Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo

El sector agrícola se encuentra entre los más beneficiados por la expansión del Internet de las Cosas (IoT), ya que permite recopilar y gestionar una gran cantidad de datos sobre el entorno de un cultivo. Este artículo presenta los resultados del diseño y la prueba de un prototipo de sistema de moni...

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Autores:
Martinez, Jorge Luis Diaz
Salcedo, Dixon
Mercado, Teobaldis
Quiñonez, Yadira
De la Hoz, Andrés Mejia
Tipo de recurso:
Article of investigation
Fecha de publicación:
2024
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
spa
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/13920
Acceso en línea:
https://hdl.handle.net/11323/13920
https://repositorio.cuc.edu.co/
Palabra clave:
Precision agriculture
Dashboard
ESP32
IoT
Sensors
Cloud monitoring
Agricultura de precisión
Sensores
Monitoreo en la nube
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
id RCUC2_35221a2c2ee2c38cd7049fd5cb9fb51d
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network_acronym_str RCUC2
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dc.title.spa.fl_str_mv Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
title Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
spellingShingle Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
Precision agriculture
Dashboard
ESP32
IoT
Sensors
Cloud monitoring
Agricultura de precisión
Sensores
Monitoreo en la nube
title_short Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
title_full Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
title_fullStr Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
title_full_unstemmed Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
title_sort Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo
dc.creator.fl_str_mv Martinez, Jorge Luis Diaz
Salcedo, Dixon
Mercado, Teobaldis
Quiñonez, Yadira
De la Hoz, Andrés Mejia
dc.contributor.author.none.fl_str_mv Martinez, Jorge Luis Diaz
Salcedo, Dixon
Mercado, Teobaldis
Quiñonez, Yadira
De la Hoz, Andrés Mejia
dc.subject.proposal.eng.fl_str_mv Precision agriculture
Dashboard
ESP32
IoT
Sensors
Cloud monitoring
topic Precision agriculture
Dashboard
ESP32
IoT
Sensors
Cloud monitoring
Agricultura de precisión
Sensores
Monitoreo en la nube
dc.subject.proposal.spa.fl_str_mv Agricultura de precisión
Sensores
Monitoreo en la nube
description El sector agrícola se encuentra entre los más beneficiados por la expansión del Internet de las Cosas (IoT), ya que permite recopilar y gestionar una gran cantidad de datos sobre el entorno de un cultivo. Este artículo presenta los resultados del diseño y la prueba de un prototipo de sistema de monitoreo de variables agrícolas, las cuales pueden almacenarse y consultarse en la nube. Se utilizaron sensores y sistemas de procesamiento de bajo costo y fácilmente adaptables a entornos agrícolas. Los resultados obtenidos confirman la viabilidad de implementar estos sistemas sin recurrir a herramientas tecnológicas y computacionales complejas.
publishDate 2024
dc.date.issued.none.fl_str_mv 2024-03
dc.date.accessioned.none.fl_str_mv 2025-01-20T17:05:04Z
dc.date.available.none.fl_str_mv 2025-01-20T17:05:04Z
dc.type.none.fl_str_mv Artículo de revista
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dc.type.content.none.fl_str_mv Text
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dc.identifier.citation.none.fl_str_mv MARTINEZ, Jorge Luis Diaz; SALCEDO, Dixon; MERCADO, Teobaldis e QUINONEZ, Yadira. Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo. RISTI [online]. 2024, n.53 [citado 2025-01-20], pp.106-121. Disponível em: <http://scielo.pt/scielo.php?script=sci_arttext&pid=S1646-98952024000100106&lng=pt&nrm=iso>. Epub 30-Abr-2024. ISSN 1646-9895. https://doi.org/10.17013/risti.53.106-121.
dc.identifier.issn.none.fl_str_mv 1646-9895
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11323/13920
dc.identifier.instname.none.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.none.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.none.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv MARTINEZ, Jorge Luis Diaz; SALCEDO, Dixon; MERCADO, Teobaldis e QUINONEZ, Yadira. Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo. RISTI [online]. 2024, n.53 [citado 2025-01-20], pp.106-121. Disponível em: <http://scielo.pt/scielo.php?script=sci_arttext&pid=S1646-98952024000100106&lng=pt&nrm=iso>. Epub 30-Abr-2024. ISSN 1646-9895. https://doi.org/10.17013/risti.53.106-121.
