. ANÁLISIS DE DATOS ................................................................................ 80 3.8. MATERIALES Y EQUIPO DE INVESTIGACIÓN ........................................ 81 4. RESULTADOS DE LA INVESTIGACIÓN ......................................................... 84 4.1 DESARROLLO DEL PROTOTIPO PARA MONITOREO DE CALIDAD DEL AGUA ................................................................................................................. 84 4.2 EVALUACIÓN EXPERIMENTAL DEL PROTOTIPO BASADO EN IOT ........... 98 5. CONCLUSIONES ............................................................................................ 108 6. RECOMENDACIONES Y TRABAJOS FUTUROS ......................................... 109 REFERENCIAS BIBLIOGRÁFICAS ................................................................... 110 ANEXOS .............................................................................................................. 127MaestríaDrinking water is a human right, it is constituted as the basis of the health and life of living beings. However, due to the variety of factors such as mining, oil exploitation, fecal contamination, among others, the lack of monitoring and the lack of knowledge of its quality, it can lead to infectious diseases that send people, among they are the most vulnerable (children and the elderly), as well as the lack of systems to detect in real time for human consumption the different coverage areas, including rural areas and those with difficult access. As a result, a monitoring system based on IoT was developed for the acquisition of data through specialized meters that achieve the capture of variables in real time and through descriptive analytical models contribute in the detection of anomalies in the physicochemical parameters of the water to human consumption. The methodology to carry out the research corresponding to a research scheme known as the Integral Model for the Professional in Engineering, which applies activities of documentation, design and development, validation and experimental evaluation. The results between the conventional method for measuring the quality of drinking water in hard-to-reach areas and the device based on IoT for this work, show reliability of the measurements carried out since they present a relative error of less than 5%. It can be concluded with this research that the prototype could be used to inform users about anomalies in the data of the drinking water quality parameters in real time, making it possible in the future to create a database that can be compared with future ones. measurements at each site in the field and develop predictive algorithms that with the information obtained can estimate the prevention of people's health.Modalidad Presencialapplication/pdfspahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Abierto (Texto Completo)Atribución-NoComercial-SinDerivadas 2.5 Colombiahttp://purl.org/coar/access_right/c_abf2Sistema de monitoreo de la calidad del agua basado en IOT, utilizando técnicas de analítica de datos para la detección de anomalías, en los acueductos ejecutados por el plan departamental de aguas (PDA) de CórdobaIOT-based water quality monitoring system, using data analytical techniques to detect anomalies, in the aqueducts executed by the departmental water plan (PDA) of CórdobaMagíster en Gestión, Aplicación y Desarrollo de SoftwareUniversidad Autónoma de Bucaramanga UNABFacultad IngenieríaMaestría en Gestión, Aplicación y Desarrollo de Softwareinfo:eu-repo/semantics/masterThesisTesishttp://purl.org/redcol/resource_type/TMSystems engineerSoftware developmentIOTMonitoringWater qualityReal timeDrinking waterPublic healthWater resourcesEnvironmental monitoringDesarrollo de SoftwareIngeniería de sistemasAgua potableSalud públicaRecursos hídricosVigilancia ambientalInternetMonitoreoCalidad del aguaTiempo realAhrend, U., Aleksy, M., Berning, M., Gebhardt, J., Mendoza, F., & Schulz, D. (2021). Sensors as the Basis for Digitalization: New Approaches in Instrumentation, IoT-concepts, and 5G. Internet of Things, 100406. https://doi.org/https://doi.org/10.1016/j.iot.2021.100406Akhter, F., Siddiquei, H. R., Alahi, M. E. E., & Mukhopadhyay, S. C. (2021). Design and Development of an IoT-enabled Portable Phosphate Detection System in Water for Smart Agriculture. Sensors and Actuators A: Physical, 112861. https://doi.org/https://doi.org/10.1016/j.sna.2021.112861Al-Turjman, F. (2020). The Cloud in Iot-Enabled Spaces. In CRC Press.Alahi, M. E. E., Mukhopadhyay, S. C., & Burkitt, L. (2018). Imprinted polymer coated impedimetric nitrate sensor for real- time water quality monitoring. Sensors and Actuators B: