Abstract
Early warning systems are designed to inform the largest number of users, such as a country or a region, about a risky situation. However, in specific domains such as agriculture, it is commonly required that these alerts be more specific according to the crops location and their properties, consequently the web services of these systems must be adapted. On the other hand, the Enterprise Services Bus with its mediation capabilities (such as message transformation and routing) and Complex Event Processing with their monitoring characteristics can be integrated to meet the adaptation requirements of web services at runtime. This paper presents an improvement for Early Warning System for coffee production that, according to the area in which a crop is located and its phenology, manages the adaptation of alerts for coffee rust, based on the integration of an Enterprise Services Bus and a Complex Events Processing.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
References
Gómez, G.C.: Desarrollos científicos de Cenicafé en la última década. Rev. Acad. Colombaina Cienc. Exactas Físicas Nat. vol. 1, no. 30, pp. 89–100 (2005)
de Camargo, A., Pereira, A.R.: Agrometeorology of the coffee crop. Geneva World Meteorological Organization (1994)
De León, C.: Enfermedades del maíz: Guía para su identificación en el campo (1974)
Gauhl, F., et al.: Multilocational evaluation of black Sigatoka resistance in banana and plantain. Evaluación, en varios lugares, de bananos y plátanos resistentes a la Sigatoka negra. IITA Res. Guide 47 (1993)
Agrios, G.N.: Fitopatología, Segunda Edición. México: UTEHA-Noriega
García, A., Obín, D.: Sistemas de Alerta Temprana para Prevención de Enfermedades y Plagas, December 2013
Wiltshire, A.: Developing early warning systems: a checklist. In: Proceedings of 3rd International Conference on Early Warning (EWC) (2006)
Ocharan, J.: Sistemas de Alerta Temprana. Fotografía actual y retos. Cuad. Int. Tecnol. Para El Desarro. Hum. no. 6, p. 2 (2007)
Flores, N.P., Lerdon, F.J., Bravo, H.R., Acuña, I.: Factibilidad De Implementar Pronosticadores Automatizados Para Controlar El Tizón Tardio De La Papa En El Sur De Chile. Agro Sur, vol. 36, no. 1, pp. 37–42, May 2008
Barquero Miranda, M.: Sistema de alerta temprana para el ojo de gallo. Rev. Inf. (2012)
Gleason, M.L., et al.: Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study. Sci. Agric. 65(SPE), 76–87 (2008)
Bonett, M.: Personalization of web services: opportunities and challenges. Ariadne, no. 28 (2001)
García Gutiérrez, V.: Sistema para la adaptación de servicios a nivel de presentación y de navegación en portales web (2013)
González, L., Ruggia, R.: Towards dynamic adaptation within an ESB-based service infrastructure layer. In: Proceedings of the 3rd International workshop on Monitoring, Adaptation and Beyond, pp. 40–47 (2010)
González, L., Laborde, J.L., Galnares, M., Fenoglio, M., Ruggia, R.: An adaptive enterprise service bus infrastructure for service based systems. In: Service-Oriented Computing–ICSOC 2013 Workshops, pp. 480–491 (2013)
Ortiz, G., Boubeta-Puig, J., de Prado, A.G., Medina-Bulo, I.: Towards event-driven context-aware web services. In: Adaptive Web Services for Modular and Reusable Software Development: Tactics and Solutions, pp. 148–159 (2012)
González, L., Ortiz, G.: An event-driven integration platform for context-aware web services. J. UCS 20(8), 1071–1088 (2014)
González, L., Ortiz, G.: An ESB-based infrastructure for event-driven context-aware web services. In: Advances in Service-Oriented and Cloud Computing, pp. 360–369. Springer (2013)
Service-Oriented Architecture (SOA) Definition. Service Architecture. http://www.service-architecture.com/articles/web-services/service-oriented_architecture_soa_definition.html. Accessed 03 Feb 2017
Yuan, S.-T., Lu, M.-R.: An value-centric event driven model and architecture: a case study of adaptive complement of SOA for distributed care service delivery. Expert Syst. Appl. 36(2), 3671–3694 (2009). Part 2
