Design of a low cost weather station for detecting environmental changes

El objetivo de esta investigación es desarrollar un prototipo de estación meteorológica secundaria para mediciones de temperatura, humedad y presión atmosférica. Para validar la operación, se realizó un análisis de varianza y un diseño experimental r&R. Los sensores TMP36, RHT03 y BMP085 fueron...

Full description

Autores:
Cama Pinto, Alejandro
Piñeres Espitia, Gabriel Dario
Rosa Morron, Daniel Eduardo de la
Estevez, Francisco
Cama Pinto, Dora
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/1870
Acceso en línea:
http://hdl.handle.net/11323/1870
https://repositorio.cuc.edu.co/
Palabra clave:
Repeatability and reproducibility (r&R)
Sensors
Variance analysis
Weather station
Estación meteorológica
análisis de varianza
repetitividad y reproducibilidad (r&R)
sensores
Rights
openAccess
License
Atribución – No comercial – Compartir igual
id RCUC2_ff4c202bbd78613da64b935c6b893632
oai_identifier_str oai:repositorio.cuc.edu.co:11323/1870
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Design of a low cost weather station for detecting environmental changes
title Design of a low cost weather station for detecting environmental changes
spellingShingle Design of a low cost weather station for detecting environmental changes
Repeatability and reproducibility (r&R)
Sensors
Variance analysis
Weather station
Estación meteorológica
análisis de varianza
repetitividad y reproducibilidad (r&R)
sensores
title_short Design of a low cost weather station for detecting environmental changes
title_full Design of a low cost weather station for detecting environmental changes
title_fullStr Design of a low cost weather station for detecting environmental changes
title_full_unstemmed Design of a low cost weather station for detecting environmental changes
title_sort Design of a low cost weather station for detecting environmental changes
dc.creator.fl_str_mv Cama Pinto, Alejandro
Piñeres Espitia, Gabriel Dario
Rosa Morron, Daniel Eduardo de la
Estevez, Francisco
Cama Pinto, Dora
dc.contributor.author.spa.fl_str_mv Cama Pinto, Alejandro
Piñeres Espitia, Gabriel Dario
Rosa Morron, Daniel Eduardo de la
Estevez, Francisco
Cama Pinto, Dora
dc.subject.eng.fl_str_mv Repeatability and reproducibility (r&R)
Sensors
Variance analysis
Weather station
Estación meteorológica
análisis de varianza
repetitividad y reproducibilidad (r&R)
sensores
topic Repeatability and reproducibility (r&R)
Sensors
Variance analysis
Weather station
Estación meteorológica
análisis de varianza
repetitividad y reproducibilidad (r&R)
sensores
description El objetivo de esta investigación es desarrollar un prototipo de estación meteorológica secundaria para mediciones de temperatura, humedad y presión atmosférica. Para validar la operación, se realizó un análisis de varianza y un diseño experimental r&R. Los sensores TMP36, RHT03 y BMP085 fueron seleccionados para la plataforma Arduino UNO y calibrados con una estación meteorológica y un higrómetro digital certificado por las autoridades. Nuestro sistema utiliza hardware y software abiertos y es una estación meteorológica de bajo costo diseñada para el análisis ambiental.