Chemical, 259, 753–761. https://doi.org/10.1016/j.snb.2017.12.104Albano, M., Ferreira, L. L., Pinho, L. M., & Alkhawaja, A. R. (2015). Computer Standards & Interfaces Message-oriented middleware for smart grids. Computer Standards & Interfaces, 38, 133–143. https://doi.org/10.1016/j.csi.2014.08.002Alcaldía de Bogota. (2021). Documentos para Agua: Agua Para el Consumo Humano.Algore, M. (2021). Machine Learning With Python: The Definitive Tool to Improve Your Python Programming and Deep Learning to Take You to The Next Level of Coding and Algorithms Optimization.Alley, E. R. (2006). Water Quality Control Handbook. In Environment (Second). McGraw Hill. https://doi.org/10.1036/0071467602Amato, A., Cozzolino, G., Maisto, A., & Pelosi, S. (2021). Monitoring Airplanes Faults Through Business Intelligence Tools (pp. 224–234). https://doi.org/10.1007/978-3-030-61105-7_22Arévalo-Gómez, M. Á., Carrillo-Zambrano, E., Herrera-Quintero, L. F., & Chavarriaga, J. (2018). Water wells monitoring solution in rural zones using IoT approaches and cloud-based real-time databases. Proceedings of the Euro American Conference on Telematics and Information Systems - EATIS ’18, 1–5. https://doi.org/10.1145/3293614.3293659Arévalo Junco, A. D. (2019). Prototipo de un sistema de monitoreo de calidad del agua subterránea en instalaciones de captación de una localidad rural del municipio de Tibaná-Boyacá. Universidad Piloto de Colombia.Aspin, A. (2020). Pro Power BI Desktop. Apress. https://doi.org/10.1007/978-14842-5763-0Aznil Ab Aziz, M., Abas, M. F., Anwar Abu Bashri, M. K., Saad, N. M., & Ariff, M. H. (2019). Evaluating IoT based passive water catchment monitoring system data acquisition and analysis. Bulletin of Electrical Engineering and Informatics, 8(4). https://doi.org/10.11591/eei.v8i4.1583Badii, M., Guillen, A., Rodríguez, C., Lugo, O., Aguilar, J., & Acuña, M. (2015). Pérdida de Biodiversidad: Causas y Efectos Biodiversity Loss: Causes and Factors. Daena: International Journal of Good Conscience, 10(2), 156–174Bagali, M. U., & Thangadurai, N. (2021). NavIC/GNSS receiver based integrated transport monitoring system using embedded system. Materials Today: Proceedings, xxxx. https://doi.org/10.1016/j.matpr.2020.11.080Bahadori, A., & Smith,Bahadori, A., & Smith, S. T. (2016). A. In Dictionary of Environmental Engineering and Wastewater Treatment (pp. 1–37). Springer International Publishing. https://doi.org/10.1007/978-3-319-26261-1_1Baird, R. B., Rice, E. W., & Posavec, S. (2017). Standard Methods For The Examination Of Water And Wastewater 23th. In Amer Public Health AssnBalachandar, S., & Chinnaiyan, R. (2020). Reliable pharma cold chain monitoring and analytics through Internet of Things Edge. In Emergence of Pharmaceutical Industry Growth with Industrial IoT Approach (pp. 133–161). Elsevier. https://doi.org/10.1016/B978-0-12-819593-2.00005-4Bastião Silva, L. A., Costa, C., & Oliveira, J. L. (2013). A common API for delivering services over multi-vendor cloud resources. Journal of Systems and Software, 86(9), 2309–2317. https://doi.org/10.1016/j.jss.2013.04.037Bastidas, S. E. C., & Plata, R. A. D. (2020). Sistema IoT con UAV y GPR para Identificar Zonas Con Aguas Subterráneas en el Departamento de la GuajiraColombia. Encuentro Internacional de Educación En IngenieríaBeigi, N. K., Partov, B., & Farokhi, S. (2018). Real-time cloud robotics in practical smart city applications. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2017-Octob, 1–5. https://doi.org/10.1109/PIMRC.2017.8292655Boehm, B. (2004). Balancing Agility and Discipline: A Guide for the Perplexed. https://doi.org/10.1007/978-3-540-24675-6_1Boeker, M., Vach, W., & Motschall, E. (2013). Google Scholar as replacement for systematic literature searches: Good relative recall and precision are not enough. BMC Medical Research Methodology, 13(1). https://doi.org/10.1186/1471-2288-13-131Boyd, C. E. (2020). Water Quality. Springer International Publishing. https://doi.org/10.1007/978-3-030-23335-8Burbano Ordoñez, C. Y., & others. (2017). Implementación de una red de sensores inalámbricos LPWAN mediante módulos LoRa para el monitoreo de la calidad del agua en 2 ríos. Universidad Distrital Francisco José de Caldas.Burgos Galeano, C. A., Lafont Álvarez, K., & Estrada Palencia, P. A. (2018). Análisis comparativo de indicadores de la calidad del agua del rio Sinú municipio de Montería, Córdoba. Modum, 55–64.Caballero-Flores, R. (2019). Análisis de errores en las medidas. https://digibuo.uniovi.es/dspace/bitstream/handle/10651/52857/ANÁLISIS DE ERRORES EN LA MEDIDA_RCF.pdf?sequence=1Caho-Rodríguez, C. A., & López-Barrera, E. A. (2017). Determinación del Índice de Calidad de Agua