System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops

Unmanned Aerial Vehicles (UAV) are part of precision agriculture; also, their impact on fast deployable wireless communication is offering new solutions and systems never envisioned before such as collecting information from underground sensors by using low power Internet of Things (IoT) technologie...

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Autores:
Castellanos, German
Deruyck, Margot
Martens, Luc
Joseph, Wout
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Escuela Colombiana de Ingeniería Julio Garavito
Repositorio:
Repositorio Institucional ECI
Idioma:
eng
OAI Identifier:
oai:repositorio.escuelaing.edu.co:001/1423
Acceso en línea:
https://repositorio.escuelaing.edu.co/handle/001/1423
https://doi.org/10.1109/access.2020.2982086
Palabra clave:
Internet de las cosas
Redes de sensores inalámbricos
Internet of things
Wireless sensor networks
Precision agriculture
NB-IoT
Unmanned aerial vehicles
Wireless underground sensor networks
Rights
openAccess
License
https://creativecommons.org/licenses/by/4.0/
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oai_identifier_str oai:repositorio.escuelaing.edu.co:001/1423
network_acronym_str ESCUELAIG2
network_name_str Repositorio Institucional ECI
repository_id_str
dc.title.eng.fl_str_mv System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
title System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
spellingShingle System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
Internet de las cosas
Redes de sensores inalámbricos
Internet of things
Wireless sensor networks
Precision agriculture
NB-IoT
Unmanned aerial vehicles
Wireless underground sensor networks
title_short System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
title_full System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
title_fullStr System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
title_full_unstemmed System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
title_sort System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops
dc.creator.fl_str_mv Castellanos, German
Deruyck, Margot
Martens, Luc
Joseph, Wout
dc.contributor.author.none.fl_str_mv Castellanos, German
Deruyck, Margot
Martens, Luc
Joseph, Wout
dc.contributor.researchgroup.spa.fl_str_mv Ecitrónica
dc.subject.armarc.spa.fl_str_mv Internet de las cosas
Redes de sensores inalámbricos
topic Internet de las cosas
Redes de sensores inalámbricos
Internet of things
Wireless sensor networks
Precision agriculture
NB-IoT
Unmanned aerial vehicles
Wireless underground sensor networks
dc.subject.armarc.eng.fl_str_mv Internet of things
Wireless sensor networks
dc.subject.proposal.eng.fl_str_mv Precision agriculture
NB-IoT
Unmanned aerial vehicles
Wireless underground sensor networks
description Unmanned Aerial Vehicles (UAV) are part of precision agriculture; also, their impact on fast deployable wireless communication is offering new solutions and systems never envisioned before such as collecting information from underground sensors by using low power Internet of Things (IoT) technologies. In this paper, we propose a (Narrow Band IoT) NB-IoT system for collecting underground soil parameters in potato crops using a UAV-aided network. To this end, a simulation tool implementing a gateway mounted on a UAV using NB-IoT based access network and LTE based backhaul network is developed. This tool evaluates the performance of a realistic scenario in a potato field near Bogota, Colombia, accounting for real size packets in a complete IoT application. While computing the wireless link quality, it allocates access and backhaul resources simultaneously based on the technologies used. We compare the performance of wireless underground sensors buried in dry and wet soils at four different depths. Results show that a single drone with 50 seconds of flight time could satisfy more than 2000 sensors deployed in a 20 hectares field, depending on the buried depth and soil characteristics. We found that an optimal flight altitude is located between 60 m and 80 m for buried sensors. Moreover, we establish that the water content reduces the maximum reachable buried depth from 70 cm in dry soils, down to 30 cm in wet ones. Besides, we found that in the proposed scenario, sensors' battery life could last up to 82 months for above ground sensors and 77 months for the deepest buried ones. Finally, we discuss the influence of the sensor's density and buried depth, the flight service time and altitude in power-constrained conditions and we propose optimal configuration to improve system performance.