publishDate 2017
dc.date.issued.none.fl_str_mv 2017-09-05
dc.date.accessioned.none.fl_str_mv 2018-11-26T16:29:51Z
dc.date.available.none.fl_str_mv 2018-11-26T16:29:51Z
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
format http://purl.org/coar/resource_type/c_6501
status_str acceptedVersion
dc.identifier.issn.spa.fl_str_mv 07981015
dc.identifier.uri.spa.fl_str_mv http://hdl.handle.net/11323/1870
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 07981015
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url http://hdl.handle.net/11323/1870
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv Abistado, K.G., Arellano, C.N., Maravillas, E.A., 2014. Weather Forecasting Using Artificial Neural Network and Bayesian Network. Journal of Advanced Computational Intelligence and Intelligent Informatics 18(5), 812-816. Antolik, M., 2000. An overview of the National Weather Service’s centralized statistical quantitative precipitation forecasts. Journal of Hydrology, 239, 306–337. Arduino, 2014. Arduino-Home [Available on line, accessed oct 25, 2014]. < http://www.arduino.cc/ >. Anzalone, G.C., Glover, A.G., Pearce, J.M., 2013. Open-source colorimeter. Sensors. 13(4), 5338-5346. < http://dx.doi.org/10.3390/s130405338 >. Azmil, M. S. A., Ya'acob, N., Tahar, K. N. and Sarnin, S. S. Wireless fire detection monitoring system for fire and rescue application. 2015 IEEE 11th International Colloquium on Signal Processing & Its Applications (CSPA), Kuala Lumpur, 2015, pp. 84-89. doi: 10.1109/CSPA.2015.7225623. Blank S., Bartolein, C., Meyer, A., Ostermeier, R., Rostanin, O., 2013. iGreen: A ubiquitous dynamic network to enable manufacturer independent data exchange in future precision farming. Computers and Electronics in Agriculture, 98, 109-116. < http://dx.doi.org/10.1016/j.compag.2013.08.001 >. Borick, C.P., Rabe, B.G., 2014. Weather or not? Examining the impact of meteorological conditions on public opinion regarding global warming. Weather, Climate, and Society 6(3), 413-424. < http://dx.doi.org/10.1175/WCAS-D-13-00042.1 >. Cama-Pinto, A., Piñeres-Espitia, G., Caicedo-Ortiz, J., Ramírez-Cerpa, E., Betancur-Agudelo, L. and Gómez-Mula, F. Received strength signal intensity performance analysis in wireless sensor network using arduino platform and xbee wireless modules. International Journal of Distributed Sensor Networks, 13(7):1550147717722691, 2017. Cama-Pinto, A., Piñeres-Espitia, G., Zamora-Musa, R., Acosta-Coll, M., Caicedo-Ortiz, J., & Sepúlveda-Ojeda, J. (2016). Design of a wireless sensor network for monitoring of flash floods in the city of barranquilla, colombia. [Diseño de una red de sensores inalámbricos para la monitorización de inundaciones repentinas en la ciudad de Barranquilla, Colombia] Ingeniare, 24(4), 581-599. Cama, A., Montoya, F.G., Gómez, J., De La Cruz, J.L., Manzano-Agugliaro, F., 2013. Integration of communication technologies in sensor networks to monitor the Amazon environment. Journal of Cleaner Production 59,32-42. < http://dx.doi.org/10.1016/j.jclepro.2013.06.041 >. Catania, P., Vallone, M., Lo Re, G., Ortolani, M., 2013 A wireless sensor network for vineyard management in Sicily (Italy). Agricultural Engineering International: CIGR Journal, 15(4), pp.139-146. Coelho, C., and Costa, S., 2010. Challenges for integrating seasonal climate forecasts in user Applications. Current Opinion in Environmental Sustainability, 2, 317-325. < http://dx.doi.org/10.1016/j.cosust.2010.09.002 >. COMAS-GONZÁLEZ, Z., ECHEVERRI-OCAMPO, I., ZAMORA-MUSA, R., Velez, J., Sarmiento, R., & Orellana, M. (2017). Tendencias recientes de la Educación Virtual y su fuerte conexión con los Entornos Inmersivos. Revista ESPACIOS, 38(15). Retrieved from: http://revistaespacios.com/a17v38n15/17381504.html D’Apuzzo, M., D’Arco, M., Pasquino, N., 2011. Design of experiments and data-fitting techniques applied to calibration of high-frequency electromagnetic field probes. Measurement (44), 1153- 1165. < http://dx.doi.org/10.1016/j.measurement.2011.03.007 >. De Sario, M., Katsouyanni, K., Michelozzi, P., 2013. Climate change, extreme weather events, air pollution and respiratory health in Europe. European Respiratory