para el sector occidental del humedal Torca-Guaymaral empleando las metodologías UWQI y CWQI. Producción + Limpia, 12(2), 35– 49. https://doi.org/10.22507/pml.v12nCamacho Botero, L. A. (2020). La paradoja de la disponibilidad de agua de mala calidad en el sector rural colombiano. Revista de Ingeniería, 49(49), 38–51. https://doi.org/10.16924/revinge.49.6Cao, H., Guo, Z., Wang, S., Cheng, H., & Zhan, C. (2020). Intelligent wide-area water quality monitoring and analysis system exploiting unmanned surface vehicles and ensemble learning. Water (Switzerland), 12(3). https://doi.org/10.3390/w12030681Carminati, M., Turolla, A., Mezzera, L., Di Mauro, M., Tizzoni, M., Pani, G., Zanetto, F., Foschi, J., & Antonelli, M. (2020). A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems. Sensors, 20(4), 1125. https://doi.org/10.3390/s20041125Carrasco Mantilla, W. (2016). Estado del arte del agua y saneamiento rural en Colombia. Revista de Ingeniería, 0(44), 46. https://doi.org/10.16924/riua.v0i44.923CEPAL. (2013). Agua para el Siglo XXI para América del Sur. Journal of Chemical Information and Modeling, 53(9), 1689–1699.Chang, J. F. (2006). Business Process Management Systems. Strategy and Implementation. Taylor & Francis GroupChen, G., & Kotz, D. (2000). A Survey of Context-Aware Mobile Computing Research. Time, 3755(TR2000-381), 1–16. https://doi.org/10.1.1.140.3131Chin Roemer, R., & Borchardt, R. (2015). Meaningful Metrics: A 21st Century Librarian’s Guide to Bibliometrics, Altmetrics, and Research Impact. Association of College and Research LibrariesCliment, E., Pelegri-Sebastia, J., Sogorb, T., Talens, J., & Chilo, J. (2017). Development of the MOOSY4 eNose IoT for Sulphur-Based VOC Water Pollution Detection. Sensors, 17(8), 1917. https://doi.org/10.3390/s17081917Coetzee, L., & Eksteen, J. (2011). The Internet of Things - promise for the future? An introduction. In In IST-Africa Conference Proceedings. IEEE.Conagua. (2010). Capítulo 3. Usos del Agua. Estadísticas Del Agua En México, Edición 2010, 61–76Copeland, D. B. (2017). Rails, Angular, Postgres, and Bootstrap: Powerful, Effective, Efficient, Full-Stack Web DevelopmentCordeiro, L., Mar, C., Valentin, E., Cruz, F., Patrick, D., Barreto, R., & Lucena, V. (2008). An agile development methodology applied to embedded control software under stringent hardware constraints. ACM SIGSOFT Software Engineering Notes, 33(1), 1. https://doi.org/10.1145/1344452.1344459Cotruvo, J. A. (2018). Drinking water quality and contaminants guidebook. Taylor & FrancisCressie, N., & Wikle, C. K. (2011). Statistics for Spatio-Temporal Data. John Wiley and SonsCVS. (2020). Cobertura geográfica Departamento de Córdoba.DANE. (2018). Censo Nacional de Población y censo nacional de vivienda Vivienda. DANE, Publicacion Para Todos, 66. https://www.dane.gov.co/index.php/estadisticas-por-tema/demografia-ypoblacion/censo-nacional-de-poblacion-y-vivenda-2018/cuantos-somosDarwish, M., & Ouda, A. (2015). Evaluation of an OAuth 2 . 0 Protocol Implementation for Web Server Applications. 2015 International Conference and Workshop on Computing and Communication (IEMCON), 2–5.De Bellis, N. (2009). Bibliometrics and Citation Analysis; from the Science Citation Index to Cybermetrics. The Scarecrow Press, Inc.De León-Peña, R., & Vargas-Lombardo, M. (2017). OpenID connect and digital identity security. Revista de Iniciación Científica, 3(2), 94–99Díaz Porras, K. P. (2019). El oro azul y su gestión de pérdidas en Colombia. Módulo Arquitectura CUC, 23(1), 9–22. https://doi.org/10.17981/mod.arq.cuc.23.1.2019.01Dow, C. (2020). Hands-On Edge Analytics with Azure IoT: Design and Develop IoT Applications with Edge Analytical Solutions Including Azure IoT Edge. Packt Publishing Ltd.Dürr, C., & Vie, J.-J. (2021). Competitive Programming in Python: 128 Algorithms to Develop your Coding Skills. In Cambridge University Press. https://doi.org/10.1017/9781108591928Edmondson, V., Cerny, M., Lim, M., Gledson, B., Lockley, S., & Woodward, J. (2018). A smart sewer asset information model to enable an ‘Internet of Things’ for operational wastewater management. Automation in Construction, 91, 193–205. https://doi.org/10.1016/j.autcon.2018.03.003Ehrenmueller-Jensen, M. (2020). Self-Service AI with Power BI Desktop. In SelfService AI with Power BI Desktop. Apress. https://doi.org/10.1007/978-1-48426231-3Emerson, S., Choi, Y. K., Hwang, D. Y., Kim, K. S., & Kim, K. H. (2015). An OAuth based authentication mechanism for IoT networks. International Conference on ICT Convergence 2015: Innovations Toward the IoT, 5G, and Smart Media Era, ICTC 2015, 1072–1074. https://doi.org/10.1109/ICTC.2015.7354740Escobar Roberto, L. A., & Gutierrez