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2021-05-12T14:18:45Z
2021-10-01T17:19:08Z
dc.date.available.none.fl_str_mv 2021-05-12T14:18:45Z
2021-10-01T17:19:08Z
dc.type.spa.fl_str_mv Artículo de revista
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identifier_str_mv 2169-3536
10.1109/ACCESS.2020.2982086
url https://repositorio.escuelaing.edu.co/handle/001/1423
https://doi.org/10.1109/access.2020.2982086
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationedition.spa.fl_str_mv Volumen 8, 2020.
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dc.relation.ispartofjournal.spa.fl_str_mv IEEE Access
dc.relation.references.spa.fl_str_mv Y. Zeng, R. Zhang and T. J. Lim, "Wireless communications with unmanned aerial vehicles: Opportunities and challenges", IEEE Commun. Mag., vol. 54, pp. 36-42, May 2016.
Y. Zeng, J. Lyu and R. Zhang, "Cellular-connected UAV: Potential challenges and promising technologies", IEEE Wireless Commun., vol. 26, no. 1, pp. 120-127, Feb. 2019.
M. Mozaffari, W. Saad, M. Bennis, Y.-H. Nam and M. Debbah, "A tutorial on UAVs for wireless networks: Applications challenges and open problems", arXiv:1803.00680, 2018, [online] Available: http://arxiv.org/abs/1803.00680.
N. H. Motlagh, T. Taleb and O. Arouk, "Low-altitude unmanned aerial vehicles-based Internet of Things services: Comprehensive survey and future perspectives", IEEE Internet Things J., vol. 3, no. 6, pp. 899-922, Dec. 2016.
X. Yu, P. Wu, W. Han and Z. Zhang, "A survey on wireless sensor network infrastructure for agriculture", Comput. Standards Interfaces, vol. 35, no. 1, pp. 59-64, Jan. 2013.
K. Goel and A. K. Bindal, "Wireless sensor network in precision agriculture: A survey report", Proc. 5th Int. Conf. Parallel Distrib. Grid Comput. (PDGC), pp. 176-181, Dec. 2018.
T. Ojha, S. Misra and N. S. Raghuwanshi, "Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges", Comput. Electron. Agricult., vol. 118, pp. 66-84, Oct. 2015.
X. Yu, P. Wu, W. Han and Z. Zhang, "Overview of wireless underground sensor networks for agriculture", Afr. J. Biotechnol., vol. 11, no. 17, pp. 3942-3948, Feb. 2012.
I. F. Akyildiz and E. P. Stuntebeck, "Wireless underground sensor networks: Research challenges", Ad Hoc Netw., vol. 4, no. 6, pp. 669-686, Nov. 2006.
H. Shakhatreh, A. H. Sawalmeh, A. Al-Fuqaha, Z. Dou, E. Almaita, I. Khalil, et al., "Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges", IEEE Access, vol. 7, pp. 48572-48634, 2019.
U. R. Mogili and B. B. V. L. Deepak, "Review on application of drone systems in precision agriculture", Procedia Comput. Sci., vol. 133, pp. 502-509, Jan. 2018.
S. Banu, "Precision agriculture: Tomorrow’s technology for today’s farmer", J. Food Process. Technol., vol. 6, no. 8, pp. 1-6, Jun. 2015.
U. Shafi, R. Mumtaz, J. García-Nieto, S. A. Hassan, S. A. R. Zaidi and N. Iqbal, "Precision agriculture techniques and practices: From considerations to applications", Sensors, vol. 19, no. 17, pp. 3796, Sep. 2019.
A. K. Saha, J. Saha, R. Ray, S. Sircar, S. Dutta, S. P. Chattopadhyay, et al., "IoT-based drone for improvement of crop quality in agricultural field", Proc. IEEE 8th Annu. Comput. Commun. Workshop Conf. (CCWC), pp. 1-4, Jan. 2018.
