Abstract
The quality of air plays a predominant role in human health and has greater influence on life expectancy. In our project, five different gas sensors are used to evaluate the quality of air. The quality of air is classified into good, moderate, unhealthy, and hazardous. For instance, this work has been conducted in Coimbatore (smart city). The presence of harmful gases determines the nature of the air and this classification can be monitored periodically by measuring the amount of SO2 and NO2, which acts as a vital parameter. These measured and classified data can be transferred to public access and decision can be taken, so that we have developed an open access website to store and display the values of classified air quality. This information to the people can be used to improve quality of life by improving the quality of air.
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Change history
18 February 2024
A correction has been published.
References
Embedded traffic control system using wireless ad hoc sensors. Middle-East J. Sci. Res. 20(2), 225–227 (2014)
Urban air pollution monitoring system with forecasting models. IEEE Sens. J. 16(8), 2598–2606 (2016)
IoT for environmental variables in urban areas. In: ELSEVIER on International Conference Ambient Systems, Networks and Technologies, ANT-2017, vol. 109, pp. 67–74 (2017)
Augustine, I., Subramaniam, K.: LPG consumption, monitoring and Booking system. Int. J. Appl. Eng. Res. 4, 3993–3998 (2016)
Ayele, T.W., Mehta, R.: Air pollution monitoring and prediction using IOT. In: 2nd International Conference on Inventive Communication and Computational Technologies (2018)
Bales, E., Nikzad, N., Quick, N., Ziftci, C., Patrick, K., Griswold, W.: Citisense: mobile air quality sensing for individuals and communities (2012)
Biswas, J., Upadhyay, E., Nayak, M., Yadav, A.K.: An analysis of ambient air quality conditions over Delhi, India from 2004 to 2009. Atmos. Clim. Sci. 1, 214–224 (2011)
Chittilappilly, A.J., Subramaniam, K.: SVM based defect detection for industrial applications. In: 2017 4th International Conference on Advanced Computing and Communication Systems (ICACCS), pp. 1–5 (2017)
Fuertes, W., Carrrera, D., Villacis, C., Toulkeridis, T., Galarraga, F., Torres, E., Aules, H.: Distributed system as Internet of Things for a new-low-cost, air pollution wireless monitoring on real time. In: 2015 IEEE/ACM 19th International Symposium on Distributed Simulation and Real Time Applications (2015)
Goyal, S.K., Ghatge, S.V., Nema, P., Tamhane, S.M.: Understanding urban vehicular pollution problems vis-a-vis ambient air quality-case study of mega city. Environ. Monit. Assess. 199, 557–569 (2006)
Gurjar, B.R., Aardenne, J., Lelievelda, J., Mohan, M.: Emission estimates and trends for mega city Delhi and implication (2004)
Ngoc, T.Q., Lee, J., Gil, K.J.: An ESB based micro scale urban air quality monitoring system. In: Fifth IEEE International Conference on Networking, Architecture, and Storage (2010)
Paulraj, M.P., Subramaniam, K., Yaccob, S.B., Adom, A.H.B.: Application specific multichannel EEG data acquisition system for portable biomedical application. In: Proceedings of the Conference on MUCET, pp. 15–28 (2012)
Paulraj, M.P., Subramaniam, K., Yaccob, S.B., Adom, A.H.B., Hema, C.R.: A Machine learning approach for distinguishing hearing perception level using auditory evoked potentials. In: IEEE EMBS Conference on Bio-Medical Engineering Sciences, pp. 991–996 (2014)
Pachiyaannan, M., Venkatesan, G.P.: Designing of Wireless Sensor Node using MSP (2013)
Raipure, S., Mehetre, D.: Wireless Sensor Network Based Pollution Monitoring System in Metropolitan Cities. In: IEEE on International Conference (2015)
Ramakrishna, G., Kasthala, S., Venkatesan, G.P.: Arduino based automatic vehicle control system. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2(6) (2017)
Rybarczyk, Y., Zalakeviciute, R.: Machine learning approach to forecasting urban pollution. IEEE J. (2016)
Shah, J., Mishra, B.: IOT enabled environmental monitoring system for smart cities. In: International Conference on Internet of Things and Applications (IOTA) (2016)
Sharma, N., Taneja, S., Sagar, V., Bhatt, A.: Forecasting air pollution load in Delhi using data analysis tools. In: International Conference on Computational Intelligence and Data Science (2016)
Sumithra, D.A., Ida, J.J., Karthika, K., Gavaskar, D.S.: A smart environmental monitoring system using Internet of Things. IJSEAS J. 2(3) (2016)
Tudose, D.S., Patrascu, T.A., Voinescu, A., Tataroiu, R., Tapus, N.: Mobile sensors in air pollution measurement. In: 8th Workshop on Positing Navigation and Communication, pp. 166–170 (2011)
Xi, X., Wei, Z., Rui, X., Wang, Y., Bai, X., Yin, W., Don, J.: A comprehensive evolution of air pollution prediction improvement by a machine learning method. In: IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI) (2015)
Xiaojun, C., Liu, X., Xu, P.: IOT - based air pollution monitoring and forecasting system. In: International Conference on Computer and Computational Sciences (2015)
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Gokul, P., Srikanth, J., Inbarasu, G., Subramaniyam, K., Prasanna Venkatesan, G.K.D. (2020). RETRACTED CHAPTER: Internet of Things Based Air Pollution Monitoring and Forecasting System. In: Karrupusamy, P., Chen, J., Shi, Y. (eds) Sustainable Communication Networks and Application. ICSCN 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-030-34515-0_46
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