Journal 42(3), 826-843. < http://dx.doi.org/10.1183/09031936.00074712 >. Doeswijk, T.G., Keesman, K.J., 2005. Adaptive weather forecasting using local meteorological information. Biosystems Engineering 91(4), 421-431. < http://dx.doi.org/10.1016/j.biosystemseng.2005.05.013 >. Evans, K. Lou, E., Faulkner, G., 2013. Optimization of a Low-Cost Force Sensor for Spinal Orthosis Applications. IEEE Transactions on Instrumentation and Measurement 62, 3243-3250. < http://dx.doi.org/10.1109/TIM.2013.2272202 >. Ford, J.D., McDowell, G., Jones, J., 2014. The state of climate change adaptation in the Arctic. Environmental Research Letters 9(10), number 104005. < http://dx.doi.org/10.1088/1748- 9326/9/10/104005 >. Fedele, A., Mazzi, A., Niero, M., Zuliani, F., Scipioni, A., 2014. Can the Life Cycle Assessment methodology be adopted to support a single farm on its environmental impacts forecast evaluation between conventional and organic production? An Italian case study. Journal of Cleaner Production, 69, 49-59. < http://dx.doi.org/10.1016/j.jclepro.2014.01.034 >. Fridzon, M.B., Ermoshenko, Yu.M., 2009. Development of the specialized automatic meteorological observational network based on the cell phone towers and aimed to enhance feasibility and reliability of the dangerous weather phenomena forecasts. Russian Meteorology and Hydrology 34(2), 128-132. < http://dx.doi.org/10.3103/S1068373909020101 >. Geissler, K., Masciadri, E., 2006. Meteorological parameter analysis above Dome C using data from the European centre for medium-range weather forecasts. Publications of the Astronomical Society of the Pacific 118(845), 1048-1065. Geng, Z., Yang, F., Li, M., Wu, N. 2013. A bootstrapping-based statistical procedure for multivariate calibration of sensor arrays. Sensors and Actuators B: Chemical 188, 440-453. < http://dx.doi.org/10.1016/j.snb.2013.06.037 >. Ghile, Y., Schulze, R., 2009. Use of an Ensemble Re-ordering Method for disaggregation of seasonal categorical rainfall forecasts into conditioned ensembles of daily rainfall for hydrological forecasting. Journal of Hydrology, 371, 85-97. < http://dx.doi.org/10.1016/j.jhydrol.2009.03.019 >. Kaloxylos, A., Eigenmann, R., Teye, F., Politopoulou, Z., Wolfert, S., Shrank, C., Dillinger, M., Lampropoulou, I., Antoniou, E., Pesonen, L., Nicole, H., Thomas, F., Alonistioti, N., Kormentzas, G., 2012. Farm management systems and the Future Internet era. Computers and Electronics in Agriculture, 89, 130-144. < http://dx.doi.org/10.1016/j.compag.2012.09.002 >. Kousari, M.R., Zarch, M.A.A., 2011. Minimum, maximum, and mean annual temperatures, relative humidity, and precipitation trends in arid and semi-arid regions of Iran. Arabian Journal of Geosciences 4(5), 907-914. < http://dx.doi.org/10.1007/s12517-009-0113-6 >. Liu, C., Anuruddha, T.A.S., Minato, A., Ozawa, S., 2014. Development of portable CO2 monitoring System. 2nd Global Conference on Civil, Structural and Environmental Engineering, GCCSEE, Shenzhen, China, 838-841, 2547-2551. < http://dx.doi.org/10.4028/www.scientific.net/AMR.838-841.2547 >. Low, M., Lee, Y., Yong, K., 2009. Application of GR&R for productivity improvement. Conference Electronics Packaging Technology EPTC 996-999. < http://dx.doi.org/10.1109/EPTC.2009.5416396 >. Luo, Y., Chang, X., Peng, S., Khan, S., Wang, W., Zheng, Q., Cai, X., 2014. Short-term forecasting of daily reference evapotranspiration usingthe Hargreaves–Samani model and temperature forecasts. Agricultural Water Management, 136, 42-51. < http://dx.doi.org/10.1016/j.agwat.2014.01.006 >. Manivannan, S., Arumugam, R., Devi, P., Paramasivam, S., Salil, P., Subbarao, B., 2010. Optimization of heat sink EMI using Design of Experiments with numerical computational investigation and experimental validation. IEEE International Symposium on Electromagnetic Compatibility (EMC) 295-300. http://dx.doi.org/10.1109/ISEMC.2010.5711288 >. McIntosh, P., Pook, M., Risbey, J., Lisson, S., Rebbeck, M., 2007. Seasonal climate forecasts for agriculture: Towards better understanding and value. Field Crops Research, 104, 130-138. < http://dx.doi.org /10.1016/j.fcr.2007.03.019 >. Meléndez Pertuz, F., Gonzalez