Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial
ilustraciones, diagramas, fotografías
- Autores:
-
Beltrán Huertas, Diana Catalina
- Tipo de recurso:
- Fecha de publicación:
- 2024
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/86103
- Palabra clave:
- 620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería
Sensor de bajo costo
Multiparámetro
PH
Temperatura
Conductividad
Evaluación
Smart sensor
Low-cost sensor
Multiparameter
Temperature
Conductivity
Assessment
Escorrentía
Ingeniería de drenaje
Runoff
Drainage engineering
sensor
sensor
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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| dc.title.spa.fl_str_mv |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| dc.title.translated.eng.fl_str_mv |
Assessment of a low-cost Smart Sensors system for surface runoff monitoring |
| title |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| spellingShingle |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial 620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería Sensor de bajo costo Multiparámetro PH Temperatura Conductividad Evaluación Smart sensor Low-cost sensor Multiparameter Temperature Conductivity Assessment Escorrentía Ingeniería de drenaje Runoff Drainage engineering sensor sensor |
| title_short |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| title_full |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| title_fullStr |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| title_full_unstemmed |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| title_sort |
Evaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficial |
| dc.creator.fl_str_mv |
Beltrán Huertas, Diana Catalina |
| dc.contributor.advisor.spa.fl_str_mv |
Mancipe Munoz, Nestor Alonso |
| dc.contributor.author.spa.fl_str_mv |
Beltrán Huertas, Diana Catalina |
| dc.contributor.researchgroup.spa.fl_str_mv |
Grupo de Investigación en Ingeniería de Recursos Hidrícos Gireh |
| dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería |
| topic |
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería Sensor de bajo costo Multiparámetro PH Temperatura Conductividad Evaluación Smart sensor Low-cost sensor Multiparameter Temperature Conductivity Assessment Escorrentía Ingeniería de drenaje Runoff Drainage engineering sensor sensor |
| dc.subject.proposal.spa.fl_str_mv |
Sensor de bajo costo Multiparámetro PH Temperatura Conductividad Evaluación |
| dc.subject.proposal.eng.fl_str_mv |
Smart sensor Low-cost sensor Multiparameter Temperature Conductivity Assessment |
| dc.subject.unesco.spa.fl_str_mv |
Escorrentía Ingeniería de drenaje |
| dc.subject.unesco.eng.fl_str_mv |
Runoff Drainage engineering |
| dc.subject.wikidata.spa.fl_str_mv |
sensor |
| dc.subject.wikidata.eng.fl_str_mv |
sensor |
| description |
ilustraciones, diagramas, fotografías |
| publishDate |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-05-16T22:28:24Z |
| dc.date.available.none.fl_str_mv |
2024-05-16T22:28:24Z |
| dc.date.issued.none.fl_str_mv |
2024 |
| dc.type.spa.fl_str_mv |
Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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info:eu-repo/semantics/acceptedVersion |
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Text |
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http://purl.org/redcol/resource_type/TM |
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acceptedVersion |
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https://repositorio.unal.edu.co/handle/unal/86103 |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
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https://repositorio.unal.edu.co/handle/unal/86103 https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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spa |
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spa |
