High-resolution monitoring of atmospheric pollutants using a system of low-cost sensors

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 7, 2014, Pages 3823-3832

  Rajasegarar, Sutharshan ^a   Havens, Timothy C ^b   Karunasekera, Shanika ^a   Leckie, Christopher ^a   Bezdek, James C ^a   Jamriska, Milan ^c   Gunatilaka, Ajith ^c   Skvortsov, Alex ^c   Palaniswami, Marimuthu ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b MICHIGAN TECHNOLOGICAL UNIVERSITY   (United States)

^c DEFENCE SCIENCE AND TECHNOLOGY ORGANISATION   (Australia)

Author keywords

Air pollution; Bayesian maximum entropy; geospatial analysis; kriging; particulate matter; spatiotemporal estimation; Wireless sensor networks

Indexed keywords

AIR POLLUTION; COST ESTIMATING; ESTIMATION; MAXIMUM ENTROPY METHODS; SENSOR NODES; SENSORS; WIRELESS SENSOR NETWORKS;

ATMOSPHERIC POLLUTANTS; BAYESIAN MAXIMUM ENTROPIES; CONTRIBUTING FACTOR; GEO-SPATIAL ANALYSIS; HIGH-RESOLUTION MONITORING; KRIGING; PARTICULATE MATTER; VICTORIA , AUSTRALIA;

COST BENEFIT ANALYSIS;

ACCURACY ASSESSMENT; ATMOSPHERIC POLLUTION; CONCENTRATION (COMPOSITION); COST-BENEFIT ANALYSIS; ESTIMATION METHOD; IMAGE RESOLUTION; PRECISION; SENSOR;

AUSTRALIA; MELBOURNE; VICTORIA [AUSTRALIA];

EID: 84896395846     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2276431     Document Type: Article

References (58)