Coneo, J., Comas Gonzalez, Z., Nuñez Perez, B., & Viloria Molinares, P. V. (2017). Integridad estructural de tuberías de transporte de hidrocarburos: Panorama actual. Retrieved from: http://www.revistaespacios.com/a17v38n17/17381701.html . Michaels, P., 1982. Atmospheric pressure patterns, climatic change and winter wheat yields in North America. Geoforum, 13(3), 263-273. < http://doi:10.1016/0016-7185(82)90015-X >. Montoya F.G., Julio Gómez, J., Cama A., Zapata-Sierra, A., De La Cruz, J.L., Manzano-Agugliaro, F., 2013. A monitoring system for intensive agriculture based on mesh networks and the android system. Computers and Electronics in Agriculture. 99, 14-20. < http://dx.doi.org/10.1016/j.compag.2013.08.028 >. Mishra, A., Siderius, C., Aberson, K., van der Ploeg, M., Froebrich, J., 2013. Short-term rainfall forecasts as a soft adaptation to climate change in irrigation management in North-East India. Agricultural Water Management, 127, 97-106. < http://dx.doi.org/10.1016/j.agwat.2013.06.001 >. Ndzi, D., Harun, A., Ramli, F., Kamarudin, M., Zakaria, A., Shakaff, A., Jaafar, M., Zhou, S., Farook, R., 2014. Wireless sensor network coverage measurement and planning in mixed crop farming. Computers and Electronics in Agriculture, 105, 83-94. < http://dx.doi.org/10.1016/j.compag.2014.04.012 >. Open-Forecast, 2014. Open-Forecast Project [Available on line, accessed oct 25, 2014]. < https://sites.google.com/site/opforecast/ >. Palmer, T.N., 2014. More reliable forecasts with less precise computations: A fast-track route to cloud-resolved weather and climate simulators? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 372(2018). < http://dx.doi.org/10.1098/rsta.2013.0391 >. Peng, P., Wang, Q., Bennett, J., Pokhrel, P., Wang, Z., 2014. Seasonal precipitation forecasts over China using monthly large-scale oceanic-atmospheric indices. Journal of Hydrology, 519, 792-802. < http://dx.doi.org/10.1016/j.jhydrol.2014.08.012 >. Schmidt, M., Klein, D., Conrad, C., Dech, S., Paeth, H., 2014. On the relationship between vegetation and climate in tropical and northern Africa. Theoretical and Applied Climatology 115(1-2), 341-353. < http://dx.doi.org/10.1007/s00704-013-0900-6 >. Sung, W.T., Chen, J.H., Hsiao, C.L., Lin, J.S., 2014. Multi-sensors data fusion based on arduino board and XBee module technology. Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C, Taiwan. Article number 6845909, pp. 422-425. http://dx.doi.org/10.1109/IS3C.2014.117>. Taylor, 2009. 1523 Digital Indoor/Outdoor Thermometer/Hygrometer. [Available on line, accessed oct 27, 2014]. http://www.taylorusa.com/media/IBs/1523_ib.pdf Vantage, 2012. Vantage Pro2 [Available on line, accessed oct 25, 2014]. http://www.davisnet.com/product_documents/weather/manuals/07395-240_IM_06312.pdf/>. Varfi, M.S., Karacostas, T.S., Makrogiannis, T.J., Flocas, A.A., 2009. Characteristics of the extreme warm and cold days over Greece. Advances in Geosciences 20, 45-50. Weber, P., Zagrabski, M., Wojciechowski, B., Nikodem, m., Kȩpa, K., Berezowski, K., 2014. Calibration of RO-based temperature sensors for a toolset for measuring thermal behavior of FPGA devices. Microelectronics Journal 1-11. http://dx.doi.org/10.1016/j.mejo.2014.06.004>. Yan, H., Zhang, J., Hou, Y., He, Y., 2009. Estimation of air temperature from MODIS data in east China. International Journal of Remote Sensing 30(23), 6261-6275. http://dx.doi.org/10.1080/01431160902842375 />. Yu, Q.S., Duan, M.Y., Zhang, T.S., Wu, H.G., Lu, S.K., 2014. An wireless collection and monitoring system design based on Arduino. Advanced Materials Research 971-973, 1076- 1080. < http://dx.doi.org/10.4028/www.scientific.net/AMR.971-973.1076 >. Zhang, D.F., Ma, R., Lu, H.W., Yang, C.J., Wu, G. A method of evaluating the distribution system reliability under freezing disaster weather based on the continuity of meteorological parameters. Power System Protection and Control. 2013. (22), 51-56. Zinyengere, N., Mhizha, T., Mashonjowa, E., Chipindu, B., Geerts. S., Raes, D., 2011. Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agricultural and Forest Meteorology, 151, 1792-1799. http://dx.doi.org/10.1016/j.agrformet.2011.07.015 >.