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Abbas, O., Abou Rjeily, Y., Sadek, M., & Shahrour, I. (2017). A large-scale experimentation of the smart sewage system. Water and Environment Journal, 31(4), 515–521. https://doi.org/10.1111/WEJ.12273 Adla, S., Rai, N. K., Karumanchi, S. H., Tripathi, S., Disse, M., & Pande, S. (2020). Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors. Sensors 2020, Vol. 20, Page 363, 20(2), 363. https://doi.org/10.3390/S20020363 Agade, P., & Bean, E. (2023). GatorByte-An Internet of Things-Based Low-Cost, Compact, and Real-Time Water Resource Monitoring Buoy Specifications table. HardwareX, 14, e00427. https://doi.org/10.1016/j.ohx.2023.e00427 AgriMetSoft. (2019). Root Mean Square Error Calculator. https://agrimetsoft.com/calculators/Root%20Mean%20Square%20Error# Ahmed, U., Mumtaz, R., Anwar, H., Mumtaz, S., & Qamar, A. M. (2020). Water quality monitoring: from conventional to emerging technologies. Water Supply, 20(1), 28– 45. https://doi.org/10.2166/WS.2019.144 Ali, A. N. A., Khan, M. Y. M. A., Bolong, N., Maarof, K. A., & Tanalol, S. H. (2020, September 26). conceptual and design framework for smart stormwater filtration. IEEE international conference on artificial intelligence in engineering and technology, iicaiet 2020. https://doi.org/10.1109/iicaiet49801.2020.9257828 Almetwally, S. A. H., Hassan, M. K., & Mourad, M. H. (2020). Real Time Internet of Things (IoT) Based Water Quality Management System. Procedia CIRP, 91, 478–485. https://doi.org/10.1016/J.PROCIR.2020.03.107 American Public Health Association (APHA). (2005). Standard method for examination of water and wastewater. https://www.standardmethods.org/ 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 Assendelft, R. S., & Ilja van Meerveld, H. J. (2019). a low-cost, multi-sensor system to monitor temporary stream dynamics in mountainous headwater catchments. sensors (switzerland), 19(21). https://doi.org/10.3390/s19214645 Barbosa, A. E., Fernandes, J. N., & David, L. M. (2012). Key issues for sustainable urban stormwater management. Water Research, 46(20), 6787–6798. https://doi.org/10.1016/j.watres.2012.05.029 Bartos, M., Wong, B., & Kerkez, B. (2018). Open storm: a complete framework for sensing and control of urban watersheds. Environmental Science: Water Research & Technology, 4(3), 346–358. https://doi.org/10.1039/C7EW00374A Berndtsson, J. C. (2010). Green roof performance towards management of runoff water quantity and quality: A review. Ecological Engineering, 36, 351–360. https://doi.org/10.1016/j.ecoleng.2009.12.014 Camarena Gamarra, P. A. (2022). Desarrollo de una red LoRaWAN® para IoT Castro, J. (2012). Validación parámetros de pH y conductividad en aguas superficiales y residuales domesticas en el laboratorio de ambiental de la CRC bajo la norma NTCISO/IEC 17025. http://repositorio.unicauca.edu.co:8080/bitstream/handle/123456789/7307/Validaci% C3%B3n%20par%C3%A1metros%20de%20pH%20y%20conductividad%20en%20a guas%20superficiales%20y%20residuales%20domesticas.pdf?sequence=1&isAllow ed=y Chen, T., Wang, M., Su, J., Ikram, R. M. A., & Li, J. (2023). Application of Internet of Things (IoT) Technologies in Green Stormwater Infrastructure (GSI): A Bibliometric Review. Sustainability, 15(18), 13317. https://doi.org/10.3390/su151813317 Delgado, A., Briciu-Burghina, C., & Regan, F. (2021). Antifouling Strategies for Sensors Used in Water Monitoring: Review and Future Perspectives. Sensors 2021, Vol. 21, Page 389, 21(2), 389. https://doi.org/10.3390/S21020389 DFRobot. (2023). Liquid Sensor. https://www.dfrobot.com/category-68.html Fell, J., Pead, J., & Winter, K. (2019). low-cost flow sensors: making smart water monitoring technology affordable. IEEE Consumer Electronics Magazine, 8(1), 72– 77. https://doi.org/10.1109/MCE.2018.2867984 FL0 - backend engineering, supercharged. (n.d.). Retrieved January 28, 2024, from https://www.fl0.com/ Giraldo, M., Jiménez Ariza, S., Martínez, J., Ramírez, P., Rodríguez Sánchez, J., Camacho-Botero, L., & Diazgranados, M. (2019). (PDF) Quantifying the performance of a SUDS treatment train. A case-study of San Cristobal Park, Bogotá (Colombia). https://www.researchgate.net/publication/336767584_Quantifying_the_performance_ of_a_SUDS_treatment_train_A_casestudy_of_San_Cristobal_Park_Bogota_Colombia HANNA. (2023). HI 9829 Medidor Multiparámetro Impermeable para pH / ISE / CE / OD / Turbidez con Opción de GPS | HANNA Instruments Colombia. HANNA. https://www.hannacolombia.com/productos/producto/hi-9829-medidormultiparametro-impermeable-para-ph-ise-ce-od-turbidez-con-opcion-de-gps Hanna. (2023). HI 9829 Medidor Multiparámetro Impermeable para pH / ISE / CE / OD / Turbidez con