1. Environmental Protection and Heritage council, "Asthma research: Abackground paper," Co-operative Studies on Priority Air Quality andHealth Related Issues, 2002.
2. Online]. Available: http://www.scew.gov.au/archive/air/pubs/aq-rsch- asthma-background-paper-200212.pdf
3. J. G. Watson, "Visibility: Science and regulation," J. Air Waste Manage.Assoc., vol. 52, no. 6, pp. 628-713, Jun. 2002.
4. J. C. Chow, J.Watson, J. Mauderly, D. Costa, R.Wyzga, S. Vedal, G. Hidy,S. Altshuler, D. Marrack, J. Heuss, G. Wolff, C. Pope, and D. Dockery,"Health effects of fine particulate air pollution: Lines that connect," J. AirWaste Manage. Assoc., vol. 56, no. 10, pp. 1368-1380, Oct. 2006. (Pubitemid 46063428)
5. Air Quality Criteria for Particulate Matter, US Environ. ProtectionAgency (US EPA), Washington, DC, USA, 1996.
6. S. H. Ling and S. F. van Eeden, "Particulate matter air pollution exposure:Role in the development and exacerbation of chronic obstructivepulmonary disease," Int. J. Chron. Obstruct. Pulmon. Dis., vol. 4, pp. 233-243, 2009.
7. A. Kimbrell, In-Car Air Pollution. The Hidden Threat to AutomobileDrivers, Int. Center Technol. Assessment, Washington, DC,USA, Rep. 4.
8. Online]. Available: http://www.andrewkimbrell.org/doc/In- carpollutionreport.pdf
9. D. Massey, A. Kulsrestha, and A. Taneja, "A study on indoor outdoorconcentration of particulate matter in rural residential houses in India," inProc. 2nd Int. Conf. Environ. Comput. Sci., 2009, pp. 218-223.
10. T. Slini, K. Karatzas, and N. Moussiopoulos, "Statistical analysis of environmentaldata as the basis of forecasting: An air quality application,"Sci. Total Environ., vol. 288, no. 3, pp. 227-237, Apr. 2002. (Pubitemid 34230402)
11. L. Diaz-Robles, J. C. Ortega, J. S. Fu, G. D. Reed, J. C. Chow,J. G.Watson, and J. A.Moncada-Herrera, "A hybrid ARIMA and artificialneural networks model to forecast particulate matter in urban areas: Thecase of Temuco, Chile," Atmos. Environ., vol. 42, no. 35, pp. 8331-8340,Nov. 2008.
12. T. Slini, A. Kaprara, K. Karatzas, and N. Moussiopoulos, " PM10 forecastingfor Thessaloniki, Greece," Environ. Modell. Softw., vol. 21, no. 4,pp. 559-565, Apr. 2006.
13. E. Stadlober, S. Hormann, and B. Pfeiler, "Quality and performance of aPM10 daily forecasting model," Atmos. Environ., vol. 42, no. 6, pp. 1098-1109, Feb. 2008.
14. F. C. Tsai, K. R. Smith, N. Vichit-Vadakan, B. D. Ostro, L. G. Chestnut,and N. Kungskulniti, "Indoor/outdoor PM10 and PM2.5 in Bankok, Thailand,"J. Exposure Anal. Environ. Epidemiol., vol. 10, no. 1, pp. 15-26,Jan./Feb. 2000. (Pubitemid 30112410)
15. L. Guoxing, S. Jing, J. S. Rohan, P. X. Chuan, Z. Maigeng, W. Xuying,C. Yue, S. Ross, and S. G. Reginald, "Temperature modifies the effectsof particulate matter on non-accidental mortality: A comparative study ofBeijing, China and Brisbane, Australia," Public Health Res., vol. 2, no. 2,pp. 21-27, 2012.
16. D. W. Dockery, C. A. Pope, X. Xu, J. D. Spengler, J. H. Ware,M. E. Fay, J. Benjamin, G. Ferris, and F. E. Speizer, "An associationbetween air pollution and mortality in six cities," New Engl. J. Med.,vol. 329, no. 24, pp. 1753-1759, Dec. 1993. (Pubitemid 23355547)
17. S. Rajasegarar, C. Leckie, and M. Palaniswami, "Detecting data anomaliesin sensor networks," in Security in Ad-hoc and Sensor Networks,R. Beyah, J. McNair, and C. Corbett, Eds. Singapore: World Scientific,Jul. 2009, pp. 231-260.
18. J. C. Bezdek, S. Rajasegarar, M. Moshtaghi, C. Leckie, M. Palaniswami,and T. Havens, "Anomaly detection in environmental monitoring networks,"IEEE Comput. Intell. Mag., vol. 6, no. 2, pp. 52-58, May 2011.
19. S. Rajasegarar, C. Leckie, and M. Palaniswami, "Anomaly detectionin wireless sensor networks," IEEE Wireless Commun., vol. 15, no. 4,pp. 34-40, Aug. 2008.
20. S. Rajasegarar, C. Leckie, M. Palaniswami, and J. C. Bezdek, "Distributedanomaly detection in wireless sensor networks," in Proc. ICCS, 2006,pp. 1-5.
21. S. Rajasegarar, J. C. Bezdek, C. Leckie, and M. Palaniswami, "Ellipticalanomalies in wireless sensor networks," ACM Trans. Sens. Netw., vol. 6,no. 1, p. 28, Dec. 2009.
22. M. Takruri, S. Rajasegarar, S. Challa, C. Leckie, and M. Palaniswami,"Spatio-temporal modelling based drift aware wireless sensor networks,"IET Wireless Sens. Syst., vol. 1, no. 2, pp. 110-122, Jun. 2011.