dc.rights.spa.fl_str_mv Atribución – No comercial – Compartir igual
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.coar.spa.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Atribución – No comercial – Compartir igual
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.publisher.spa.fl_str_mv Revista Espacios
institution Corporación Universidad de la Costa
bitstream.url.fl_str_mv https://repositorio.cuc.edu.co/bitstream/11323/1870/1/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf
https://repositorio.cuc.edu.co/bitstream/11323/1870/2/license.txt
https://repositorio.cuc.edu.co/bitstream/11323/1870/4/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf.jpg
https://repositorio.cuc.edu.co/bitstream/11323/1870/5/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf.txt
bitstream.checksum.fl_str_mv 3b16fddde33e73df41e6e14c9881837d
8a4605be74aa9ea9d79846c1fba20a33
f17ccd963d1a96b4515b73217f70a62b
d1cc9a56d92842be54dcb45cf0215897
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Universidad de La Costa
repository.mail.fl_str_mv bdigital@metabiblioteca.com
_version_ 1808400264319729664
spelling Cama Pinto, Alejandroa2e20771fdbf383813a600293f3732f6Piñeres Espitia, Gabriel Dario1560714ef1fd6ceda28e93b1c47da050Rosa Morron, Daniel Eduardo de laf23c4670fcb44d7d568390eaf173a0a2300Estevez, Francisco644769ab65fb8078e90c07cb7f139458300Cama Pinto, Dora3743283716944d8510b6e133f3a4e7d62018-11-26T16:29:51Z2018-11-26T16:29:51Z2017-09-0507981015http://hdl.handle.net/11323/1870Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/El objetivo de esta investigación es desarrollar un prototipo de estación meteorológica secundaria para mediciones de temperatura, humedad y presión atmosférica. Para validar la operación, se realizó un análisis de varianza y un diseño experimental r&R. Los sensores TMP36, RHT03 y BMP085 fueron seleccionados para la plataforma Arduino UNO y calibrados con una estación meteorológica y un higrómetro digital certificado por las autoridades. Nuestro sistema utiliza hardware y software abiertos y es una estación meteorológica de bajo costo diseñada para el análisis ambiental.The aim of this research is to develop a secondary weather station prototype for measurements of temperature, humidity and atmospheric pressure. To validate the operation, a variance analysis and an experimental design r&R were conducted. The TMP36, RHT03 and BMP085 sensors were selected for Arduino UNO platform and calibrated with a weather station and a digital hygrometer certifies by the authorities. Our system uses open hardware and software and is a low cost weather station designed for environmental analysisengRevista EspaciosAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Repeatability and reproducibility (r&R)SensorsVariance analysisWeather stationEstación meteorológicaanálisis de varianzarepetitividad y reproducibilidad (r&R)sensoresDesign of a low cost weather station for detecting environmental changesArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionAbistado, K.G., Arellano, C.N., Maravillas, E.A., 2014. Weather Forecasting Using Artificial Neural Network and Bayesian Network. Journal of Advanced Computational Intelligence and Intelligent Informatics 18(5), 812-816. Antolik, M., 2000. An overview of the National Weather Service’s centralized statistical quantitative precipitation forecasts. Journal of Hydrology, 239, 306–337. Arduino, 2014. Arduino-Home [Available on line, accessed oct 25, 2014]. < http://www.arduino.cc/ >. Anzalone, G.C., Glover, A.G., Pearce, J.M., 2013. Open-source colorimeter. Sensors. 13(4), 5338-5346. < http://dx.doi.org/10.3390/s130405338 >. Azmil, M. S. A., Ya'acob, N., Tahar, K. N. and Sarnin, S. S. Wireless fire detection monitoring system for fire and rescue application. 