1646-9895
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/13920
https://repositorio.cuc.edu.co/
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language spa
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dc.relation.references.none.fl_str_mv Abd El-Kader, S. M. (2020). Laying the foundations for an IoT reference architecture for agricultural application domain. IEEE Access, 8, 190194-190230. https://doi.org/10.1109/ACCESS.2020.3031634 [ Links ]
Aguilar, J., García, R., Toro, M., Pinto, A., & Rodríguez, P. (2020). A systematic literature review on the use of machine learning in precision livestock farming. Computers and Electronics in Agriculture, 179. https://doi.org/10.1016/j.compag.2020.105826 [ Links ]
Alfred, R., Obit, J. H., Chin, C. P. Y., Haviluddin, H., & Lim, Y. (2021). Towards paddy rice smart farming: A review on big data, machine learning, and rice production tasks. IEEE Access, 9. https://doi.org/10.1109/ACCESS.2021.3069449 [ Links ]
Ali, J. (2012). Factors affecting the adoption of information and communication technologies (ICTs) for farming decisions. Journal of Agricultural and Food Information, 13(1), 78-96. https://doi.org/10.1080/10496505.2012.636980 [ Links ]
Amanullah, M. A., Habeeb, R. A. A., Nasaruddin, F. H., Gani, A., Ahmed, E., Nainar, A. S. M., Akim, N. M., & Imran, M. (2020). Deep learning and big data technologies for IoT security. Computer Communications, 151. https://doi.org/10.1016/j.comcom.2020.01.016 [ Links ]
Arsovski, Z., Lula, P., & Đorđević, A. (2016). Impact of ICT on quality of life. [ Links ]
Bankole, F. O., Shirazi, F., & Brown, I. (2011). Investigating the impact of ICT investments on human development. In EJISDC (Vol. 48). http://www.ejisdc.org [ Links ]
Bhatia, G., Joshi, N., Iyengar, S., Rajpal, S., & Mahadevan, K. (2021). Crop Prediction Based on Environmental Conditions and Disease Prediction. Smart Innovation, Systems and Technologies, 195. https://doi.org/10.1007/978-981-15-7078-0_31 [ Links ]
Biradar, H. B., & Shabadi, L. (2017). Review on IOT based multidisciplinary models for smart farming. RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings, 2018-Janua, 1923-1926. https://doi.org/10.1109/RTEICT.2017.8256932 [ Links ]
Bouachir, W., Ihou, K. E., Gueziri, H. E., Bouguila, N., & Belanger, N. (2019). Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2923765 [ Links ]
Bula, A. (2020). Importancia de la Agricultura en el Desarrollo. [ Links ]
Cecinati, F., Moreno-Ródenas, A. M., Rico-Ramirez, M. A., ten Veldhuis, M. C., & Langeveld, J. G. (2018). Considering rain gauge uncertainty using kriging for uncertain data. Atmosphere, 9(11). https://doi.org/10.3390/atmos9110446 [ Links ]
de la Casa, A., Ovando, G., Bressanini, L., Martínez, J., Díaz, G., & Miranda, C. (2018). Soybean crop coverage estimation from NDVI images with different spatial resolution to evaluate yield variability in a plot. ISPRS Journal of Photogrammetry and Remote Sensing, 146. https://doi.org/10.1016/j.isprsjprs.2018.10.018 [ Links ]
Dobrescu, R., Merezeanu, D., & Mocanu, S. (2019). Context-aware control and monitoring system with IoT and cloud support. Computers and Electronics in Agriculture, 160. https://doi.org/10.1016/j.compag.2019.03.005 [ Links ]
Gašparović, S. (2019). Impact of ICT on some segments of everyday life of highschool population of the city of Zagreb. IJRAR- International Journal of Research and Analytical Reviews, 6(2), 62-65. [ Links ]
Ge, X. Y., Ding, J. L., Wang, J. Z., Sun, H. L., & Zhu, Z. Q. (2020). A New Method for Predicting Soil Moisture Based on UAV Hyperspectral Image. Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis, 40(2). https://doi.org/10.3964/j.issn.1000-0593(2020)02-0602-08 [ Links ]
Gopinath, R. (2023). Perception of ICT in farming practices with special reference to e-commerce in agriculture. IJRAR-International Journal of Research and Analytical Reviews, 6. http://ijrar.com/ [ Links ]
Hernandez, R. M. (2017). Impact of ICT on education: Challenges and perspectives. Propósitos y Representaciones, 5(1), 325-347. https://doi.org/10.20511/pyr2017.v5n1.149 [ Links ]
Khan, M. A., & Salah, K. (2018). IoT security: Review, blockchain solutions, and open challenges. Future Generation Computer Systems, 82. https://doi.org/10.1016/j.future.2017.11.022 [ Links ]
Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. NJAS - Wageningen Journal of Life Sciences, 90-91(October), 100315. https://doi.org/10.1016/j.njas.2019.100315 [ Links ]