The EU Potato Sector |Europatat, Nov. 2019, [online] Available: https://europatat.eu/activities/the-eu-potato-sector/.
Boletin Mensual Regional No08, Bogotá, Colombia, 2018.
El cultivo de la papa (Solanum tuberosum L.) y un estudio de caso de los costos de producción de papa Pastusa Suprema, Bogota, Colombia, vol. 55, Jan. 2017.
Potato | Land & Water | Food and Agriculture Organization of the United Nations | Land & Water | Food and Agriculture Organization of the United Nations, Nov. 2019, [online] Available: http://www.fao.org/land-water/databases-and-software/crop-information/potato/en/.
Aqeel-ur-Rehman, A. Z. Abbasi, N. Islam and Z. A. Shaikh, "A review of wireless sensors and networks’ applications in agriculture", Comput. Standards Interfaces, vol. 36, no. 2, pp. 263-270, Feb. 2014.
H. Jawad, R. Nordin, S. Gharghan, A. Jawad and M. Ismail, "Energy-efficient wireless sensor networks for precision agriculture: A review", Sensors, vol. 17, no. 8, pp. 1781, Aug. 2017.
A. Salam and S. Shah, "Internet of Things in smart agriculture: Enabling technologies", Proc. IEEE 5th World Forum Internet Things (WF-IoT), pp. 692-695, Apr. 2019.
M. Ayaz, M. Ammad-Uddin, Z. Sharif, A. Mansour and E.-H.-M. Aggoune, "Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk", IEEE Access, vol. 7, pp. 129551-129583, 2019.
C.-R. Rad, O. Hancu, I.-A. Takacs and G. Olteanu, "Smart monitoring of potato crop: A cyber-physical system architecture model in the field of precision agriculture", Agricult. Agricult. Sci. Procedia, vol. 6, pp. 73-79, Jan. 2015.
Y. Suleman, R. V. Manurung, D. Kurniawan, I. D. P. Hermida and A. Heryana, "Development of precision farming using modular multi node sensor", Proc. Int. Conf. Radar Antenna Microw. Electron. Telecommun. (ICRAMET), pp. 99-103, Nov. 2018.
H. Gao, Y. Xu, Y. Yin, W. Zhang, R. Li and X. Wang, "Context-aware QoS prediction with neural collaborative filtering for Internet-of-Things services", IEEE Internet Things J., Dec. 2, 2019.
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spelling Castellanos, Germanf7fe8d4e940fb92b121fa70333515d0a600Deruyck, Margot5f9cd89b20ceca784214b206147f2adf600Martens, Luc9fedb037e06697211fc4df61a264102a600Joseph, Woutc3d8535a86ff89c7fbd729a7c4ec1ce1600Ecitrónica2021-05-12T14:18:45Z2021-10-01T17:19:08Z2021-05-12T14:18:45Z2021-10-01T17:19:08Z20202169-3536https://repositorio.escuelaing.edu.co/handle/001/142310.1109/ACCESS.2020.2982086https://doi.org/10.1109/access.2020.2982086Unmanned Aerial Vehicles (UAV) are part of precision agriculture; also, their impact on fast deployable wireless communication is offering new solutions and systems never envisioned before such as collecting information from underground sensors by using low power Internet of Things (IoT) technologies. In this paper, we propose a (Narrow Band IoT) NB-IoT system for collecting underground soil parameters in potato crops using a UAV-aided network. To this end, a simulation tool implementing a gateway mounted on a UAV using NB-IoT based access network and LTE based backhaul network is developed. This tool evaluates the performance of a realistic scenario in a potato field near Bogota, Colombia, accounting for real size packets in a complete IoT application. While computing the wireless link quality, it allocates access and backhaul resources simultaneously based on the technologies used. We compare the performance of wireless underground sensors buried in dry and wet soils at four different depths. Results show that a