Mostrar el registro sencillo del ítem

dc.contributor.authorCama Pinto, Alejandrospa
dc.contributor.authorPiñeres Espitia, Gabriel Dariospa
dc.contributor.authorCaicedo Ortiz, Jose Gregoriospa
dc.contributor.authorRamirez Cerpa, Elkin Duvanspa
dc.contributor.authorBetancur Agudelo, Leonardospa
dc.contributor.authorGómez Mula, Franciscospa
dc.date.accessioned2018-11-23T22:02:51Z
dc.date.available2018-11-23T22:02:51Z
dc.date.issued2017-07-02
dc.identifier.issn15501329spa
dc.identifier.urihttp://hdl.handle.net/11323/1789spa
dc.description.abstractToday, through the monitoring of agronomic variables, the wireless sensor networks are playing an increasingly important role in precision agriculture. Among the emerging technologies used to develop prototypes related to wireless sensor network, we find the Arduino platform and XBee radio modules from the DIGI Company. In this article, based on field tests, we conducted a comparative analysis of received strength signal intensity levels, calculation of path loss with “log-normal shadowing” and free-space path loss models. In addition, we measure packet loss for different transmission, distances and environments with respect to an “Arduino Mega” board, and radio modules XBee PRO S1 and XBee Pro S2. The tests for the packet loss and received strength signal intensity level show the best performance for the XBee Pro S2 in the indoor, outdoor, and rural scenarios.spa
dc.language.isoeng
dc.publisherInternational Journal of Distributed Sensor Networksspa
dc.rightsAtribución – No comercial – Compartir igualspa
dc.subjectpacket losseng
dc.subjectradio propagation modeleng
dc.subjectreceived strength signal intensity leveleng
dc.subjectwireless sensor networkeng
dc.subjectXBeeeng
dc.titleReceived strength signal intensity performance analysis in wireless sensor network using Arduino platform and XBee wireless moduleseng
dc.typeArtículo de revistaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references1. Srbinovska M, Gavrovski C, Dimcev V, et al. Environmental parameters monitoring in precision agriculture using wireless sensor networks. J Clean Prod 2015; 88: 297–307.2. Montoya FG, Go´mez J, Cama A, et al. A monitoring system for intensive agriculture based on mesh networks and the android system. Comput Electron Agr 2013; 99: 14–20. 3. Cama-Pinto A, Gil-Montoya F, Go´mez-Lo´pez J, et al. Wireless surveillance system for greenhouse crops (Dyna. 81,184,164.), Revista DYNA, 2014, http://www.scielo.org.co/pdf/dyna/v81n184/v81n184a22.pdf 4. Urbano-molano Aparicio F. Redes de Sensores Inala´mbricos Aplicadas a Optimizacio´n en Agricultura de Precisio´n para Cultivos de Cafe´ en Colombia. J Cienc Ing 2012; 5(1): 46–52. 5. Xiao L and Guo L. The realization of precision agriculture monitoring system based on wireless sensor network. In: Proceedings of the international conference on computer and communication technologies in agriculture engineering (CCTAE’10), Chengdu, China, 12–13 June 2010, pp.89–92. New York: IEEE. 6. Ministerio de Educacio´n, 2009, http://www.mineducacion.gov.co/cvn/1665/w3-article-200749.html (accessed 28 August 2016). 7. Cirstea C, Cernaianu M and Gontean A. Packet loss analysis in wireless sensor networks routing protocols. In: Proceedings of the 2012 35th international conference on telecommunications and signal processing (TSP), Prague, 3–4 July 2012, pp.37–41. New York: IEEE. 8. Bas CU and Ergen SC. Spatio-temporal characteristics of link quality in wireless sensor networks. In: Proceedings of the 2010 IEEE wireless communications and networking conference (WCNC), Shanghai, China, 1–4 April 2012, pp.1152–1157. New York: IEEE. 9. Goldsmith A. Wireless communications. New York: Cambridge University Press, 2005. 10. Al-Busaidi AM. Development of an educational environment for online control of a biped robot using MATLAB and Arduino. In: Proceedings of the 2012 9th FranceJapan & 7th Europe-Asia congress on mechatronics (MECATRONICS)/13th int’l workshop on research and education in mechatronics (REM), Paris, France, 21–23 November 2012, pp.337–344. New York: IEEE. 11. Al-kadi T, Al-tuwaijri Z and Al-omran A. Arduino Wi-Fi network analyzer. Proced Comput Sci 2013; 21: 522–529. 12. Kornuta JA, Nipper ME and Dixon JB. Low-cost microcontroller platform for studying lymphatic biomechanics in vitro. J Biom 2013; 46(1): 183–186. 13. Xu J, Liu W, Lang F, et al. Distance measurement model based on RSSI in WSN. Wirel Sens Netw 2010; 2(8): 606–611. 