Sistema de análisis para el incremento de la producción de granjas avícolas en Colombia. Caso de estudioproyecto proavícola

  1. Valderrama Mendoza, Mateo 1
  2. Rodríguez Urrego, Leonardo 1
  3. Cobo, Luis 1
  4. Martínez, Gloria María 2
  1. 1 Universidad EAN
    info

    Universidad EAN

    Bogotá, Colombia

    ROR https://ror.org/00tncsy16

  2. 2 Grupo Linkpoint
Zeitschrift:
Avances: Investigacion en Ingeniería

ISSN: 2619-6581,  1794-4953

Datum der Publikation: 2019

Ausgabe: 16

Nummer: 1

Seiten: 7-19

Art: Artikel

DOI: 10.18041/1794-4953/AVANCES.1.5254 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Andere Publikationen in: Avances: Investigacion en Ingeniería

Zusammenfassung

This paper provides the insights of the SCADA software which allows measuring, registering and controlling variables relevant for the increasement of the productivity in Poultry farms in Colombia by using some intelligent algorithms and BIG DATA. Therefore, this paper shows a brief description of the technological progress of the Colombian Poultry sector and the importance of the variables implemented on the SCADA software for the Poultry FarmsProject. Likewise, this article includes a graphic description that represents the code which was generated in the LabVIEW program, regarding some algorithms that allow the management of the data acquired from the SCADA software. Also, the development of the project is deeply explained, besides devices, and subsystems that make up the software/hardware and the methodology used for their design and interaction. The main functionalities of the software are described as invoking subprograms on specific screens, generate alarms, write data in local storage and send readings to a server in the cloud for BIG DATA processing. Finally, the relevance of project development and its impact on the analysis, parameterization, and control of the increasement of productivity in Colombian Poultry farms is concluded.  