single drone with 50 seconds of flight time could satisfy more than 2000 sensors deployed in a 20 hectares field, depending on the buried depth and soil characteristics. We found that an optimal flight altitude is located between 60 m and 80 m for buried sensors. Moreover, we establish that the water content reduces the maximum reachable buried depth from 70 cm in dry soils, down to 30 cm in wet ones. Besides, we found that in the proposed scenario, sensors' battery life could last up to 82 months for above ground sensors and 77 months for the deepest buried ones. Finally, we discuss the influence of the sensor's density and buried depth, the flight service time and altitude in power-constrained conditions and we propose optimal configuration to improve system performance.Los vehículos aéreos no tripulados (UAV) forman parte de la agricultura de precisión; además, su impacto en la comunicación inalámbrica de rápido despliegue está ofreciendo nuevas soluciones y sistemas nunca antes previstos, como la recogida de información de sensores subterráneos mediante el uso de tecnologías del Internet de las cosas (IoT) de baja potencia. En este trabajo, proponemos un sistema (Narrow Band IoT) NB-IoT para la recogida de parámetros del suelo subterráneo en cultivos de patata utilizando una red asistida por UAV. Para ello, se desarrolla una herramienta de simulación que implementa una pasarela montada en un UAV utilizando una red de acceso basada en NB-IoT y una red de retorno basada en LTE. Esta herramienta evalúa el rendimiento de un escenario realista en un campo de patatas cerca de Bogotá, Colombia, teniendo en cuenta paquetes de tamaño real en una aplicación completa de IoT. Mientras computa la calidad del enlace inalámbrico, asigna los recursos de acceso y backhaul simultáneamente basándose en las tecnologías utilizadas. Comparamos el rendimiento de los sensores inalámbricos subterráneos enterrados en suelos secos y húmedos a cuatro profundidades diferentes. Los resultados muestran que un solo dron con 50 segundos de vuelo podría satisfacer a más de 2000 sensores desplegados en un campo de 20 hectáreas, dependiendo de la profundidad enterrada y de las características del suelo. Encontramos que una altitud de vuelo óptima se sitúa entre 60 m y 80 m para los sensores enterrados. Además, establecemos que el contenido de agua reduce la profundidad máxima alcanzable enterrada de 70 cm en suelos secos, hasta 30 cm en los húmedos. Además, descubrimos que en el escenario propuesto, la vida de la batería de los sensores podría durar hasta 82 meses para los sensores en superficie y 77 meses para los más enterrados. Por último, analizamos la influencia de la densidad del sensor y la profundidad de enterrado, el tiempo de servicio de vuelo y la altitud en condiciones de energía limitada y proponemos una configuración óptima para mejorar el rendimiento del sistema.1 Department of Electronics Engineering, Colombian School of Engineering, Bogota 111166, Colombia 2 IMEC, Department of Information Technology, Ghent University, 9052 Ghent, Belgium Corresponding author: German Castellanos (german.castellanos@ugent.be) The work of German Castellanos was supported in part by the Colfuturo (Fundación para el futuro de Colombia), and in part by the Colombian School of Engineering – Julio Garavito, Doctoral scholarship Colfuturo-PCB 2018.14 páginasapplication/pdfengIEEEFundación para el futuro de Colombia, Colombia.