Opción de GPS | HANNA Instruments Colombia. https://www.hannacolombia.com/productos/producto/hi-9829-medidormultiparametro-impermeable-para-ph-ise-ce-od-turbidez-con-opcion-de-gps Ideam, & Invemar. (2021). Protocolo de monitoreo y seguimiento del agua. In Ideam, Invemar. Lakshmikantha, V., Hiriyannagowda, A., Manjunath, A., Patted, A., Basavaiah, J., & Anthony, A. A. (2021). IoT based smart water quality monitoring system. Global Transitions Proceedings, 2, 181–186. https://doi.org/10.1016/j.gltp.2021.08.062 Lambrou, T. P., Anastasiou, C. C., Panayiotou, C. G., & Polycarpou, M. M. (2014). a lowcost sensor network for real-time monitoring and contamination detection in drinking water distribution systems. IEEE Sensors Journal, 14(8), 2765–2772. https://doi.org/10.1109/JSEN.2014.2316414 Linjama, J., Puustinen, M., Koskiaho, J., Sirkka, T., Kotilainen, H., & Granlund, K. (2009). implementation of automatic sensors for continuous monitoring of runoff quantity and quality in small catchments. Agricultural and Food Science, 18(3–4), 417–427. https://doi.org/10.23986/afsci.5957 Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H. J., Kumar, S., Moradkhani, H., Seo, D. J., Schwanenberg, D., Smith, P., Van Dijk, A. I. J. M., Van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., & Restrepo, P. (2012). advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities. Hydrology and Earth System Sciences, 16(10), 3863–3887. https://doi.org/10.5194/hess-16-3863-2012 Malek, K., Ortíz Rodríguez, E., Lee, Y.-C., Murillo, J., Mohammadkhorasani, A., Vigil, L., Zhang, S., & Moreu, F. (2023). Design and implementation of sustainable solar energy harvesting for low-cost remote sensors equipped with real-time monitoring systems. Journal of Infrastructure Intelligence and Resilience, 2(3), 100051. https://doi.org/10.1016/J.IINTEL.2023.100051 Mancipe, N., Beltrán, D., Sandoval, J., Riaño, M. F., Rodríguez, E., Castañeda, P., & Alarcón, E. (2022). Evaluación del impacto hidrológico y ambiental de sistemas urbanos de drenaje sostenible (SUDS), caso de estudio en el campus de la Universidad Nacional de Colombia - Sede Bogotá Montenegro, A. (2016). Desarrollo de un sistema de monitoreo de la calidad del agua utilizando sensores capacitivos de bajo costo (Tesis de maestría). Pontificia Universidad Javeriana, Murphy, K., Heery, B., Sullivan, T., Zhang, D., Paludetti, L., Lau, K. T., Diamond, D., Costa, E., O’Connor, N., & Regan, F. (2015). a low-cost autonomous optical sensor for water quality monitoring. Talanta, 132, 520–527. https://doi.org/10.1016/j.talanta.2014.09.045 O’Flynn, B., Martínez-Català, R., Harte, S., O’Mathuna, C., Geary, J., Slater, C., Regan, F., Diamond, D., & Murphy, H. (2007). SmartCoast: A Wireless Sensor Network for water quality monitoring. Proceedings - Conference on Local Computer Networks, LCN, 815–816. https://doi.org/10.1109/LCN.2007.151 Parra, L., Rocher, J., Escrivá, J., & Lloret, J. (2018). design and development of low cost smart turbidity sensor for water quality monitoring in fish farms. Aquacultural Engineering, 81, 10–18. https://doi.org/10.1016/j.aquaeng.2018.01.004 Poquita-Du, R. C., Morgia Du, I. P., & Todd, P. A. (2023). EmerSense: A low-cost multiparameter logger to monitor occurrence and duration of emersion events within intertidal zones. HardwareX, 14, e00410. https://doi.org/10.1016/J.OHX.2023.E00410 Raja, L., Shanthi, G., & Periasamy, P. S. (2019). internet of things based real time water monitoring system. International Journal of Recent Technology and Engineering, 8(2), 1368–1372. https://doi.org/10.35940/ijrte.B2026.078219 Rasin, Z., & Rizal Abdullah, M. (2012). water quality monitoring system using zigbee based wireless sensor network grid-connected quasi-z-source photovoltaic inverter with energy storage view project water quality monitoring system using zigbee based wireless sensor network. https://www.researchgate.net/publication/228785823 Rizzo, A., Bresciani, R., Martinuzzi, N., & Masi, F. (2020). Online monitoring of a longterm full-scale constructed wetland for the treatment of winery wastewater in Italy. Applied Sciences (Switzerland), 10(2), 555. https://doi.org/10.3390/app10020555 Salam, A. E. U., Sadjad, R. S. oed, Rezkullah, F. A. S., & Fakhri, M. (2019). online hydraulic parameter monitoring system in water distribution network. ICIC Express Letters, Part B: Applications, 10(12), 1037–1045. https://doi.org/10.24507/icicelb.10.12.1037 Salim, T. I., Haiyunnisa, T., & Alam, H. S. (2017). design and implementation of water quality monitoring for eel fish aquaculture. 