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Wireless Personal Communications

, Volume 108, Issue 4, pp 2499–2515 | Cite as

A Comprehensive Review of Wireless Sensor Networks Based Air Pollution Monitoring Systems

  • R. Kingsy GraceEmail author
  • S. Manju
Article
  • 151 Downloads

Abstract

Wireless Sensor Networks (WSN) consists of sensors used for sensing environmental conditions and many more applications in real world. Air pollution is a threat to the life of humans. To control the air pollution it is necessary to monitor the pollutant gases in periodically. Various air pollution monitoring systems using sensor network have been developed, deployed and tested in the literature. This paper presents a comparative study about the literature for air pollution monitoring systems based on the classification such as stationary air pollution monitoring systems, dynamic air pollution monitoring systems and pollution data analysis techniques. These pollution monitoring systems are compared based on the methodologies followed, microcontroller used, communication device used, pollutants analyzed using sensors, evaluation attributes, tested location and performance of the system. This paper also discusses the merits and demerits of the air pollution monitoring systems.

Keywords

Air pollution Sensor network Air quality 

Notes

Acknowledgements

The authors gratefully acknowledge the use of facilities of Sri Ramakrishna Engineering College, Coimbatore, India. This research was funded by University Grant Commission (UGC) of INDIA under Minor Research Project Scheme (Proposal No: 4280).