2015 IEEE 11th International Colloquium on Signal Processing & Its Applications (CSPA), Kuala Lumpur, 2015, pp. 84-89. doi: 10.1109/CSPA.2015.7225623. Blank S., Bartolein, C., Meyer, A., Ostermeier, R., Rostanin, O., 2013. iGreen: A ubiquitous dynamic network to enable manufacturer independent data exchange in future precision farming. Computers and Electronics in Agriculture, 98, 109-116. < http://dx.doi.org/10.1016/j.compag.2013.08.001 >. Borick, C.P., Rabe, B.G., 2014. Weather or not? Examining the impact of meteorological conditions on public opinion regarding global warming. Weather, Climate, and Society 6(3), 413-424. < http://dx.doi.org/10.1175/WCAS-D-13-00042.1 >. Cama-Pinto, A., Piñeres-Espitia, G., Caicedo-Ortiz, J., Ramírez-Cerpa, E., Betancur-Agudelo, L. and Gómez-Mula, F. Received strength signal intensity performance analysis in wireless sensor network using arduino platform and xbee wireless modules. International Journal of Distributed Sensor Networks, 13(7):1550147717722691, 2017. Cama-Pinto, A., Piñeres-Espitia, G., Zamora-Musa, R., Acosta-Coll, M., Caicedo-Ortiz, J., & Sepúlveda-Ojeda, J. (2016). Design of a wireless sensor network for monitoring of flash floods in the city of barranquilla, colombia. [Diseño de una red de sensores inalámbricos para la monitorización de inundaciones repentinas en la ciudad de Barranquilla, Colombia] Ingeniare, 24(4), 581-599. Cama, A., Montoya, F.G., Gómez, J., De La Cruz, J.L., Manzano-Agugliaro, F., 2013. Integration of communication technologies in sensor networks to monitor the Amazon environment. Journal of Cleaner Production 59,32-42. < http://dx.doi.org/10.1016/j.jclepro.2013.06.041 >. Catania, P., Vallone, M., Lo Re, G., Ortolani, M., 2013 A wireless sensor network for vineyard management in Sicily (Italy). Agricultural Engineering International: CIGR Journal, 15(4), pp.139-146. Coelho, C., and Costa, S., 2010. Challenges for integrating seasonal climate forecasts in user Applications. Current Opinion in Environmental Sustainability, 2, 317-325. < http://dx.doi.org/10.1016/j.cosust.2010.09.002 >. COMAS-GONZÁLEZ, Z., ECHEVERRI-OCAMPO, I., ZAMORA-MUSA, R., Velez, J., Sarmiento, R., & Orellana, M. (2017). Tendencias recientes de la Educación Virtual y su fuerte conexión con los Entornos Inmersivos. Revista ESPACIOS, 38(15). Retrieved from: http://revistaespacios.com/a17v38n15/17381504.html D’Apuzzo, M., D’Arco, M., Pasquino, N., 2011. Design of experiments and data-fitting techniques applied to calibration of high-frequency electromagnetic field probes. Measurement (44), 1153- 1165. < http://dx.doi.org/10.1016/j.measurement.2011.03.007 >. De Sario, M., Katsouyanni, K., Michelozzi, P., 2013. Climate change, extreme weather events, air pollution and respiratory health in Europe. European Respiratory Journal 42(3), 826-843. < http://dx.doi.org/10.1183/09031936.00074712 >. Doeswijk, T.G., Keesman, K.J., 2005. Adaptive weather forecasting using local meteorological information. Biosystems Engineering 91(4), 421-431. < http://dx.doi.org/10.1016/j.biosystemseng.2005.05.013 >. Evans, K. Lou, E., Faulkner, G., 2013. Optimization of a Low-Cost Force Sensor for Spinal Orthosis Applications. IEEE Transactions on Instrumentation and Measurement 62, 3243-3250. < http://dx.doi.org/10.1109/TIM.2013.2272202 >. Ford, J.D., McDowell, G., Jones, J., 2014. The state of climate change adaptation in the Arctic. Environmental Research Letters 9(10), number 104005. < http://dx.doi.org/10.1088/1748- 9326/9/10/104005 >. Fedele, A., Mazzi, A., Niero, M., Zuliani, F., Scipioni, A., 2014. Can the Life Cycle Assessment methodology be adopted to support a single farm on its environmental impacts forecast evaluation between conventional and organic production? An Italian case study. Journal of Cleaner Production, 69, 49-59. < http://dx.doi.org/10.1016/j.jclepro.2014.01.034 >. Fridzon, M.B., Ermoshenko, Yu.M., 2009. Development of the specialized automatic meteorological observational network based on the cell phone towers and aimed to enhance feasibility and reliability of the dangerous weather phenomena forecasts. Russian Meteorology and Hydrology 34(2), 128-132. < http://dx.doi.org/10.3103/S1068373909020101 >. Geissler, K., Masciadri, E., 2006. Meteorological parameter analysis above Dome C using data from the European centre for medium-range weather forecasts. Publications of the Astronomical Society of the Pacific 