14. Lee J-H, Choi J, Lee W-H, et al. Measurement and analysis on land-to-ship offshore wireless channel in 2.4 GHz. IEEE Wirel Commun Lett 2017; 6(2): 222–225. 15. Biaou U, Sadoudi L, Bocquet M, et al. Modeling of ZigBee (IEEE 802.15.4) channel in rail environment for intelligent transport. In: Proceedings of the 2015 4th IEEE international conference on advanced logistics and transport, IEEE ICALT 2015, art. no. 7136637, 2015, pp.293– 298. 16. Seybold J. Introduction to RF propagation. Hoboken, NJ: Wiley Interscience, 2005. 17. Chrysikos T, Georgopoulos G and Kotsopoulos S. Wireless channel characterization for a home indoor propagation topology at 2.4 GHz. Proceedings of the wireless telecommunications symposium, New York, 13– 15 April 2011, article no. 5960879. New York: IEEE. 18. Mahalin NH, Sharifah HS, Syed Yusof SK, et al. RSSI measurements for enabling IEEE 802.15.4 coexistence with IEEE 802.11b/g. In: Proceedings of the IEEE region 10 annual international conference on TENCON, Singapore, 23–26 January 2009, pp.1–4. New York: IEEE. 19. Hamida E, Ben Lyon I, Chelius G, et al. Investigating the impact of human activity on the performance of wireless networks—an experimental approach. In: Proceedings of the 2010 IEEE international symposium on a world of wireless mobile and multimedia networks (WoWMoM), Montreal, QC, Canada, 14–17 June 2010. New York: IEEE. 20. Pellegrini RM, Persia S, Volponi D, et al. 2011; RF propagation analysis for ZigBee Sensor Network using RSSI measurements. In: Proceedings of the 2011 2nd international conference on wireless communication, vehicular technology, information theory and aerospace & electronic systems technology (Wireless VITAE), Chennai, India, 28 Febraury–3 March 2011, pp.1–5. New York: IEEE. 21. Harun A, Ramli MF, Kamarudin LM, et al. Comparative performance analysis of wireless RSSI in wireless sensor networks motes in tropical mixed-crop precision farm. In: Proceedings of the 2012 third international conference on intelligent systems modelling and simulation, Kota Kinabalu, Malaysia, 8–10 February 2012, pp.606– 610. New York: IEEE. 22. Kodali RK, Rawat N and Boppana L. WSN sensors for precision agriculture. In: Proceedings of the region 10 symposium, Kuala Lumpur, Malaysia, 14–16 April 2014, pp.643–648. New York: IEEE. 23. Howell B, Anderson E and Flores A. A low cost wireless sensor network for landslide hazard monitoring. In Proceedings of the geoscience and remote sensing symposium (IGARSS), Munich, 22–27 July 2012, pp.4793–4796. New York: IEEE. 24. Zamora R. Ana´lisis de requerimiento para la implementacio´n de Laboratorios Remotos. Barranquilla, Colombia: Educosta, 2011. 25. Mahmoud KH. Data collection and processing from distributed system of wireless sensors. Master Thesis, Masaryk University, Brno, 2013. 26. Caicedo-Ortiz J, Coll MAA and Cama-Pinto A. Modelo de despliegue de una WSN para la medicio´n de las variables clima´ticas que causan fuertes precipitaciones. WSN deployment model for measuring climate variables that cause strong precipitation, pp.106–115, http://www.scielo.org.co/pdf/prosp/v13n1/v13n1a11.pdf 27. Libelium, http://www.libelium.com/products/waspmote 28. Faludi R. Building wireless sensor networks. 4th ed. USA: Brian Jepson, 2012, p.32. 29. Arnil J, Punsawad Y and Wongsawat Y. Wireless sensor network-based smart room system for healthcare monitoring. In: Proceedings of the 2011 IEEE international conference on robotics and biomimetics (ROBIO), Karon Beach, Phuket, Thailand, 7–11 December 2011, pp.2073– 2076. New York: IEEE. 30. Benkic K, Malajner M, Planinsic P, et al. Using RSSI value for distance estimation in wireless sensor networks based on ZigBee. In: Proceedings of the 15th international conference on systems, signals and image processing, Bratislava, 25–28 June 2008, pp.303–306. New York: IEEE. 31. Chrysikos T and Kotsopoulos S. Characterization of large-scale fading for the 2.4 GHz channel in obstacledense indoor propagation topologies. Proceedings of the 2012 IEEE vehicular technology conference, Quebec City, QC, Canada, 3–6 September 2012, article no. 6399239. New York: IEEE. 32. Kurt S and Tavli B. Path-loss modeling for wireless sensor networks: a review of models and comparative evaluations. IEEE Antenn Propag M 2016; 59(1): 18–37. 33. Farahani S. ZigBee wireless networks and transceivers. 1st ed. Oxford: Elsevier Ltd., 2008, p.173.spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

  • Artículos científicos [3154]
    Artículos de investigación publicados por miembros de la comunidad universitaria.

Mostrar el registro sencillo del ítem