2016 International Symposium on Electronics and Smart Devices, ISESD 2016, 208–213. https://doi.org/10.1109/ISESD.2016.7886720 SDA. (2020). SISISTEMAS URBANOS DE DRENAJE SOSTENIBLE (SUDS). Seders, L. A., Shea, C. A., Lemmon, M. D., Maurice, P. A., & Talley, J. W. (2007). LakeNet: An Integrated Sensor Network for Environmental Sensing in Lakes. Https://Home.Liebertpub.Com/Ees, 24(2), 183–191. https://doi.org/10.1089/EES.2006.0044 Valle, L. (2017). Sensor de nivel de agua con Arduino utilizando ultrasonidos. https://programarfacil.com/blog/arduino-blog/sensor-de-nivel-de-agua-con-arduino/ Vijayakumar, N., & Ramya, R. (2015, July 15). the real time monitoring of water quality in iot environment. IEEE International Conference on Circuit, Power and Computing Technologies, ICCPCT 2015. https://doi.org/10.1109/ICCPCT.2015.7159459 Zita, A. (2018). Diferencia entre exactitud y precisión - Diferenciador. https://www.diferenciador.com/diferencia-entre-exactitud-y-precision/ |
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Bogotá - Ingeniería - Maestría en Ingeniería - Recursos Hidráulicos |
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Bogotá, Colombia |
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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Mancipe Munoz, Nestor Alonso1ec21831856a251e487e482eccfdde47600Beltrán Huertas, Diana Catalinafff374cb8ffee4ea9021ef480098d2fcGrupo de Investigación en Ingeniería de Recursos Hidrícos Gireh2024-05-16T22:28:24Z2024-05-16T22:28:24Z2024https://repositorio.unal.edu.co/handle/unal/86103Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramas, fotografíasEl seguimiento de la escorrentía superficial, especialmente en relación con las estructuras que gestionan este fenómeno tales como los sistemas urbanos de drenaje sostenible (SUDS), ha experimentado un notable interés en la última década. Los sensores de bajo costo han surgido como herramientas esenciales para la monitorización del agua y los SUDS, siendo empleados por diversos investigadores. Estas herramientas, han tenido una aplicación limitada en investigaciones colombianas, específicamente en el monitoreo de SUDS. Es por esto que surge la pregunta de investigación: ¿cuáles son las ventajas y desventajas de los Smart Sensors en el seguimiento de la escorrentía superficial y su aplicabilidad en SUDS en tiempo casi real? Para abordar esta pregunta, la presente investigación evalúa un sistema de Smart sensor que incluye mediciones de pH, conductividad y temperatura en escenarios tales como en laboratorio, en muestreo in-situ y en muestreo continuo. Los resultados obtenidos revelan que el desempeño (en términos de exactitud y precisión) del Smart sensor es comparable al de un multiparámetro comercial en mediciones puntuales, con un ahorro del 80% del costo. Sin embargo, se identifican desafíos en la transmisión de datos en entornos con conectividad limitada para escenarios de monitoreo continuo. Estos hallazgos indican que, si bien los sensores de bajo costo son viables para medición puntual, aún existen obstáculos para su implementación en medición continua y en tiempo real. Esta investigación no solo contribuye al avance del monitoreo de SUDS en Bogotá mediante la adopción de sensores de bajo costo, sino que también señala un potencial significativo para investigaciones futuras centradas en la mejora de la implementación en medición continua de estos sensores. (Texto tomado de la fuente).The surface runoff monitoring related to structures such as Sustainable Urban Drainage Systems (SUDS) has increased significantly in the past decade. Low-cost sensors have emerged as essential tools for water and SUDS monitoring, widely adopted by various researchers. However, these tools have seen limited application in Colombian research, specifically in SUDS monitoring. The research question to be addressed is: What are the advantages and disadvantages of Smart Sensors for monitoring surface runoff and its applicability for monitoring