Ramirez, N. (2020). Implementación de un sistema electrónico de monitoreo de la calidad del agua para un estanque piscícola. Universidad Distrital Francisco José de CaldasEspake, P. (2015). Learning Heroku Postgres. Packt PublishingFayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37–54.Foro Económico Mundial. (2019). Informe de riesgos mundiales 2019 14.a edición.García, S., Luengo, J., & Herrera, F. (2015). Data Preprocessing in Data Mining. In Intelligent Systems Reference Library (Vol. 72). Springer International Publishing. https://doi.org/10.1007/978-3-319-10247-4Geetha, S., & Gouthami, S. (2016). Internet of things enabled real time water quality monitoring system. Smart Water, 2(1), 1. https://doi.org/10.1186/s40713-017-0005-yGingras, Y. (2016). Bibliometrics and Research Evaluation: Uses and Abuses (History and Foundations of Information Science). The MIT Press.Global Water. (2019). Water Quality. In Instrumentation Resource Book (pp. 54– 101). http://www.globalw.com/downloads/Catalog/WaterQuality.pdfGorchev, H. G., & Ozolins, G. (1984). WHO guidelines for drinking- water quality. WHO Chronicle, 38(3), 104–108.Goyal, H. R., Ghanshala, K. K., & Sharma, S. (2021a). Flash flood risk management modeling in indian cities using IoT based reinforcement learning. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2021.01.072Goyal, H. R., Ghanshala, K. K., & Sharma, S. (2021b). Recommendation based rescue operation model for flood victim using smart IoT devices. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.12.959Greenfeld, D. R., & Greenfeld, A. R. (2020). Django Crash Course.Greengard, S. (2015). The Internet of ThingsGubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010Gupta, A. (2013). Java EE 7 Essentials: Enterprise Developer Handbook (M. Loukides & M. Blanchette (eds.); First Edit). O’Reilly Media, Inc. https://doi.org/10.1007/978-1-4302-4426-4Guzmán, B. L., Nava, G., & Díaz, P. (2015). La calidad del agua para consumo humano y su asociación con la morbimortalidad en Colombia, 2008-2012. Biomedica, 35(3), 177–190. https://doi.org/10.7705/biomedica.v35i0.2511Hakim, W. L., Hasanah, L., Mulyanti, B., & Aminudin, A. (2019). Characterization of turbidity water sensor SEN0189 on the changes of total suspended solids in the water. Journal of Physics: Conference Series, 1280, 022064. https://doi.org/10.1088/1742-6596/1280/2/022064Havinek, P. (2009). Risk Management of Water Supply and Sanitation Systems (P. Hlavinek, C. Popovska, J. Marsalek, I. Mahrikova, & T. Kukharchyk (eds.)). Springer Netherlands. https://doi.org/10.1007/978-90-481-2365-0Hill, C. A., Biemer, P. P., Buskirk, T. D., Japec, L., Kirchner, A., Kolenikov, S., & Lyberg, L. E. (2021). Big Data Meets Survey Science: A Collection of Innovative Methods. In Wiley Series in Survey Methodology. WileyHlavinek, P. (2020). Management of Water Quality and Quantity (M. Zelenakova, P. Hlavínek, & A. M. Negm (eds.)). Springer International Publishing. https://doi.org/10.1007/978-3-030-18359-2Hoyos Botero, C. (2000). Un modelo para investigación documental (Señal Editora (ed.)).Hu, Z., & Liu, L. (2018). Prediction of water pollution by nutrients based on eutrophication evaluation. Chemical Engineering Transactions, 71, 667–672. https://doi.org/10.3303/CET1871112IGAC. (2017). Mapas Departamentales Físico Políticos. Instituto Geográfico Agustín Codazzi.Islam, M., Ashraf, F., Alam, T., Misran, N., & Mat, K. (2018). A Compact Ultrawideband Antenna Based on Hexagonal Split-Ring Resonator for pH Sensor Application. Sensors, 18(9), 2959. https://doi.org/10.3390/s18092959James, S. (2016). An Introduction to Data Analysis using Aggregation Functions in R. In An Introduction to Data Analysis using Aggregation Functions in R. Springer International Publishing. https://doi.org/10.1007/978-3-319-46762-7Jia, T., Zhao, X., Wang, Z., Gong, D., & Ding, G. (2016). Model Transformation and Data Migration from Relational Database to MongoDB. 2016 IEEE International Congress on Big Data (BigData Congress), 60–67. https://doi.org/10.1109/BigDataCongress.2016.16John, V., & Liu, X. (2017). A Survey of Distributed Message Broker QueuesKachroud, M., Trolard, F., Kefi, M., Jebari, S., & Bourrié, G. (2019). Water quality indices: Challenges and application limits in the literature. Water (Switzerland), 11(2), 1–26. https://doi.org/10.3390/w11020361Kaur, H., Singh, S. P., Bhatnagar, S., & Solanki, A. (2021). Chapter 10 - Intelligent Smart Home Energy Efficiency Model Using Artificial Intelligence and Internet of Things (G. Kaur, P. Tomar, & M. B. T.