Rede de Sensores para Controle Inteligente de Ambientes
Abstract
In general, laboratories or labs are workplaces that provide controlled conditions for experiments and measurements to be performed. For this reason, controlling temperature and humidity is an important requirement that needs to be achieved in order to guarantee the reproducibility of processes carried out in labs. Aiming to introduce efficient environmental controlling mechanisms, we present in this paper an intelligent environmental control system based on sensors network and pattern classification. Our system uses the information generated by the sensors to make decisions for constant controlling of temperature and relative humidity within the lab.
References
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Barroca, N., Borges, L. M., Velez, F. J., Monteiro, F., G´orski, M., and Castro-Gomes, J. (2013). Wireless sensor networks for temperature and humidity monitoring within concrete structures. Construction and Building Materials, 40(0):1156 – 1166.
Berry, M. J. and Linoff, G. S. (2004). Data Mining Techniques: for Marketing, Sales, and Customer Relationship Mangement. Wiley Publishing, Inc, Indianapolis, Indiana, USA, 2nd edition.
da Silva, L. T. (2013). Uma proposta de automação residencial utilizando a plataforma de prototipagem eletrônica arduino. Revista Tecnologias em Projeção.
Faceli, K., Lorena, A. C., Gama, J., and de Carvalho, A. C. (2011). Inteligência Artificial: uma Abordagem de Aprendizado de Máquina. LTC - Livros técnicos e científicos Editora Ltda.
Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver & Boyd.
Halkidi, M., Batistakis, Y., and Vazirgiannis, M. (2002). Clustering validity checking methods: part ii. SIGMOD Rec., 31 (3):19–27.
Lorena, A. C. and de Carvalho, A. C. P. L. F. (2007). Uma introdução às support vector machines. Revista de Informática Teórica e Aplicada (RITA), 14(2):43 –67.
Margolis, M. (2011). Arduino Cookbook. O’Reilly Media, USA, 2nd edition.
Maycon J. C. Mesquita, Jose C. G. Neto, W. R. M. A. (2014). Sistema de controle e supervisão residencial utilizando plataforma arduino.
McRoberts, M. (2011). Beginning Arduino. Apress, USA, 1st edition.
Mitchell, T. M. (1997). Machine Learning. McGraw-Hill, Inc., New York, NY, USA, 1st edition.
Vera-Repullo, J., Ruiz-Peñalver, L., Jiménez-Buendía, M., Rosillo, J., and Molina-Martínez, J. (2015). Software for the automatic control of irrigation using weighing-drainage lysimeters. Agricultural Water Management, 151(0):4 – 12. New proposals in the automation and remote control of water management in agriculture: agromotic systems.
Xu, R. and Wunsch, II, D. (2005). Survey of clustering algorithms. IEEE Transactions on Neural Networks, 16(3):645–678.
Yuwono, M., Guo, Y., Wall, J., Li, J., West, S., Platt, G., and Su, S. W. (2015). Unsupervised feature selection using swarm intelligence and consensus clustering for automatic fault detection and diagnosis in heating ventilation and air conditioning systems. Applied Soft Computing, 34(0):402 – 425.
Published
2016-07-04
How to Cite
DA SILVA, Artejose Revoredo; XAVIER-JÚNIOR, João C. ; DA SILVA, Ivanovitch Medeiros Dantas.
Rede de Sensores para Controle Inteligente de Ambientes. In: PROCEEDINGS OF BRAZILIAN SYMPOSIUM ON UBIQUITOUS AND PERVASIVE COMPUTING (SBCUP), 8. , 2016, Porto Alegre.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 1096-1105.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2016.9458.