References

  1. 1.
    Lanjewar, U. M., & Shah, J. J. (2012). Air pollution monitoring and tracking system using mobile sensors and analysis of data using data mining. International Journal of Advanced Computer Research, 2, 19–23.Google Scholar
  2. 2.
    Tudose, D. S., Patrascu, T. A., Voinescu, A., Tataroiu, R., & Tapus, N. (2011). Mobile sensors in air pollution measurement. In 8th Workshop on positioning navigation and comm., pp. 166–170.Google Scholar
  3. 3.
    Rushikesh, R., & Sivappagari, C. M. R. (2015). Development of IoT based vehicular pollution monitoring system. In International conference on green computing and internet of things, pp.779–783.Google Scholar
  4. 4.
    ITU report on Internet of Things Executive Summary. www.itu.intlinternet of things.
  5. 5.
    Kadri, A., Yaacoub, E., Mushtaha, M., & Abu-Dayya, A. (2013). Wireless sensor network for real-time air pollution monitoring. In 1st International conference on communications, signal processing, and their applications (ICCSPA), IEEE.Google Scholar
  6. 6.
    The United States Environmental Protection Agency (US EPA). http://www.epa.gov/.
  7. 7.
    Fuertes, W., Carrera, D., Villacis, C., Toulkeridis, T., Galarraga, F., & Aules, E. T. H. (2015). Distributed system as internet of things for a new low-cost, air pollution wireless monitoring on real time. In 19th IEEE/ACM international symposium on distributed simulation and real timeapplications, pp. 58–67.Google Scholar
  8. 8.
    Al-Dabbous, A. N., Kumar, P., & Khan, A. R. (2016). Prediction of airborne nanoparticles at roadside using a feed-forward artificial neural network. Atmospheric Pollution Research, 1–9.Google Scholar
  9. 9.
    Yi, W. Y., Lo, K. M., Mak, T., Leung, K. S., Leung, Y., & Meng, M. L. (2015). A survey of wireless sensor network based air pollution monitoring systems. Sensors, 15, 31392–31427.  https://doi.org/10.3390/s151229859.CrossRefGoogle Scholar
  10. 10.
    Gulia, S., Shiva Nagendra, S. M., Khare, M., & Khanna, I. (2015). Urban air quality management—a review. Atmospheric Pollution Research, 6, 286–304.CrossRefGoogle Scholar
  11. 11.
    Auto Fuel Policy, Report of the Expert Committee on Auto Fuel Policy—Executive Summary, Ministry of Petroleum and Natural Gases, Government of India, 48 pages, 2002.Google Scholar
  12. 12.
    Molina, L. T., Kolb, C. E., de Foy, B., Lamb, B. K., Brune, W. H., Jimenez, J. L., et al. (2007). Air quality in North America’s most populous city- overview of the MCMA–2003 campaign. Atmospheric Chemistry and Physics, 7, 2447–2473.CrossRefGoogle Scholar
  13. 13.
    Badami, M. G. (2005). Transport and urban air pollutionin India. Environmental Management, 36, 195–204.CrossRefGoogle Scholar
  14. 14.
    Anjaneyulu, M. V. L. R., Harikrishna, M., & Chenchuobulu, S. (2006). Modeling ambient carbon monoxide pollutant due to road traffic. Proceedings of World Academy of Science Engineering and Technology, 17, 103–106.Google Scholar
  15. 15.
    Singh, A. K., Gupta, H. K., Gupta, K., Singh, P., Gupta, V. B., & Sharma, R. C. (2007). A comparative study of air pollution in Indian cities. Bulletin of Environmental Contamination and Toxicology, 78, 411–416.CrossRefGoogle Scholar
  16. 16.
    Wang, H., Fu, L., Zhou, Y., Du, X., & Ge, W. (2010). Trends in vehicular emissions in China’s mega cities from 1995 to 2005. Environmental Pollution, 158, 394–400.CrossRefGoogle Scholar
  17. 17.
    Figueiredo, M. L., Monteiro, A., Lopes, M., Ferreira, J., & Borrego, C. (2013). Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal. Environmental Monitoring and Assessment, 185, 5847–58602013.CrossRefGoogle Scholar
  18. 18.
    Gokhale, S., & Khare, M. (2007). A theoretical framework for the episodic–Urban Air Quality Management Plan (e-UAQMP). Atmospheric Environment, 41, 7887–7894.CrossRefGoogle Scholar
  19. 19.
    Faulkner, M., & Russell, P. (2010). A report to DEFRA and the devolved administrations. Review of Local Air Quality Management, 98 pages.Google Scholar
  20. 20.
    Copenhagen. (2015). Air Quality in Europe. EEA (European Environment Agency) Technical Report, 88 pages.Google Scholar
  21. 21.
    Country Synthesis Report on Urban Air Quality Management for Singapore. (2006). Asian Development Bank and the Clean Air Initiative for Asian Cities (CAI–Asia) Centre, Philippines, 22 pages.Google Scholar
  22. 22.
    Edesess, M. (2011). Roadside air pollution in Hong Kong: Why is It stillso Bad? School of Energy and Environment, City University of Hong Kong, 19 pages.Google Scholar
  23. 23.
    Future Policy for Motor Vehicle Emission Reduction (10th Report). (2011). Central Environmental Council, Government of Japan, 2 pages.Google Scholar
  24. 24.
    Baldasano, J. M., Valera, E., & Jimenez, P. (2003). Air quality data from large cities. Science of the Total Environment, 307, 141–165.CrossRefGoogle Scholar
  25. 25.
    Chan, C. K., & Yao, X. (2008). Air pollution in mega cities in China. Atmospheric Environment, 42, 1–42.CrossRefGoogle Scholar
  26. 26.
  27. 27.
    Kingsy Grace, R., Manimegalai, R., Geetha Devasena, M. S., Rajathi, S., Usha, K., & Raabiathul Baseria N. (2016). Air pollution analysis using enhanced k-means clustering algorithm for real time sensor data. In IEEE region 10 conference (TENCON)—proceedings of the international conference, pp. 1945–1949.Google Scholar
  28. 28.
    Weston, S. (2011). An overview of environmental monitoring and its significance in resource and environmental management. School of Resource and Environmental Studies, Dalhousie University.Google Scholar
  29. 29.
    Artiola, J. F., Pepper, I. L., & Brusseau, M. (2004). Environmental monitoring and characterization. Burlington, MA: Elsevier Academic Press.Google Scholar
  30. 30.