Bibliographische Referenzen

  • M. Aguilera, “Determinantes del Desarrollo en la Avicultura en Colombia: Instituciones, Organizaciones y Tecnología”, Revista del Banco de la República, vol. 87, no 1046, p. 21-56., 2014.
  • J. Herrera, M. Barrios, and S. Pérez, “Diseño e implementación de un sistema scada inalámbrico mediante la tecnología zigbee y arduino”, Prospect J., vol. 12, no. 2, pp. 65-72, 2014. https://doi.org/10.15665/rp.v12i2.290
  • R. Osorio, I. D. F. Ferreira, J. A. Osorio, K. S. Rocha, and L. M. Guerra Garcia, “Modelamiento del Ambiente Térmico y Aéreo de un Galpón de Presión Negativa Tipo Túnel para Pollitos”, Rev. Fac. Nac. Agron., vol. 66, no. 2, pp. 7085–7093, 2013. https://doi.org/10.15446/rfnam
  • M. Eady, D. Samuel, and B. Bowker, “Effect of pH and postmortem aging on protein extraction from broiler breast muscle”, Poult. Sci., vol. 93, no. 7, pp. 1825–1833, 2014. https://doi.org/10.3382/ps.2013-03619
  • National Instruments, “¿Qué es Adquisición de Datos? - National Instruments”, 2016. [Online]. Available: https://www.ni.com/data-acquisition/what-is/esa/
  • F. L. Pedraza Valencia, “Galpones más eficientes” UN Periódico No. 167 - Universidad Nacional de Colombia - Unimedios, 07 junio, 2013. [Online]. Available: https://issuu.com/mediosdigitales/docs/unperiodico167
  • I. Demongodin and N. Koussoulas, “Modelling of hybrid control systems using Petri nets”, Int. Conf. Autom. Mix. Process, 1998. https://doi.org/10.1.1.27.7826
  • FENAVI, “Producción pública”, 2018. [Online]. Available: https://fenavi.org/estadisticas/informacion-estadistica-publica/
  • M. Aguilera, “Determinantes del Desarrollo en la Avicultura en Colombia: Instituciones, Organizaciones y Tecnología”, Revista del Banco de la República, vol. 87, no 1046, p. 30., 2014.
  • M. Aguilera, “Determinantes del Desarrollo en la Avicultura en Colombia: Instituciones, Organizaciones y Tecnología”, Revista del Banco de la República, vol. 87, no 1046, p. 44., 2014.
  • M. Ruzal, D. Shinder, I. Malka, and S. Yahav, “Ventilation plays an important role in hens’ egg production at high ambient temperature”, Poult. Sci., vol. 90, no. 4, pp. 856–862, Apr. 2011. https://doi.org/10.3382/ps.2010-00993.
  • Aviagen, “Manual de Manejo del Pollo de Engorde Ross”, Aviagen, p. 134, 2014. [Online]. Available: https://bit.ly/2VHK3iV
  • D. H. Mccreery, “Water Consumption Behavior in Broilers”, PhD thesis, Poultry Science, Univ. of Arkansas, Arkansas, EEUU, 2015.
  • Arbor Acres-Aviagen “Guía de Manejo del Pollo de Engorde”, p. 65, 2009. [Online]. Available: https://bit.ly/2EteTGe
  • J. Du, W. Li, and J. Guo, “Design of LabVIEW Based General Data Acquisition System”, 2017 IEEE 2nd Inf. Technol. Networking, Electron. Autom. Control Conf., pp. 1235–1239, Dec. 2017. https://doi.org/10.1109/ITNEC.2017.8284973
  • National Instruments, “Fundamentals , System Design , and Setup for the 4 to 20 mA Current Loop”, NI Whitepaper, 2019. [Online]. Available: https://bit.ly/30AQs37
  • National Instruments, “Data Acquisition and Signal Conditioning”, Course Software, 2003. [Online]. Available: http://www.n4iqt.com/dallasis4/labview_7.0_daq_course.pdf
  • M. N. Ashraf, S. A. Bin Khalid, M. S. Ahmed, and A. Munir, “Implementation of Intranet-SCADA using LabVIEW based data acquisition and management”, in ICC 2009 - International Conference of Computing in Engineering, Science and Information, pp. 244–249, 2009. https://doi.org/10.1109/ICC.2009.41
  • C. Wei and S. Wenxia, “Design of temperature collecting and power control system for fluidized bed based on LabVIEW”, in 2017 Chinese Automation Congress (CAC), pp. 2396–2400, 2017. https://doi.org/10.1109/CAC.2017.8243177
  • Nattional Instruments, LabView: Measurements Manual. 2003. [Online]. Available: http://fy.chalmers.se/~f7xlh/LV_Kurs/LV_Meas_Man_2003.pdf
  • J. B. Mandhare and S. P Jadhav, “LabView based PI Controller for a Level Control System”, Int. J. Appl. Inf. Syst., vol. ICWAC 2014, no. 1, pp. 18–23, 2014.
  • I. Demongodin and N. Koussoulas, “Modelling of hybrid control systems using Petri nets”, Int. Conf. Autom. Mix. Process, 1998. https://doi.org/10.1.1.27.7826
  • R. Bitter, T. Mohiuddin, and M. Nawrocki, LabVIEW: Advanced programming techniques. Crc Press, 2006. https://doi.org/10.1201/9781420004915
  • S. Wolfert, L. Ge, C. Verdouw, and M. J. Bogaardt, “Big Data in Smart Farming – A review”, Agric. Syst., vol. 153, pp. 69–80, 2017. https://doi.org/10.1016/j.agsy.2017.01.023
  • W. B. Roush, W. A. Dozier, and S. L. Branton, “Comparison of Gompertz and nEural Network Models of Broiler Growth”, Poult. Sci., vol. 85, no. 4, pp. 794–797, Apr. 2006. https://doi.org/10.1093/ps/85.4.794
Fuente de los datos: Dialnet