118(845), 1048-1065. Geng, Z., Yang, F., Li, M., Wu, N. 2013. A bootstrapping-based statistical procedure for multivariate calibration of sensor arrays. Sensors and Actuators B: Chemical 188, 440-453. < http://dx.doi.org/10.1016/j.snb.2013.06.037 >. Ghile, Y., Schulze, R., 2009. Use of an Ensemble Re-ordering Method for disaggregation of seasonal categorical rainfall forecasts into conditioned ensembles of daily rainfall for hydrological forecasting. Journal of Hydrology, 371, 85-97. < http://dx.doi.org/10.1016/j.jhydrol.2009.03.019 >. Kaloxylos, A., Eigenmann, R., Teye, F., Politopoulou, Z., Wolfert, S., Shrank, C., Dillinger, M., Lampropoulou, I., Antoniou, E., Pesonen, L., Nicole, H., Thomas, F., Alonistioti, N., Kormentzas, G., 2012. Farm management systems and the Future Internet era. Computers and Electronics in Agriculture, 89, 130-144. < http://dx.doi.org/10.1016/j.compag.2012.09.002 >. Kousari, M.R., Zarch, M.A.A., 2011. Minimum, maximum, and mean annual temperatures, relative humidity, and precipitation trends in arid and semi-arid regions of Iran. Arabian Journal of Geosciences 4(5), 907-914. < http://dx.doi.org/10.1007/s12517-009-0113-6 >. Liu, C., Anuruddha, T.A.S., Minato, A., Ozawa, S., 2014. Development of portable CO2 monitoring System. 2nd Global Conference on Civil, Structural and Environmental Engineering, GCCSEE, Shenzhen, China, 838-841, 2547-2551. < http://dx.doi.org/10.4028/www.scientific.net/AMR.838-841.2547 >. Low, M., Lee, Y., Yong, K., 2009. Application of GR&R for productivity improvement. Conference Electronics Packaging Technology EPTC 996-999. < http://dx.doi.org/10.1109/EPTC.2009.5416396 >. Luo, Y., Chang, X., Peng, S., Khan, S., Wang, W., Zheng, Q., Cai, X., 2014. Short-term forecasting of daily reference evapotranspiration usingthe Hargreaves–Samani model and temperature forecasts. Agricultural Water Management, 136, 42-51. < http://dx.doi.org/10.1016/j.agwat.2014.01.006 >. Manivannan, S., Arumugam, R., Devi, P., Paramasivam, S., Salil, P., Subbarao, B., 2010. Optimization of heat sink EMI using Design of Experiments with numerical computational investigation and experimental validation. IEEE International Symposium on Electromagnetic Compatibility (EMC) 295-300. http://dx.doi.org/10.1109/ISEMC.2010.5711288 >. McIntosh, P., Pook, M., Risbey, J., Lisson, S., Rebbeck, M., 2007. Seasonal climate forecasts for agriculture: Towards better understanding and value. Field Crops Research, 104, 130-138. < http://dx.doi.org /10.1016/j.fcr.2007.03.019 >. Meléndez Pertuz, F., Gonzalez Coneo, J., Comas Gonzalez, Z., Nuñez Perez, B., & Viloria Molinares, P. V. (2017). Integridad estructural de tuberías de transporte de hidrocarburos: Panorama actual. Retrieved from: http://www.revistaespacios.com/a17v38n17/17381701.html . Michaels, P., 1982. Atmospheric pressure patterns, climatic change and winter wheat yields in North America. Geoforum, 13(3), 263-273. < http://doi:10.1016/0016-7185(82)90015-X >. Montoya F.G., Julio Gómez, J., Cama A., Zapata-Sierra, A., De La Cruz, J.L., Manzano-Agugliaro, F., 2013. A monitoring system for intensive agriculture based on mesh networks and the android system. Computers and Electronics in Agriculture. 99, 14-20. < http://dx.doi.org/10.1016/j.compag.2013.08.028 >. Mishra, A., Siderius, C., Aberson, K., van der Ploeg, M., Froebrich, J., 2013. Short-term rainfall forecasts as a soft adaptation to climate change in irrigation management in North-East India. Agricultural Water Management, 127, 97-106. < http://dx.doi.org/10.1016/j.agwat.2013.06.001 >. Ndzi, D., Harun, A., Ramli, F., Kamarudin, M., Zakaria, A., Shakaff, A., Jaafar, M., Zhou, S., Farook, R., 2014. Wireless sensor network coverage measurement and planning in mixed crop farming. Computers and Electronics in Agriculture, 105, 83-94. < http://dx.doi.org/10.1016/j.compag.2014.04.012 >. Open-Forecast, 2014. Open-Forecast Project [Available on line, accessed oct 25, 2014]. < https://sites.google.com/site/opforecast/ >. Palmer, T.N., 2014. More reliable forecasts with less precise computations: A fast-track route to cloud-resolved weather and climate simulators? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 372(2018). < http://dx.doi.org/10.1098/rsta.2013.0391 >. Peng, P., Wang, Q., Bennett, J., Pokhrel, P., Wang, Z., 2014. Seasonal precipitation forecasts over China using monthly large-scale oceanic-atmospheric indices. Journal of Hydrology, 519, 792-802. < http://dx.doi.org/10.1016/j.jhydrol.2014.08.012 >. Schmidt, M., Klein, D., Conrad, C., Dech, S., Paeth, H., 2014. On the relationship between vegetation and climate in tropical and northern Africa. Theoretical and Applied Climatology 115(1-2), 341-353. < http://dx.doi.org/10.1007/s00704-013-0900-6 >. Sung, W.T., Chen, J.H., Hsiao, C.L., Lin, J.S., 2014. Multi-sensors data fusion based on arduino board and XBee module technology. Proceedings - 2014 International Symposium on Computer, Consumer and Control, IS3C, Taiwan. Article number 6845909, pp. 422-425. http://dx.doi.org/10.1109/IS3C.2014.117>. Taylor, 2009. 1523 Digital Indoor/Outdoor Thermometer/Hygrometer. [Available on line, accessed oct 27, 2014]. http://www.taylorusa.com/media/IBs/1523_ib.pdf Vantage, 2012. Vantage Pro2 [Available on line, accessed oct 25, 2014]. http://www.davisnet.com/product_documents/weather/manuals/07395-240_IM_06312.pdf/>. Varfi, M.S., Karacostas, T.S., Makrogiannis, T.J., Flocas, A.A., 2009. Characteristics of the extreme warm and cold days over Greece. Advances in Geosciences 20, 45-50. Weber, P., Zagrabski, M., Wojciechowski, B., Nikodem, m., Kȩpa, K., Berezowski, K., 2014. Calibration of RO-based temperature sensors for a toolset for measuring thermal behavior of FPGA devices. Microelectronics Journal 1-11. http://dx.doi.org/10.1016/j.mejo.2014.06.004>. Yan, H., Zhang, J., Hou, Y., He, Y., 2009. Estimation of air temperature from MODIS data in east China. International Journal of Remote Sensing 30(23), 6261-6275. http://dx.doi.org/10.1080/01431160902842375 />. Yu, Q.S., Duan, M.Y., Zhang, T.S., Wu, H.G., Lu, S.K., 2014. An wireless collection and monitoring system design based on Arduino. Advanced Materials Research 971-973, 1076- 1080. < http://dx.doi.org/10.4028/www.scientific.net/AMR.971-973.1076 >. Zhang, D.F., Ma, R., Lu, H.W., Yang, C.J., Wu, G. A method of evaluating the distribution system reliability under freezing disaster weather based on the continuity of meteorological parameters. Power System Protection and Control. 2013. (22), 51-56. Zinyengere, N., Mhizha, T., Mashonjowa, E., Chipindu, B., Geerts. S., Raes, D., 2011. Using seasonal climate forecasts to improve maize production decision support in Zimbabwe. Agricultural and Forest Meteorology, 151, 1792-1799. http://dx.doi.org/10.1016/j.agrformet.2011.07.015 >.ORIGINALDesign of a low cost weather station for detecting environmental changes.pdfDesign of a low cost weather station for detecting environmental changes.pdfapplication/pdf1553427https://repositorio.cuc.edu.co/bitstream/11323/1870/1/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf3b16fddde33e73df41e6e14c9881837dMD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstream/11323/1870/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52open accessTHUMBNAILDesign of a low cost weather station for detecting environmental changes.pdf.jpgDesign of a low cost weather station for detecting environmental changes.pdf.jpgimage/jpeg92871https://repositorio.cuc.edu.co/bitstream/11323/1870/4/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf.jpgf17ccd963d1a96b4515b73217f70a62bMD54open accessTEXTDesign of a low cost weather station for detecting environmental changes.pdf.txtDesign of a low cost weather station for detecting environmental changes.pdf.txttext/plain41181https://repositorio.cuc.edu.co/bitstream/11323/1870/5/Design%20of%20a%20low%20cost%20weather%20station%20for%20detecting%20environmental%20changes.pdf.txtd1cc9a56d92842be54dcb45cf0215897MD55open access11323/1870oai:repositorio.cuc.edu.co:11323/18702023-12-14 17:47:30.05open accessRepositorio Universidad de La Costabdigital@metabiblioteca.comTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=

Publicaciones similares