    Wiersma, G. B. (2004). Environmental monitoring. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
  31. 31.
  32. 32.
    Prasad, R. V., Baig, M. S., Mishra, R. K., Rajalakshmi, P., Desai, U. B., & Merchant, S. N. (2011). Real time wireless air pollution monitoring system. ICTACT Journal on Communication Technology, 2, 370–375.CrossRefGoogle Scholar
  33. 33.
    Zheng, K., Zhao, S., Yag, Z., Xiong, X., & Xiang, W. (2016). Design and implementation of LPWA-based air quality monitoring system. IEEE Access, 4, 3238–3245.CrossRefGoogle Scholar
  34. 34.
    Fuertes, W., Carrera, D., Villacis, C., Toulkeridis, T., Galarraga, F., & Aules, E. T. H. (2015). Distributed system as internet of things for a new low-cost, air pollution wireless monitoring on real time. In 19th IEEE/ACM international symposium on distributed simulation and real time applications, pp. 58–67.Google Scholar
  35. 35.
    Ibrahim, M., Elgamri, A., Babiker, S., & Mohamed, A. (2015). Internet of Things based smart environmental monitoring using Raspberry-Pi computer. IEEE 159–164.Google Scholar
  36. 36.
    Ficcola, G. B., Sommese, R., Tfano, I., Caonico, R., & Vntre, G. (2016). Polluino: An efficient cloud based management of Iot devices for air quality monitoring. In IEEE 2nd international forum on research and technologies for society and industry leveraging a better tomorrow (RTSI).Google Scholar
  37. 37.
    Lanjewar, U. M., & Shah, J. J. (2012). Air pollution monitoring and tracking system using mobile sensors and analysis of data using data mining. International Journal of Advanced Computer Research, 2, 19–23.Google Scholar
  38. 38.
    Balasubramaniyan, C., & Manivannan, D. (2016). IoT enabled air quality monitoring system (AQMS) using Raspberry Pi. Indian Journal of Science and Technology.  https://doi.org/10.17485/ijst/2016/v9i39/90414.CrossRefGoogle Scholar
  39. 39.
    Shum, L. V., Rajalakshmi, P., Afonja, A., McPhillips, G., Binions, R., Cheng, L., & Hailes, S. (2011) On the development of a sensor module for real-time pollution monitoring. In IEEE.Google Scholar
  40. 40.
    Bishop, G. A., Hottor-Raguindin, R., Stedman, D. H., McClintock, P., Theobald, Ed, Johnson, J. D., et al. (2015). On-road heavy-duty vehicle emissions monitoring system (OHMS). Environmental Science & Technology, 49, 1639–1645.CrossRefGoogle Scholar
  41. 41.
    Jamil, M. S., Jamil, M. A., Mazhar, A., Ikram, A., Ahmed, A., & Munawar, U. (2015). Smart environment monitoring system by employing wireless sensor networks on vehicles for pollution free smart cities. Procedia Engineering, 107, 480–484.CrossRefGoogle Scholar
  42. 42.
    Manna, S., Bhunia, S. S., & Mukherjee, N. (2014). Vehicular pollution monitoring using IoT. In IEEE international conference on recent advances and innovation in engineering.Google Scholar
  43. 43.
    Rushikesh, R., & Sivappagari, C. M. R. (2015). Development of IoT based vehicular pollution monitoring system. In International conference on green computing and internet of things, pp. 779–783.Google Scholar
  44. 44.
    Ma, Y., Richards, M., Ghanem, M., Guo, Y., & Hassard, J. (2008). Air pollution monitoring and mining based on sensor grid in London. Sensors, 8, 3601–3623.CrossRefGoogle Scholar
  45. 45.
    Kim Oanh, N. T., Martel, M., Pongkiatkul, P., & Berkowicz, R. (2008). Determination of fleet hourly emission and on-road vehicle emission factor using integrated monitoring and modeling approach. Atmospheric Research, 89, 223–232.CrossRefGoogle Scholar
  46. 46.
    Yu, R., Yang, Y., Yang, L., Han, G., & Move, O. A. (2016). RAQ–a random forest approach for predicting air quality in urban sensing systems. Sensors, 1–18.Google Scholar
  47. 47.
    Ghaemi, Z., Farnaghi, M., & Alimohammadi, A. (2015). Hadoop-based distributed system for online prediction of air pollution based on support vector machine. In International conference on sensors & models in remote sensing & photogrammetry, pp. 215–219.Google Scholar
  48. 48.
    Ojeda-Magaña, B., Cortina-Januchs, M. G., Barrón-Adame, J. M., Quintanilla-Domínguez, J., Hernandez, W., Vega-Corona, A., Ruelas, R., & Andina, D. (2010). Air pollution analysis with a PFCM clustering algorithm applied in a real database of Salamanca (Mexico). In IEEE, pp. 1297–1302.Google Scholar
  49. 49.
    Dogruparmak, S. C., Keskin, G. A., Yaman, S., & Alkan, A. (2014). Using principal component analysis and fuzzy C-means clustering for the assessment of air quality monitoring. Atmospheric Pollution Research, 5, 656–663.CrossRefGoogle Scholar
  50. 50.
    Salcedo, R. L. R., Alvim Ferraz, M. C. M., Alves, C. A., & Martins, F. G. (1999). Time-series analysis of air pollution data. Atmospheric Environment, 33(15), 2361–2372.CrossRefGoogle Scholar
  51. 51.
    Warsono, S., Bartolucci, A. A., & Bae, S. (2001). Mathematical modeling of environmental data. Mathematical and Computer Modeling, 33(6–7), 793–800.zbMATHGoogle Scholar
  52. 52.
    Wang, J. M., Jeong, C. H., Zimmerman, N., Healy, R. M., Wang, D. K., Ke, F., et al. (2015). Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters. Atmospheric Measurement Techniques, 8, 3263–3275.CrossRefGoogle Scholar
  53. 53.
    Asghari Esfandani, M., & Nematzadeh, H. (2016). Predicting air pollution in Tehran: Genetic algorithm and back propagation neural network. Journal of AI and Data Mining, 4, 49–54.Google Scholar
  54. 54.
    Soltaniye, M., Moslehi, P., & Yari, M. (2012). The concentration of suspended particles in the air in Tehran predicted by neural network models and compare multiple regression model. Tehran: Sanati Sharif University.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringSri Ramakrishna Engineering CollegeCoimbatore-22India

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