A Comprehensive Review of Wireless Sensor Networks Based Air Pollution Monitoring Systems
- 151 Downloads
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.
KeywordsAir pollution Sensor network Air quality
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).
- 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.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.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.ITU report on Internet of Things Executive Summary. www.itu.intlinternet of things.
- 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.The United States Environmental Protection Agency (US EPA). http://www.epa.gov/.
- 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.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
- 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
- 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
- 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.Copenhagen. (2015). Air Quality in Europe. EEA (European Environment Agency) Technical Report, 88 pages.Google Scholar
- 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.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.Future Policy for Motor Vehicle Emission Reduction (10th Report). (2011). Central Environmental Council, Government of Japan, 2 pages.Google Scholar
- 26.Web Reference. https://airnow.gov/index.cfm?action=aqibasics.aqi.
- 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.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.Artiola, J. F., Pepper, I. L., & Brusseau, M. (2004). Environmental monitoring and characterization. Burlington, MA: Elsevier Academic Press.Google Scholar
- 31.Web Reference. https://www.link-labs.com/blog/iot-environmental-monitoring.
- 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.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.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.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
- 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
- 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.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
- 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.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.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
- 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.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