-A. I. to S. P. I. of T. I. Tanque (eds.); pp. 183–210). Academic Press. https://doi.org/https://doi.org/10.1016/B978-012-818576-6.00010-1Kim, H. (2021). Software Engineering in IoT, Big Data, Cloud and Mobile Computing (H. Kim & R. Lee (eds.); Vol. 930). Springer International Publishing. https://doi.org/10.1007/978-3-030-64773-Kothari, N., Shreemali, J., Chakrabarti, P., & Poddar, S. (2021). Design and implementation of IoT sensor based drinking water quality measurement system. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.12.1142Lai, C. S., Lai, L. L., & Lai, Q. H. (2021). Smart Grids and Big Data Analytics for Smart Cities. In Smart Grids and Big Data Analytics for Smart Cities. Springer International Publishing. https://doi.org/10.1007/978-3-030-52155-4Larson, B. (2019). Data Analysis with Microsoft Power BI. McGraw-Hill Education.Lea, P. (2018). Internet of Things for Architects: Architecting IoT solutions by implementing sensors, communication infrastructure, edge computing, analytics, and security. Packt PublishingLea, P. (2020). IoT and Edge Computing for Architects.Lee, R. (2020). Big Data, Cloud Computing, and Data Science Engineering (R. Lee (ed.); Vol. 844). Springer International Publishing. https://doi.org/10.1007/9783-030-24405-7Leke, C. A., & Marwala, T. (2019). Deep Learning and Missing Data in Engineering Systems (Vol. 48). Springer International Publishing. https://doi.org/10.1007/978-3-030-01180-2Lima-Rodrigues, L. M. S., & Rodrigues, D. A. (2020). Agenda 2030. Quaestio - Revista de Estudos Em Educação, 22(3), 721–739. https://doi.org/10.22483/2177-5796.2020v22n3p721-739Little, R. J. A., & Rubin, D. B. (2019). Statistical Analysis with Missing Data. In Wiley Series in Probability and Statistics. John Wiley & SonsLivelihoods & Natural Resource Man, International Water & Sanitation C, Centre for Economic and Social Stu, & Watershed Support Services & Activ. (2014). Sustainable Water and Sanitation Services. In Sustainable Water and Sanitation Services: The Life-Cycle Cost Approach to Planning and Management. Routledge. https://doi.org/10.4324/9780203521670Loucks, D. P., & van Beek, E. (2017). Water resource systems planning and management: An introduction to methods, models, and applications. In Water Resource Systems Planning and Management: An Introduction to Methods, Models, and Applications. https://doi.org/10.1007/978-3-319-44234-1Ma, H., & Wang, J. (2021). The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy. In J. MacIntyre, J. Zhao, & X. Ma (Eds.), Advances in Intelligent Systems and Computing (Vol. 1282). Springer International Publishing. https://doi.org/10.1007/978-3-03062743-0Megargel, A., Shankararaman, V., & Walker, D. K. (2020). Software Engineering in the Era of Cloud Computing (M. Ramachandran & Z. Mahmood (eds.)). Springer International Publishing. https://doi.org/10.1007/978-3-030-33624-0Melé, A. (2020). Django 3 By Example: Build powerful and reliable Python web applications from scratch (3th ed.). PACKT PublishingMelendez Gelvez, I., Quijano Parra, A., & Pardo Perez, E. (2015). Actividad genotóxica de aguas antes y despues de clorar en la planta de potabilización Empopamplona. Bistua Revista De La Facultad De Ciencias Basicas, 13(2), 12. https://doi.org/10.24054/01204211.v2.n2.2015.1795Meneses, H. W. P., García, J. P. M., & Sánchez, M. E. L. (2018). AQUASMART, La Solución Mecatrónica al Manejo de Recursos Hídricos. Encuentro Internacional de Educación En Ingeniería.Micheli, G. De. (2020). Embedded, Cyber-Physical, and IoT Systems. In S. S. Bhattacharyya, M. Potkonjak, & S. Velipasalar (Eds.), Embedded, CyberPhysical, and IoT Systems. Springer International Publishing. https://doi.org/10.1007/978-3-030-16949-7Decreto número 1575 de 2007, 14 (2007).Ministerio de la protección social, & Ministerio de Ambiente, V. y D. T. (2007). Resolución 2115/2007. Gaceta Oficial, 23.Minteer, A. (2017). Analytics for the Internet of Things (IoT): Intelligent analytics for your intelligent devices. Packt PublishingMirzavand, R., Honari, M., Laribi, B., Khorshidi, B., Sadrzadeh, M., & Mousavi, P. (2018). An Unpowered Sensor Node for Real-Time Water Quality Assessment (Humic Acid Detection). Electronics, 7(10), 231. https://doi.org/10.3390/electronics710023Mishra, V., Kumar, T., Bhalla, K., & Patil, M. M. (2018). SuJAL: Design and Development of IoT-Based Real-Time Lake Monitoring System. 