SUDS in near-real-time? This research evaluates a Smart Sensor system for measuring pH, conductivity, and temperature in scenarios such as: laboratory, in-situ sampling, and continuous monitoring. The results point out that the Smart Sensor's performance is similar to that of a commercial multiparameter for punctual monitoring, saving 80% of its cost. However, challenges in data transmission are identified for environments with limited connectivity in continuous monitoring circumstances. These findings suggest that while low-cost sensors show promise for punctual measurements, obstacles persist for continuous and real-time implementation. This research not only contributes to advance in SUDS monitoring in Bogotá by using low-cost sensors but also demonstrates its potential for future research to enhance implementation of continuous monitoring of these type sensors.MaestríaMagíster en Ingeniería - Recursos HidráulicosModelación de fenómenos y amenazas naturales96 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Recursos HidráulicosFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingenieríaSensor de bajo costoMultiparámetroPHTemperaturaConductividadEvaluaciónSmart sensorLow-cost sensorMultiparameterTemperatureConductivityAssessmentEscorrentíaIngeniería de drenajeRunoffDrainage engineeringsensorsensorEvaluación de un sistema Smart Sensors de bajo costo para el monitoreo de la escorrentía superficialAssessment of a low-cost Smart Sensors system for surface runoff monitoringTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAbbas, O., Abou Rjeily, Y., Sadek, M., & Shahrour, I. (2017). A large-scale experimentation of the smart sewage system. Water and Environment Journal, 31(4), 515–521. https://doi.org/10.1111/WEJ.12273Adla, S., Rai, N. K., Karumanchi, S. H., Tripathi, S., Disse, M., & Pande, S. (2020). Laboratory Calibration and Performance Evaluation of Low-Cost Capacitive and Very Low-Cost Resistive Soil Moisture Sensors. Sensors 2020, Vol. 20, Page 363, 20(2), 363. https://doi.org/10.3390/S20020363Agade, P., & Bean, E. (2023). GatorByte-An Internet of Things-Based Low-Cost, Compact, and Real-Time Water Resource Monitoring Buoy Specifications table. HardwareX, 14, e00427. https://doi.org/10.1016/j.ohx.2023.e00427AgriMetSoft. (2019). Root Mean Square Error Calculator. https://agrimetsoft.com/calculators/Root%20Mean%20Square%20Error#Ahmed, U., Mumtaz, R., Anwar, H., Mumtaz, S., & Qamar, A. M. (2020). Water quality monitoring: from conventional to emerging technologies. Water Supply, 20(1), 28– 45. https://doi.org/10.2166/WS.2019.144Ali, A. N. A., Khan, M. Y. M. A., Bolong, N., Maarof, K. A., & Tanalol, S. H. (2020, September 26). conceptual and design framework for smart stormwater filtration. IEEE international conference on artificial intelligence in engineering and technology, iicaiet 2020. https://doi.org/10.1109/iicaiet49801.2020.9257828Almetwally, S. A. H., Hassan, M. K., & Mourad, M. H. (2020). Real Time Internet of Things (IoT) Based Water Quality Management System. Procedia CIRP, 91, 478–485. https://doi.org/10.1016/J.PROCIR.2020.03.107American Public Health Association (APHA). (2005). Standard method for examination of water and wastewater. https://www.standardmethods.org/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 – BoyacáAssendelft, R. S., & Ilja van Meerveld, H. J. 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Diferencia entre exactitud y precisión - Diferenciador. https://www.diferenciador.com/diferencia-entre-exactitud-y-precision/Universidad Nacional de ColombiaInvestigadoresLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/86103/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1010209903.2024.pdf1010209903.2024.pdfTesis de Maestría en Ingeniería - Recursos Hidráulicosapplication/pdf3263563https://repositorio.unal.edu.co/bitstream/unal/86103/2/1010209903.2024.pdf5786bbb83029eafab688839ea808d78bMD52THUMBNAIL1010209903.2024.pdf.jpg1010209903.2024.pdf.jpgGenerated Thumbnailimage/jpeg4867https://repositorio.unal.edu.co/bitstream/unal/86103/3/1010209903.2024.pdf.jpgc321b5cc2e59046015559f33fb178645MD53unal/86103oai:repositorio.unal.edu.co:unal/861032024-05-16 23:04:54.015Repositorio Institucional Universidad Nacional de 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