Kocian, A., & Incrocci, L. (2020). Learning from Data to Optimize Control in Precision Farming. Stats, 3(3). https://doi.org/10.3390/stats3030018 [ Links ]
Marwa, M. E., Mburu, J., Oburu, R. E. J., Mwai, O., & Kahumbu, S. (2020). Impact of ICT based extension services on dairy production and household welfare: The case of iCow service in Kenya. Journal of Agricultural Science, 12(3), 141. https://doi.org/10.5539/jas.v12n3p141 [ Links ]
Miller, G. A., Hyslop, J. J., Barclay, D., Edwards, A., Thomson, W., & Duthie, C. A. (2019). Using 3D Imaging and Machine Learning to Predict Liveweight and Carcass Characteristics of Live Finishing Beef Cattle. Frontiers in Sustainable Food Systems, 3. https://doi.org/10.3389/fsufs.2019.00030 [ Links ]
Minagricultura. (2018). Un Campo para la Equidad: Política Agropecuaria y de Desarrollo Rural. [ Links ]
Mohammad El-Basioni, B. M., & Abd El-Kader, S. M. (2020). Laying the foundations for an IoT reference architecture for agricultural application domain. IEEE Access, 8. https://doi.org/10.1109/ACCESS.2020.3031634 [ Links ]
Mohamad Noor, M. B., & Hassan, W. H. (2019). Current research on Internet of Things (IoT) security: A survey. Computer Networks, 148. https://doi.org/10.1016/j.comnet.2018.11.025 [ Links ]
Newase, A. D., Sheetlani, J., Sai, S., & Patil, R. D. (2017). A literature review on impact of information and communication technology tools on rural society of India. Indian Journal of Computer Science and Engineering, 8(3), 235-240. [ Links ]
Oussous, A., Benjelloun, F. Z., Ait Lahcen, A., & Belfkih, S. (2018). Big Data technologies: A survey. In Journal of King Saud University - Computer and Information Sciences, 30, (4). https://doi.org/10.1016/j.jksuci.2017.06.001 [ Links ]
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Parra-Peña, R., Puyana, R., & Yepes-Chica, F. (2021). Análisis de la productividad del sector agropecuario en Colombia y su impacto en temas como: encadenamientos productivos, sostenibilidad e internacionalización, en el marco del programa Colombia más competitiva. [ Links ]
Punchihewa, D. J., & Wimalaratne, P. (2010). Towards an ICT enabled farming community. E-Governance in Practice, India (pp. 201-207). https://www.icta.lk [ Links ]
Sidhu, S., Mohd, B. J., & Hayajneh, T. (2019). Hardware security in IoT devices with emphasis on hardware trojans. Journal of Sensor and Actuator Networks, 8(3). https://doi.org/10.3390/jsan8030042 [ Links ]
Thangaraju, G., Agnes, X., & Rani, K. (2016). A study to improve the organic farming and the impact of ICT in organic agriculture with special reference to Perambalur district in Tamilnadu (Data analysis with K-means clustering algorithm in datamining). International Journal of Emerging Technology in Computer Science & Electronics, 20. [ Links ]
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Vergara-Díaz, O., Kefauver, S., Araus, J. L., & Aranjuelo, I. (2020). Development of novel technological approaches for a reliable crop characterization under changing environmental conditions. NIR News, 31(7-8). https://doi.org/10.1177/096033602097874 [ Links ]
Wei, H. E., Grafton, M., Bretherton, M., Irwin, M., & Sandoval, E. (2021). Evaluation of point hyperspectral reflectance and multivariate regression models for grapevine water status estimation. Remote Sensing, 13(16). https://doi.org/10.3390/rs13163198 [ Links ]
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)© Copyright 2024 Elsevier B.V., All rights reserved.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Martinez, Jorge Luis DiazSalcedo, DixonMercado, TeobaldisQuiñonez, YadiraDe la Hoz, Andrés Mejia2025-01-20T17:05:04Z2025-01-20T17:05:04Z2024-03MARTINEZ, Jorge Luis Diaz; SALCEDO, Dixon; MERCADO, Teobaldis e QUINONEZ, Yadira. Internet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipo. RISTI [online]. 2024, n.53 [citado 2025-01-20], pp.106-121. Disponível em: <http://scielo.pt/scielo.php?script=sci_arttext&pid=S1646-98952024000100106&lng=pt&nrm=iso>. Epub 30-Abr-2024. ISSN 1646-9895. https://doi.org/10.17013/risti.53.106-121.1646-9895https://hdl.handle.net/11323/13920Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/El sector agrícola se encuentra entre los más beneficiados por la expansión del Internet de las Cosas (IoT), ya que permite recopilar y gestionar una gran cantidad de datos sobre el entorno de un cultivo. Este artículo presenta los resultados del diseño y la prueba de un prototipo de sistema de monitoreo de variables agrícolas, las cuales pueden