2018 3rd International Conference on Circuits, Control, Communication and Computing (I4C), 1–4. https://doi.org/10.1109/CIMCA.2018.8739Mitsa, T. (2010). Temporal Data Mining. Chapman and Hall/CRC. https://doi.org/10.1201/9781420089776Molenberghs, G., Fitzmaurice, G., Kenward, M., Tsiatis, B., & Verbeke, G. (2015). Handbook of Missing Data Methodology. In G. Molenberghs, G. Fitzmaurice, M. G. Kenward, & A. Tsiatis (Eds.), Handbook of Missing Data Methodology. Chapman and Hall/CRC. https://doi.org/10.1201/b17622Morales García, J., Peñuela Meneses, W., & Leyes Sánchez, M. (2018). Aquasmart, la solución mecatrónica al manejo de recursos hídricos. Encuentro Internacional de Educación En Ingeniería ACOFI, 1–7.Moreno Arboleda, F. J., Quintero Rendón, J. E., & Rueda Vásquez, R. (2016). Una comparación de rendimiento entre Oracle y MongoDB. Ciencia e Ingeniería Neogranadina, 26(1), 109. https://doi.org/10.18359/rcin.1669Munirathinam, S. (2021). Drift Detection Analytics for IoT Sensors. Procedia Computer Science, 180, 903–912. https://doi.org/https://doi.org/10.1016/j.procs.2021.01.341Musa, P., Sugeru, H., & Mufza, H. F. (2019). An intelligent applied Fuzzy Logic to prediction the Parts per Million (PPM) as hydroponic nutrition on the based Internet of Things (IoT). 2019 Fourth International Conference on Informatics and Computing (ICIC), 1–7. https://doi.org/10.1109/ICIC47613.2019.8985712Naqvi, S., Yfantidou, S., & Zimányi, E. (2017). Advanced Databases. Time Series Databases and InfluxDB. In Universite libre de Bruxelles.Norris, D. J. (2020). Machine Learning with the Raspberry Pi: Experiments with Data and Computer Vision. Apress. https://doi.org/10.1007/978-1-4842-5174-4Núñez-Blanco, Y., Ramírez-Cerpa, E., & Sánchez-Comas, A. (2020). Revisión de sistemas de telemetría en ríos: propuesta para el río Magdalena, Barranquilla, Colombia. Tecnología y Ciencias Del Agua, 11(5), 298–343. https://doi.org/10.24850/j-tyca-2020-05-08Ojha, A. (2020). Sensors in Water Pollutants Monitoring: Role of Material (D. Pooja, P. Kumar, P. Singh, & S. Patil (eds.)). Springer Singapore. https://doi.org/10.1007/978-981-15-0671-0OMS. (2006). Guidelines for drinking- water qualitOMS, O. M. D. L. S., & UNICEF, F. de las N. U. para la I. (2017). Progresos en materia de agua potable, saneamiento e higiene. In Organización Mundial de la Salud.Organización Mundial de La Salud. (2011). Guías para la calidad del agua de consumo humano. Organización Mundial de La Salud, 4, 608.Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. PLOS Medicine, 18(3), e1003583. https://doi.org/10.1371/journal.pmed.1003583Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., MayoWilson, E., McDonald, S., … McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews. BMJ, 372, n160. https://doi.org/10.1136/bmj.n160Parameswari, M., & Moses, M. B. (2018). Online measurement of water quality and reporting system using prominent rule controller based on aqua care-IOT. Design Automation for Embedded Systems, 22(1–2), 25–44. https://doi.org/10.1007/s10617-017-9187-7Particle. (2020). Quick Start: ARGON. Particle.Io.Pilicita Garrido, A., Borja López, Y., & Gutiérrez Constante, G. (2020). Rendimiento de MariaDB y PostgreSQL. Revista Científica y Tecnológica UPSE, 7(2), 09– 16. https://doi.org/10.26423/rctu.v7i2.538Poongodi, T., Rathee, A., Indrakumari, R., & Suresh, P. (2020). Principles of Internet of Things (IoT) Ecosystem: Insight Paradigm. In S.-L. Peng, S. Pal, & L. Huang (Eds.), Intelligent Systems Reference Library. Springer International Publishing. https://doi.org/10.1007/978-3-030-33596-0Poza Luján, J. L. (2012). Proposed smart control distributed architecture based on service quality policies. Doctoral thesis. Universidad Politécnica de ValenciaPrashanth, D. S., Patel, G., & Bharathi, B. (2017). Research and development of a mobile based women safety application with real-time database and datastream network. 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT), 1–5. https://doi.org/10.1109/ICCPCT.2017.8074261Programa de las Naciones Unidas para el Desarrollo. (2015). Objetivos de Desarrollo del Milenio. In Humanismo y Trabajo Social: Vols 5 (93-101).Puig, V., Ocampo-Martínez, C., Pérez, R., Cembrano, G., Quevedo, J., & Escobet, T. (Eds.). (2017). Real-time Monitoring and Operational Control of DrinkingWater Systems. Springer International Publishing. https://doi.org/10.1007/9783-319-50751-4Quintana Fajardo, B. F., & Sarabia Caffroni, J. J. (2018). Arquitectura para el sistema de monitoreo de la calidad del agua de los caños y lagos internos del Distrito de Cartagena de Indias soportada en tecnologías de internet de las cosas. Universidad de CartagenaRad, R. (2018). Power BI Service Content. In Pro Power BI Architecture (pp. 29– 57). Apress. https://doi.org/10.1007/978-1-4842-4015-1_3Raghuvanshi, A., & Singh, U. K. (2020). Internet of Things for smart cities- security issues and challenges. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.10.849Rajanna, R. R., Natarajan, S., & Vittal, P. R. (2018). An IoT Wi-Fi Connected Sensor For Real Time Heart Rate Variability Monitoring. 