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessAtribución 4.0 Internacional (CC BY 4.0)http://purl.org/coar/access_right/c_abf2https://ieeexplore.ieee.org/document/9042335System Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato CropsArtículo de revistainfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85Volumen 8, 2020.56836568238N/AIEEE AccessY. Zeng, R. Zhang and T. J. Lim, "Wireless communications with unmanned aerial vehicles: Opportunities and challenges", IEEE Commun. Mag., vol. 54, pp. 36-42, May 2016.Y. Zeng, J. Lyu and R. Zhang, "Cellular-connected UAV: Potential challenges and promising technologies", IEEE Wireless Commun., vol. 26, no. 1, pp. 120-127, Feb. 2019.M. Mozaffari, W. Saad, M. Bennis, Y.-H. Nam and M. Debbah, "A tutorial on UAVs for wireless networks: Applications challenges and open problems", arXiv:1803.00680, 2018, [online] Available: http://arxiv.org/abs/1803.00680.N. H. Motlagh, T. Taleb and O. Arouk, "Low-altitude unmanned aerial vehicles-based Internet of Things services: Comprehensive survey and future perspectives", IEEE Internet Things J., vol. 3, no. 6, pp. 899-922, Dec. 2016.X. Yu, P. Wu, W. Han and Z. Zhang, "A survey on wireless sensor network infrastructure for agriculture", Comput. Standards Interfaces, vol. 35, no. 1, pp. 59-64, Jan. 2013.K. Goel and A. K. Bindal, "Wireless sensor network in precision agriculture: A survey report", Proc. 5th Int. Conf. Parallel Distrib. Grid Comput. (PDGC), pp. 176-181, Dec. 2018.T. Ojha, S. Misra and N. S. Raghuwanshi, "Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges", Comput. Electron. Agricult., vol. 118, pp. 66-84, Oct. 2015.X. Yu, P. Wu, W. Han and Z. Zhang, "Overview of wireless underground sensor networks for agriculture", Afr. J. Biotechnol., vol. 11, no. 17, pp. 3942-3948, Feb. 2012.I. F. Akyildiz and E. P. Stuntebeck, "Wireless underground sensor networks: Research challenges", Ad Hoc Netw., vol. 4, no. 6, pp. 669-686, Nov. 2006.H. Shakhatreh, A. H. Sawalmeh, A. Al-Fuqaha, Z. Dou, E. Almaita, I. Khalil, et al., "Unmanned aerial vehicles (UAVs): A survey on civil applications and key research challenges", IEEE Access, vol. 7, pp. 48572-48634, 2019.U. R. Mogili and B. B. V. L. Deepak, "Review on application of drone systems in precision agriculture", Procedia Comput. Sci., vol. 133, pp. 502-509, Jan. 2018.S. Banu, "Precision agriculture: Tomorrow’s technology for today’s farmer", J. Food Process. Technol., vol. 6, no. 8, pp. 1-6, Jun. 2015.U. Shafi, R. Mumtaz, J. García-Nieto, S. A. Hassan, S. A. R. Zaidi and N. Iqbal, "Precision agriculture techniques and practices: From considerations to applications", Sensors, vol. 19, no. 17, pp. 3796, Sep. 2019.A. K. Saha, J. Saha, R. Ray, S. Sircar, S. Dutta, S. P. Chattopadhyay, et al., "IoT-based drone for improvement of crop quality in agricultural field", Proc. IEEE 8th Annu. Comput. Commun. Workshop Conf. (CCWC), pp. 1-4, Jan. 2018.The EU Potato Sector |Europatat, Nov. 2019, [online] Available: https://europatat.eu/activities/the-eu-potato-sector/.Boletin Mensual Regional No08, Bogotá, Colombia, 2018.El cultivo de la papa (Solanum tuberosum L.) y un estudio de caso de los costos de producción de papa Pastusa Suprema, Bogota, Colombia, vol. 55, Jan. 2017.Potato | Land & Water | Food and Agriculture Organization of the United Nations | Land & Water | Food and Agriculture Organization of the United Nations, Nov. 2019, [online] Available: http://www.fao.org/land-water/databases-and-software/crop-information/potato/en/.Aqeel-ur-Rehman, A. Z. Abbasi, N. Islam