almacenarse y consultarse en la nube. Se utilizaron sensores y sistemas de procesamiento de bajo costo y fácilmente adaptables a entornos agrícolas. Los resultados obtenidos confirman la viabilidad de implementar estos sistemas sin recurrir a herramientas tecnológicas y computacionales complejas.The agricultural sector is among the most benefited by the Internet of Things (IoT) expansion since it allows collecting and managing a large amount of data about a crop's environment. This article presents the results of designing and testing a prototype monitoring system for agricultural variables, which can be stored and consulted in the cloud. Low-cost sensors and processing systems were easily adaptable to agricultural environments. The results confirmed the viability of implementing this system without resorting to complex technological and computational tools.16 páginasapplication/pdfspaAssociacao Iberica de Sistemas e Tecnologias de Informacao (AISTI)Portugalhttps://scielo.pt/scielo.php?script=sci_arttext&pid=S1646-98952024000100106&lng=pt&nrm=iso&tlng=esInternet de las cosas aplicado a la agricultura: estado actual y su aplicación mediante un prototipoArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85RISTI - Revista Iberica de Sistemas e Tecnologias de InformacaoAbd El-Kader, S. M. (2020). Laying the foundations for an IoT reference architecture for agricultural application domain. IEEE Access, 8, 190194-190230. https://doi.org/10.1109/ACCESS.2020.3031634 [ Links ]Aguilar, J., García, R., Toro, M., Pinto, A., & Rodríguez, P. (2020). A systematic literature review on the use of machine learning in precision livestock farming. Computers and Electronics in Agriculture, 179. https://doi.org/10.1016/j.compag.2020.105826 [ Links ]Alfred, R., Obit, J. H., Chin, C. P. Y., Haviluddin, H., & Lim, Y. (2021). Towards paddy rice smart farming: A review on big data, machine learning, and rice production tasks. IEEE Access, 9. https://doi.org/10.1109/ACCESS.2021.3069449 [ Links ]Ali, J. (2012). Factors affecting the adoption of information and communication technologies (ICTs) for farming decisions. Journal of Agricultural and Food Information, 13(1), 78-96. https://doi.org/10.1080/10496505.2012.636980 [ Links ]Amanullah, M. A., Habeeb, R. A. A., Nasaruddin, F. H., Gani, A., Ahmed, E., Nainar, A. S. M., Akim, N. M., & Imran, M. (2020). Deep learning and big data technologies for IoT security. Computer Communications, 151. https://doi.org/10.1016/j.comcom.2020.01.016 [ Links ]Arsovski, Z., Lula, P., & Đorđević, A. (2016). Impact of ICT on quality of life. [ Links ]Bankole, F. O., Shirazi, F., & Brown, I. (2011). Investigating the impact of ICT investments on human development. In EJISDC (Vol. 48). http://www.ejisdc.org [ Links ]Bhatia, G., Joshi, N., Iyengar, S., Rajpal, S., & Mahadevan, K. (2021). Crop Prediction Based on Environmental Conditions and Disease Prediction. Smart Innovation, Systems and Technologies, 195. https://doi.org/10.1007/978-981-15-7078-0_31 [ Links ]Biradar, H. B., & Shabadi, L. (2017). Review on IOT based multidisciplinary models for smart farming. RTEICT 2017 - 2nd IEEE International Conference on Recent Trends in Electronics, Information and Communication Technology, Proceedings, 2018-Janua, 1923-1926. https://doi.org/10.1109/RTEICT.2017.8256932 [ Links ]Bouachir, W., Ihou, K. E., Gueziri, H. E., Bouguila, N., & Belanger, N. (2019). Computer Vision System for Automatic Counting of Planting Microsites Using UAV Imagery. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2923765 [ Links ]Bula, A. (2020). Importancia de la Agricultura en el Desarrollo. [ Links ]Cecinati, F., Moreno-Ródenas, A. M., Rico-Ramirez, M. A., ten Veldhuis, M. C., & Langeveld, J. G. (2018). Considering rain gauge uncertainty using kriging for uncertain data. Atmosphere, 9(11). https://doi.org/10.3390/atmos9110446 [ Links ]de la Casa, A., Ovando, G., Bressanini, L., Martínez, J., Díaz, G., & Miranda, C. (2018). Soybean crop coverage estimation from NDVI images with different spatial resolution to evaluate yield variability in a plot. ISPRS Journal of Photogrammetry and Remote Sensing, 146. https://doi.org/10.1016/j.isprsjprs.2018.10.018 [ Links ]Dobrescu, R., Merezeanu, D., & Mocanu, S. (2019). Context-aware control and monitoring system with IoT and cloud support. Computers and Electronics in Agriculture, 160. https://doi.org/10.1016/j.compag.2019.03.005 [ Links ]Gašparović, S. (2019). Impact of ICT on some segments of everyday life of highschool population of the city of Zagreb. IJRAR- International Journal of Research and Analytical Reviews, 6(2), 62-65. [ Links ]Ge, X. Y., Ding, J. L., Wang, J. Z., Sun, H. L., & Zhu, Z. Q. (2020). A New Method for Predicting Soil Moisture Based on UAV Hyperspectral Image. Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis, 40(2). https://doi.org/10.3964/j.issn.1000-0593(2020)02-0602-08 [ Links ]Gopinath, R. (2023). Perception of ICT in farming practices with special reference to e-commerce in agriculture. IJRAR-International Journal of Research and Analytical Reviews, 6. http://ijrar.com/ [ Links ]Hernandez, R. M. (2017). Impact of ICT on education: Challenges and perspectives. Propósitos y Representaciones, 5(1), 325-347. https://doi.org/10.20511/pyr2017.v5n1.149 [ Links ]Khan, M. A., & Salah, K. (2018). IoT security: Review, blockchain solutions, and open challenges. 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Remote Sensing, 13(16). https://doi.org/10.3390/rs13163198 [ Links ]12110653Precision agricultureDashboardESP32IoTSensorsCloud monitoringAgricultura de precisiónSensoresMonitoreo en la nubePublicationORIGINALInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdfInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdfapplication/pdf770824https://repositorio.cuc.edu.co/bitstreams/62330a39-4768-47e9-93d8-96aa46e08781/downloadd98942854545ea35ad6688b1a8bc4709MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-815543https://repositorio.cuc.edu.co/bitstreams/c58f9237-0cca-4a62-9428-0ec3768161d0/download73a5432e0b76442b22b026844140d683MD52TEXTInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdf.txtInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdf.txtExtracted texttext/plain40343https://repositorio.cuc.edu.co/bitstreams/0fc9906e-6df4-4ce8-b54b-b6909f9453ba/download26aeaeabad50c9906a20cf787719dd85MD53THUMBNAILInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdf.jpgInternet of Things (IoT) applied to agriculture current state and its application through a prototype.pdf.jpgGenerated Thumbnailimage/jpeg12153https://repositorio.cuc.edu.co/bitstreams/55bacab9-c0d0-494b-a98e-9e86f0e96ab4/download57a0d9504ec225e450d2b1be107fc23aMD5411323/13920oai:repositorio.cuc.edu.co:11323/139202025-01-21 04:02:35.794https://creativecommons.org/licenses/by-nc-nd/4.0/© Copyright 2024 Elsevier B.V., All rights reserved.open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa 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ara ejercer estos derechos sobre la Obra tal y como se indica a continuación:</p>
    <ol type="a">
      <li>Reproducir la Obra, incorporar la Obra en una o más Obras Colectivas, y reproducir la Obra incorporada en las Obras Colectivas.</li>
      <li>Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.</li>
      <li>Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.</li>
    </ol>
    <p>Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).</p>
  </li>
  <br/>
  <li>
    Restricciones.
    <p>La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:</p>
    <ol type="a">
      <li>Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).</li>
      <li>Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.</li>
      <li>Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.</li>
      <li>
        Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:
        <ol type="i">
          <li>Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.</li>
          <li>Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
        </ol>
      </li>
      <li>Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.</li>
    </ol>
  </li>
  <br/>
  <li>
    Representaciones, Garantías y Limitaciones de Responsabilidad.
    <p>A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Limitación de responsabilidad.
    <p>A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.</p>
  </li>
  <br/>
  <li>
    Término.
    <ol type="a">
      <li>Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.</li>
      <li>Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.</li>
    </ol>
  </li>
  <br/>
  <li>
    Varios.
    <ol type="a">
      <li>Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.</li>
      <li>Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.</li>
      <li>Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.</li>
      <li>Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.</li>
    </ol>
  </li>
  <br/>
</ol>


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