Tin Dioxide Sensor Array Network for Air Quality Monitoring

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-44 Number-1
Year of Publication : 2017
Authors : Kavita K. Ahuja, N. N. Jani
DOI :  10.14445/22312803/IJCTT-V44P105

MLA

Kavita K. Ahuja, N. N. Jani   "Tin Dioxide Sensor Array Network for Air Quality Monitoring". International Journal of Computer Trends and Technology (IJCTT) V44(1):29-32, February 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
This review paper presents a sensor network for outdoor air quality monitoring whose nodes includes sensor array which capture the air pollutant gases measurement with CO2 calibration using sensors which are located at different locations of urban city of Gujarat state of India. This calibration is performed on period of time of the year 2016 with daily basis. The research is considered on the analysis of pollutant gases which emits from industries and vehicles are CO2, CO, NO2. Gas concentration values are plotted on graphs to make better and efficient analysis. The main objective of the work is to increase awareness and alertness for people of urban areas towards their health life in aspect of the air which they take while breathing.

References
[1] M. Balabanovi´c and Y. Shoham. Fab: content based, collaborative recommendati-on. Communications of the ACM,40(3):66–72, 1997.
[2] A. B. BarragansMart?nez, E. Costa Montenegro, J. C. Burguillo-Rial, M. Rey-L´opez, F. A. Mikic-Fonte, and A. Peleteiro-Ramallo. A hybrid content-based and item-based collaborative filtering approach to recommend tv programs enhanced with singular value decomposition. Information Sciences, 180(22):4290–4311, 2010.
[3] I. Bartolini, Z. Zhang, and D. Papadias. Collaborative filtering with personalized skylines. IEEE Transactions on Knowledge and Data Engineering, 23(2):190–203, 2011.
[4] J. Bennett and S. Lanning. The Netflix prize.In Proceedings of KDD Cup and Workshop, 2007.
[5] D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993–1022,2003.
[6] L. M. de Campos, J. M. Fern´andez-Luna, J. F. Huete, and M. A. Rueda-Morales.Combining content-based and collaborative recommendations: A hybrid approach based on bayesian networks. International Journal of Approximate Reasoning,51(7):785–799, 2010.
[7] Z. Gantner, L. Drumond, C. Freudenthaler, S. Rendle, and L. Schmidt-Thieme.Learning attribute to feature map-pings for cold start recommendations.In Proceedings of the IEEEInternational Conference on Data Mining (ICDM), 2010.
[8] J. L. Herlocker, J. A. Konstan, A. Borchers, and J. Riedl.An algorithmic framework for performing collaborative filtering.In Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 1999.
[9] G. Adomavicius and A. Tuzhilin, “Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions,” IEEE Trans. Knowl. Data Eng., vol. 17, no. 6, 734–749, Jun. 2005.
[10] D. Agarwal and B.-C. Chen, “Regression-based latent factor mod-els,” in Proc. ACM SIGKDD Int. Conf. Knowl.Discovery Data Min-ing, 2009, pp. 19–28.
[11] D. Agarwal and B.-C. Chen, “fLDA: Matrix factorization through latent dirichletallocation,” in Proc. 3rd Int. Conf. Web Search Data Mining, 2010, pp. 91–100.
[12] D. Almazro, G. Shahatah, L. Albdulkarim, M. Kherees, R. Martinez, and W. Nzoukou, “A survey paper on recommender systems,”CoRR, abs/1006.5278, 2010.
[13] M. Balabanovi_c and Y. Shoham, “Fab: Content-based, collaborative recommen-dation,” Commun. ACM, vol. 40, no. 3, pp. 66–72, 1997.
[14] A. B. Barrag_ans-Mart_?nez, E. Costa-Montenegro, J. C. Burguillo-Rial, M. Rey-Lopez,_ F. A. MikicFonte, and A. Peleteiro-Ramallo, “A hybrid content-based and item-based collaborative filtering approach to recommend tv programs enhanced with singular value decomposition,” Inf. Sci., vol. 180, no. 22, pp. 4290–4311, 2010.
[15] I. Bartolini, Z. Zhang, and D. Papadias, “Collaborative filtering with personalized skylines,” IEEE Trans. Knowl. Data Eng., vol. 23, no. 2, pp. 190–203, Feb. 2011.
[16] J. Bennett and S. Lanning, “The Netflix prize,” in Proc. KDD Cup Workshop, 2007, pp.3–6.
[17] D. M. Blei, A. Y. Ng, and M. I. Jordan, “Latent dirichlet allocation,” J. Mach. Learn. Res., vol. 3, pp. 993–1022, 2003.
[18] J. Bobadilla, F. Ortega, A. Hernando, and A. Guti_errez, “Recommender systems survey,”Knowl. Based Syst., vol. 46,pp. 109–132, 2013.

Keywords
Air Quality, Sensor network, Urban Area.