2018 3rd International Conference on Circuits, Control, Communication and Computing (I4C), 1–4. https://doi.org/10.1109/CIMCA.2018.8739323Ratnaparkhi, S., Khan, S., Arya, C., Khapre, S., Singh, P., Diwakar, M., & Shankar, A. (2020). Smart agriculture sensors in IOT: A review. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2020.11.138Ray, P. P., Dash, D., & De, D. (2019). Internet of things-based real-time model study on e-healthcare: Device, message service and dew computing. Computer Networks, 149, 226–239. https://doi.org/10.1016/j.comnet.2018.12.006Asamblea General de las Naciones Unidas, Naciones Unidas 3 (2010).Rethlefsen, M. L., Kirtley, S., Waffenschmidt, S., Ayala, A. P., Moher, D., Page, M. J., & Koffel, J. B. (2021). PRISMA-S: an extension to the PRISMA Statement for Reporting Literature Searches in Systematic Reviews. Systematic Reviews, 10(1), 39. https://doi.org/10.1186/s13643-020-01542-zRey Graña, C., & Ramil Diaz, M. (2011). Series temporales. Introduccion a La Estadistica Descriptiva. Segunda Edicion, 85–105. https://doi.org/10.4272/978-84-9745-167-3.ch4Rojo-Nieto, E., & Montoto, T. (2017). Basuras marinas, plásticos y microplásticos orígenes, impactos y consecuencias de una amenaza global. Ecologistas en AcciónRondero, C., & Font, V. (2015). Articulación de la complejidad matemática de la media aritmética. Ensenanza de Las Ciencias, 33(2), 29–49. https://doi.org/10.5565/rev/ensciencias.1386Ruiz, C. A., Salazar, D. M., & Rodríguez González, N. (2020). La prestación de los servicios de agua potable y saneamiento básico en Colombia análisis y prospectiva. In Investigaciones y productos CIDRuiz, C. A., Salazar, D. M., & Rodríguez, N. (2020). The provision of drinking water and basic sanitation services in Colombia: analysis and prospective. Documentos FCE-CID Escuela de Economía, 34, 1–86. www.fce.unal.edu.co/centro-editorial/documentos.htmlRuiz Peláez, J. G., & Rodríguez Malagón, M. N. (2015). Población y muestra. Epidemiología Clínica: Investigación Clínica Aplicada, 62–66.Russo, C., Ramón, H., Alonso, N., Cicerchia, B., Esnaola, L., & Tessore, J. P. (2015). Tratamiento Masivo de Datos Utilizando Técnicas de Machine Learning Resumen Contexto Introducción. 131–134Samaranayake, P., Ramanathan, K., & Laosirihongthong, T. (2017). Implementing industry 4.0 — A technological readiness perspective. 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 529–533. https://doi.org/10.1109/IEEM.2017.8289947Saravanan, K., Anusuya, E., Kumar, R., & Son, L. H. (2018). Real-time water quality monitoring using Internet of Things in SCADA. Environmental Monitoring and Assessment, 190(9). https://doi.org/10.1007/s10661-018-6914xSchwaber, K. (2004). Agile Project Management with Scrum (Vol. 7, Issue CMM). https://doi.org/10.1201/9781420084191-c2Seamark, P., & Martens, T. (2019). Pro Dax with Power Bi: Business Intelligence with Powerpivot and SQL Server Analysis Services Tabular. Apress. https://doi.org/10.1007/978-1-4842-4897-3Sebastian, A. (2020). Smart Systems and IoT: Innovations in Computing. In A. K. Somani, R. S. Shekhawat, A. Mundra, S. Srivastava, & V. K. Verma (Eds.), Smart Innovation, Systems and Technologies. Springer Singapore. https://doi.org/10.1007/978-981-13-8406-6Serpanos, D., & Wolf, M. (2018). Internet-of-Things (IoT) Systems. In Internet-ofThings (IoT) Systems. Springer International Publishing. https://doi.org/10.1007/978-3-319-69715-4Serrano Castaño, C. E. (2002). Modelo integral para el profesional en ingeniería (Universidad del Cauca (Ed.)).Shaw, P. (2013). Postgres Succinctly. In Syncfusion IncSierra, C. A. (2011). Calidad del Agua. Evaluación y diagnóstico. In Journal of Chemical Information and Modeling. https://repository.udem.edu.co/handle/11407/2568Siow, E., Tiropanis, T., & Hall, W. (2018). Analytics for the Internet of Things. ACM Computing Surveys, 51(4), 1–36. https://doi.org/10.1145/3204947Spandana, K., & Rao, V. R. S. (2018). Internet of Things (Iot) Based smart water quality monitoring system. International Journal of Engineering and Technology(UAE), 7(3), 259–262. https://doi.org/10.14419/ijet.v7i3.6.14985Suresh, A., Nandagopal, M., Pethuru Raj, Neeba, E. A., & Lin, J.