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...

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Main Authors:	Cama Pinto, Alejandro, Piñeres Espitia, Gabriel Dario, Rosa Morron, Daniel Eduardo de la, Estevez, Francisco, Cama Pinto, Dora
Format:	Article in Journal/Newspaper
Language:	English
Published:	Revista Espacios 2017
Subjects:	Repeatability and reproducibility (r&R) Sensors Variance analysis Weather station Estación meteorológica análisis de varianza repetitividad y reproducibilidad (r&R) sensores Arctic
Online Access:	http://hdl.handle.net/11323/1870 https://repositorio.cuc.edu.co/

id	ftunivcosta:oai:repositorio.cuc.edu.co:11323/1870
record_format	openpolar
institution	Open Polar
collection	REDICUC - Repositorio Universidad de La Costa
op_collection_id	ftunivcosta
language	English
topic	Repeatability and reproducibility (r&R) Sensors Variance analysis Weather station Estación meteorológica análisis de varianza repetitividad y reproducibilidad (r&R) sensores
spellingShingle	Repeatability and reproducibility (r&R) Sensors Variance analysis Weather station Estación meteorológica análisis de varianza repetitividad y reproducibilidad (r&R) sensores Cama Pinto, Alejandro Piñeres Espitia, Gabriel Dario Rosa Morron, Daniel Eduardo de la Estevez, Francisco Cama Pinto, Dora Design of a low cost weather station for detecting environmental changes
topic_facet	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. 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 analysis
format	Article in Journal/Newspaper
author	Cama Pinto, Alejandro Piñeres Espitia, Gabriel Dario Rosa Morron, Daniel Eduardo de la Estevez, Francisco Cama Pinto, Dora
author_facet	Cama Pinto, Alejandro Piñeres Espitia, Gabriel Dario Rosa Morron, Daniel Eduardo de la Estevez, Francisco Cama Pinto, Dora
author_sort	Cama Pinto, Alejandro
title	Design of a low cost weather station for detecting environmental changes
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
publisher	Revista Espacios
publishDate	2017
url	http://hdl.handle.net/11323/1870 https://repositorio.cuc.edu.co/
genre	Arctic
genre_facet	Arctic
op_relation	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 >. 07981015 http://hdl.handle.net/11323/1870 Corporación Universidad de la Costa REDICUC - Repositorio CUC https://repositorio.cuc.edu.co/
op_rights	Atribución – No comercial – Compartir igual info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2
op_doi	https://doi.org/10.3390/s130405338
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spelling	ftunivcosta:oai:repositorio.cuc.edu.co:11323/1870 2024-01-14T10:03:20+01:00 Design of a low cost weather station for detecting environmental changes Cama Pinto, Alejandro Piñeres Espitia, Gabriel Dario Rosa Morron, Daniel Eduardo de la Estevez, Francisco Cama Pinto, Dora 2017-09-05 application/pdf http://hdl.handle.net/11323/1870 https://repositorio.cuc.edu.co/ eng eng Revista Espacios 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 >. 07981015 http://hdl.handle.net/11323/1870 Corporación Universidad de la Costa REDICUC - Repositorio CUC https://repositorio.cuc.edu.co/ Atribución – No comercial – Compartir igual info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 Repeatability and reproducibility (r&R) Sensors Variance analysis Weather station Estación meteorológica análisis de varianza repetitividad y reproducibilidad (r&R) sensores Artículo de revista http://purl.org/coar/resource_type/c_6501 Text info:eu-repo/semantics/article http://purl.org/redcol/resource_type/ART info:eu-repo/semantics/acceptedVersion http://purl.org/coar/version/c_ab4af688f83e57aa 2017 ftunivcosta https://doi.org/10.3390/s130405338 2023-12-17T19:23:59Z 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 analysis Article in Journal/Newspaper Arctic REDICUC - Repositorio Universidad de La Costa

Design of a low cost weather station for detecting environmental changes

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