and Z. A. Shaikh, "A review of wireless sensors and networks’ applications in agriculture", Comput. Standards Interfaces, vol. 36, no. 2, pp. 263-270, Feb. 2014.H. Jawad, R. Nordin, S. Gharghan, A. Jawad and M. Ismail, "Energy-efficient wireless sensor networks for precision agriculture: A review", Sensors, vol. 17, no. 8, pp. 1781, Aug. 2017.A. Salam and S. Shah, "Internet of Things in smart agriculture: Enabling technologies", Proc. IEEE 5th World Forum Internet Things (WF-IoT), pp. 692-695, Apr. 2019.M. Ayaz, M. Ammad-Uddin, Z. Sharif, A. Mansour and E.-H.-M. Aggoune, "Internet-of-Things (IoT)-based smart agriculture: Toward making the fields talk", IEEE Access, vol. 7, pp. 129551-129583, 2019.C.-R. Rad, O. Hancu, I.-A. Takacs and G. Olteanu, "Smart monitoring of potato crop: A cyber-physical system architecture model in the field of precision agriculture", Agricult. Agricult. Sci. Procedia, vol. 6, pp. 73-79, Jan. 2015.Y. Suleman, R. V. Manurung, D. Kurniawan, I. D. P. Hermida and A. Heryana, "Development of precision farming using modular multi node sensor", Proc. Int. Conf. Radar Antenna Microw. Electron. Telecommun. (ICRAMET), pp. 99-103, Nov. 2018.H. Gao, Y. Xu, Y. Yin, W. Zhang, R. Li and X. Wang, "Context-aware QoS prediction with neural collaborative filtering for Internet-of-Things services", IEEE Internet Things J., Dec. 2, 2019.Internet de las cosasRedes de sensores inalámbricosInternet of thingsWireless sensor networksPrecision agricultureNB-IoTUnmanned aerial vehiclesWireless underground sensor networksTEXT10.1109ACCESS.2020.2982086.pdf.txt10.1109ACCESS.2020.2982086.pdf.txtExtracted texttext/plain74438https://repositorio.escuelaing.edu.co/bitstream/001/1423/3/10.1109ACCESS.2020.2982086.pdf.txtcd8f33e87136e3f1d6f77acb0b697055MD53open accessSystem Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops.pdf.txtSystem Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops.pdf.txtExtracted texttext/plain74438https://repositorio.escuelaing.edu.co/bitstream/001/1423/5/System%20Assessment%20of%20WUSN%20Using%20NB-IoT%20UAV-Aided%20Networks%20in%20Potato%20Crops.pdf.txtcd8f33e87136e3f1d6f77acb0b697055MD55open accessTHUMBNAIL10.1109ACCESS.2020.2982086.pdf.jpg10.1109ACCESS.2020.2982086.pdf.jpgGenerated Thumbnailimage/jpeg17330https://repositorio.escuelaing.edu.co/bitstream/001/1423/4/10.1109ACCESS.2020.2982086.pdf.jpga653e83899f5b3360ad8d2ebf4e3dc96MD54open accessSystem Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops.pdf.jpgSystem Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops.pdf.jpgGenerated Thumbnailimage/jpeg17330https://repositorio.escuelaing.edu.co/bitstream/001/1423/6/System%20Assessment%20of%20WUSN%20Using%20NB-IoT%20UAV-Aided%20Networks%20in%20Potato%20Crops.pdf.jpga653e83899f5b3360ad8d2ebf4e3dc96MD56open accessLICENSElicense.txttext/plain1881https://repositorio.escuelaing.edu.co/bitstream/001/1423/1/license.txt5a7ca94c2e5326ee169f979d71d0f06eMD51open accessORIGINALSystem Assessment of WUSN Using NB-IoT UAV-Aided Networks in Potato Crops.pdfapplication/pdf9900329https://repositorio.escuelaing.edu.co/bitstream/001/1423/2/System%20Assessment%20of%20WUSN%20Using%20NB-IoT%20UAV-Aided%20Networks%20in%20Potato%20Crops.pdf8d8224dd874d0ccc312caae6a54e73a4MD52open access001/1423oai:repositorio.escuelaing.edu.co:001/14232022-08-02 03:01:12.17open accessRepositorio Escuela Colombiana de Ingeniería Julio Garavitorepositorio.eci@escuelaing.edu.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