-W. (2020). Industrial IoT Application Architectures and Use Cases. Auerbach Publications.Suseendran, G., & Balaganesh, D. (2021). Smart cattle health monitoring system using IoT sensors. Materials Today: Proceedings. https://doi.org/https://doi.org/10.1016/j.matpr.2021.01.873Sutradhar, B. C. (2013). ISS-2012 Proceedings Volume On Longitudinal Data Analysis Subject to Measurement Errors, Missing Values, and/or Outliers (B. C. Sutradhar (Ed.); Vol. 211). Springer New York. https://doi.org/10.1007/9781-4614-6871-4Tanwar, S. (2020). Fog Data Analytics for IoT Applications: Next Generation Process Model with State of the Art Technologies (S. Tanwar (Ed.); Vol. 76). Springer Singapore. https://doi.org/10.1007/978-981-15-6044-6The Government Office for Science. (2014). The IoT: making the most of the Second Digital Revolution. WordLink, 1–40. https://doi.org/GS/14/1230Torres Pardo, J. C. (2017). Definition of a Reference Architecture for Information Systems in Ubiquitous Wireless Sensor Networks based on quality of service. Master’s Degree Option Work. Universidad Nacional de ColombiaTukey, J. W. (1962). The Future of Data Analysis. The annals of mathematical statistics.UNESCO. (2015). El Crecimiento Insostenible Y La Creciente Demanda Mundial De Agua. Wwdr, 12UNESCO. (2019). Informe Mundial de las Naciones Unidas sobre el Desarrollo de los Recursos Hídricos 2019. No dejar a nadie atrás. In Organización de las Naciones Unidas para la Educación, la Ciencia y la CulturaUNESCO. (2020). Informe Mundial de las Naciones Unidas sobre el Desarrollo de los Recursos Hídricos 2020. In Agua y Cambio ClimáticoUrrútia, G., & Bonfill, X. (2010). Declaración PRISMA: una propuesta para mejorar la publicación de revisiones sistemáticas y metaanálisis. Medicina Clínica, 135(11), 507–511. https://doi.org/10.1016/j.medcli.2010.01.015van Eck, N. J., & Waltman, L. (2011). Text mining and visualization using VOSviewer. Text Mining and Visualization, 1–5.van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070. https://doi.org/10.1007/s11192-017-2300-7Vélez, A., & Calvo, G. (1992). La investigación documental. Estado del arte y del conocimiento. Análisis de la investigación en la formación de investigadores. Universidad de la SabanaViegas, V., Pereira, J. M. D., Girao, P., Postolache, O., & Salgado, R. (2018). IoT applied to Environmental Monitoring in Oysters’ Farms. 2018 International Symposium in Sensing and Instrumentation in IoT Era (ISSI), 1–5. https://doi.org/10.1109/ISSI.2018.8538136Vikesland, P. J. (2018). Nanosensors for water quality monitoring. Nature Nanotechnology, 13(8), 651–660. https://doi.org/10.1038/s41565-018-0209-9Viloria, A., Acuña, G. C., Alcázar Franco, D. J., Hernández-Palma, H., Fuentes, J. P., & Rambal, E. P. (2019). Integration of Data Mining Techniques to PostgreSQL Database Manager System. Procedia Computer Science, 155, 575–580. https://doi.org/10.1016/j.procs.2019.08.080Wade, R. (2020). Advanced Analytics in Power BI with R and Python. Apress. https://doi.org/10.1007/978-1-4842-5829-3Water-quality engineering in natural systems: fate and transport processes in the water environment. (2013). Choice Reviews Online, 50(12), 50-6781-50–6781. https://doi.org/10.5860/choice.50-6781Weber, R. H., & Weber, R. (2010). Internet of Things. In Development. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-11710-7Weiser, M. (1991). The computer for the 21st century. Scientific American (International Edition), 265(3), 66–75. https://doi.org/10.1038/scientificamerican0991-94Wolf, W. H. W. H. (1994). Hardware-software co-design of embedded systems. Proceedings of the IEEE, 82(7), 967–989. https://doi.org/10.1109/5.293155Wong, B. P., & Kerkez, B. (2016). Real-time environmental sensor data: An application to water quality using web services. Environmental Modelling & Software, 84, 505–517. https://doi.org/10.1016/j.envsoft.2016.07.020World Health Organization. (2019). Safe water, better health. In Geneva: World Health Organization; 2019. Licence: CC BY-NC-SA 3.0 IGOWortham, R. H. (2020). Transparency for Robots and Autonomous Systems. The Institution of Engineering and TechnologyYanes, A. R., Martinez, P., & Ahmad, R. (2020). Towards automated aquaponics: A review on monitoring, IoT, and smart systems. Journal of Cleaner Production, 263, 121571. https://doi.org/https://doi.org/10.1016/j.jclepro.2020.121571Zelenakova, M., Hlavínek, P., & Negm, A. M. (2020). Management of Water Quality and Quantity. Springer International Publishing. https://doi.org/10.1007/978-3-030-18359-2Ziegler, A. (2014). In-situ Materials Characterization (A. Ziegler, H. Graafsma, X. F. Zhang, & J. W. M. Frenken (Eds.); Vol. 193). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-45152-2Zimányi, E., Sakr, M., & Lesuisse, A. (2020). MobilityDB: A Mobility Database Based on PostgreSQL and PostGIS. ACM Transactions on Database Systems, 45(4), 1–42. https://doi.org/10.1145/3406534Zou, Q., Xiong, Q., Li, Q., Yi, H., Yu, Y., & Wu, C. (2020). A water quality prediction method based on the multi-time scale bidirectional long short-term memory network. 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