González, L.: Plataforma ESB Adaptativa para Sistemas Basados en Servicios. Universidad de la República, Montevideo, Uruguay (2011)
Kazhamiakin, R.: Adaptation and monitoring in S-Cube: global vision and roadmap. In: Workshop on Service Monitoring, Adaptation and Beyond, p. 67 (2009)
Gaitan, A., et al.: Evento de La Niña en Colombia: Recomendaciones para la caficultura (2016)
Osorio, C.A.R., Giraldo, C.A.S., Ardila, M.A.C., Bustamante, A.L.G.: La Roya del Cafeto en Colombia Impacto, manejo y costos del control, February 2011
Corrales, D.C., Ledezma, A., Peña, A.J., Hoyos, J., Figueroa, A., Corrales, J.C.: Un nuevo conjunto de datos para la detección de roya en cultivos de café Colombianos basado en clasificadores. Sist. Telemática, vol. 12, no. 29, pp. 9–23 (2014)
Corrales, D.C., Figueroa, A., Ledezma, A., Corrales, J.C.: An empirical multi-classifier for coffee rust detection in Colombian crops. In: Proceedings of 15th International Conference Computational Science and Its Applications – ICCSA 2015, Banff, AB, Canada, 22–25 June 2015, Part I, vol. 9155, pp. 60–74 (2015)
Corrales, D.C., Casas, A.F., Ledezma, A., Corrales, J.C.: Two-level classifier ensembles for coffee rust estimation in Colombian crops. Int. J. Agric. Environ. Inf. Syst. IJAEIS 7(3), 41–59 (2016)
Lasso, E., Thamada, T.T., Meira, C.A.A., Corrales, J.C.: Graph patterns as representation of rules extracted from decision trees for coffee rust detection. In: Garoufallou, E., Hartley, R.J., Gaitanou, P. (eds.) Metadata and Semantics Research, pp. 405–414. Springer International Publishing (2015)
Meira, C.A., Rodrigues, L.H., Moraes, S.A.: Análise da epidemia da ferrugem do cafeeiro com árvore de decisão. Trop. Plant Pathol. vol. 33, no. 2, pp. 114–124 (2008)
Meira, C.A.A., Rodrigues, L.H.A., de Moraes, S.A.: Modelos de alerta para o controle da ferrugem-do-cafeeiro em lavouras com alta carga pendente. Pesqui. Agropecuária Bras. vol. 44, pp. 233–242 (2009)
Cintra, M.E., Meira, C.A.A., Monard, M.C., Camargo, H.A., Rodrigues, L.H.A.: The use of fuzzy decision trees for coffee rust warning in Brazilian crops. In: 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 1347–1352 (2011)
Ramírez, V.H., et al.: Variabilidad climática y la floración del café en Colombia (2013)
Dossot, D., D’Emic, J., Romero, V.: Mule in action. Manning, Greenwich (2014)
EsperTech - Products. http://www.espertech.com/products/. Accessed 02 Mar 2016
Goncalves, A.: Beginning Java EE 6 with GlassFish 3. Apress, Berkely (2010)
Momjian, B.: PostgreSQL: Introduction and Concepts, vol. 192. Addison-Wesley, New York (2001)
Liang-Jie, Z.: Web Services Research and Practices. Idea Group Inc (IGI), Hershey (2008)
PROCAGICA by Jacques Avelino - Research Project on ResearchGate. ResearchGate. https://www.researchgate.net/project/PROCAGICA
Acknowledgements
The authors are grateful to the University of Cauca and its Telematics Engineering Group (GIT), the Colombian Administrative Department of Science, Technology and Innovation (Colciencias), AgroCloud project of The Interinstitutional Network of Climate Change and Food Security of Colombia (RICCLISA) for supporting this research and the InnovAccion Cauca project of the Colombian Science, Technology and Innovation Fund (SGR-CTeI) for PhD scholarship granted to MsC. Emmanuel Lasso.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Valencia, O.R., Lasso, E., Corrales, J.C. (2018). Improving Early Warning Systems for Agriculture Based on Web Service Adaptation. In: Angelov, P., Iglesias, J., Corrales, J. (eds) Advances in Information and Communication Technologies for Adapting Agriculture to Climate Change. AACC'17 2017. Advances in Intelligent Systems and Computing, vol 687. Springer, Cham. https://doi.org/10.1007/978-3-319-70187-5_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-70187-5_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-70186-8
Online ISBN: 978-3-319-70187-5
eBook Packages: EngineeringEngineering (R0)