23. S. Rajasegarar, C. Leckie, J. C. Bezdek, and M. Palaniswami, "Centeredhyperspherical and hyperellipsoidal one-class support vector machinesfor anomaly detection in sensor networks," IEEE Trans. Inf. ForensicsSecurity, vol. 5, no. 3, pp. 518-533, Sep. 2010.
24. A. Shilton, S. Rajasegarar, and M. Palaniswami, "Combined multiclassclassification and anomaly detection for large-scale wireless sensor networks,"in Proc. IEEE 8th Int. Conf. Intell. Sens., Sens. Netw. Inf. Process.,Melbourne, VIC, Austrlia, Apr. 2013, pp. 491-496.
25. M. Moshtaghi, S. Rajasegarar, C. Leckie, and S. Karunasekera, "An efficienthyperellipsoidal clustering algorithm for resource-constrained environments,"Pattern Recognit., vol. 44, no. 9, pp. 2197-2209, Sep. 2011.
26. M. Moshtaghi, T. Havens, L. Park, J. C. Bezdek, S. Rajasegarar,C. Leckie, M. Palaniswami, and J. Keller, "Clustering ellipses for anomalydetection," Pattern Recognit., vol. 44, no. 1, pp. 55-69, Jan. 2011.
27. S. Rajasegarar, A. Shilton, C. Leckie, R. Kotagiri, and M. Palaniswami,"Distributed training of multiclass conic-segmentation support vectormachines on communication constrained networks," in Proc. 6th Int.Conf. Intell. Sens., Sens. Netw. Inf. Process., Brisbane, QLD, Austrlia,Dec. 2010, pp. 211-216.
28. M. Moshtaghi, J. C. Bezdek, T. C. Havens, C. Leckie, S. Karunasekera,S. Rajasegarar, and M. Palaniswami, "Streaming analysis in wirelesssensor networks," Wireless Commun. Mobile Comput., 2012.
29. Online].Available: http://onlinelibrary.wiley.com/doi/10.1002/wcm.2248/ pdf
30. C. Oreilly, A. Gluhak, M. A. Imran, and S. Rajasegarar, "Online anomalyrate parameter tracking for anomaly detection in wireless sensor networks,"in Proc. IEEE Conf. Sens., Mesh Ad Hoc Commun. Netw., Seoul,Korea, Jun. 2012, pp. 191-199.
31. J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, "Internet of things(IoT): A vision, architectural elements, and future directions," FutureGener. Comput. Syst., vol. 29, no. 7, pp. 1645-1660, Sep. 2013.
32. Internet of Things, 2013.
33. Online]. Available: http://issnip.unimelb.edu.au/research-program/ Internet-of-Things
34. Environment Protection Authority Victoria Sensor Locations, Australia,2012.
35. Online]. Available: http://www.epa.vic.gov.au/air/airmap/default. aspmapView=melb&id=10213&tab=Particles
36. M. L. Serre and G. Christakos, "Modern geostatistics: ComputationalBME analysis in the light of uncertain physical knowledge - The equusbeds study," Stochastic Environ. Res. Risk Assessment, vol. 13, no. 1/2,pp. 1-26, Apr. 1999. (Pubitemid 129514557)
37. C. Mendis, A. Skvortsov, A. Gunatilaka, and S. Karunasekera, "Performanceof wireless chemical sensor network with dynamic collaboration,"IEEE Sensors J., vol. 12, no. 8, pp. 2630-2637, Aug. 2012.
38. S. Karunasekera, C. Mendis, A. Skvortsov, and A. Gunatilaka, "A decentralizeddynamic sensor activation protocol for chemical sensor networks,"in Proc. 9th IEEE NCA, Jul. 15-17, 2010, pp. 218-223.
39. H.-h. K. Burke, "Detection of regional air pollution episodes utilizingsatellite digital data in the visual range," IEEE Trans. Geosci. RemoteSens., vol. GE-20, no. 2, pp. 154-158, Apr. 1982.
40. F. Cuccoli, L. Facheris, S. Tanelli, and D. Giuli, "Infrared tomographicsystem for monitoring the two-dimensional distribution of atmosphericpollution over limited areas," IEEE Trans. Geosci. Remote Sens., vol. 38,no. 1, pp. 155-168, Jan. 2000. (Pubitemid 30556238)
41. A. Srivastava, N. Oza, and J. Stroeve, "Virtual sensors: Using data miningtechniques to efficiently estimate remote sensing spectra," IEEE Trans.Geosci. Remote Sens., vol. 43, no. 3, pp. 590-600, Mar. 2005. (Pubitemid 40320280)
42. H.-L. Yu, C.-H. Wang, M.-C. Liu, and Y.-M. Kuo, "Estimation of fineparticulate matter in Taipei using land use regression and Bayesian maximumentropy methods," Int. J. Environ. Res. Public Health, vol. 8, no. 6,pp. 2153-2169, Jun. 2011.
43. V. Epitropou, L. Johansson, K. D. Karatzas1, A. Bassoukos,A. Karppinen, J. Kukkonen, and M. Haakana, "Fusion of environmentalinformation for the delivery of orchestrated services for the atmosphericenvironment in the pescado project," in Proc. Int. Congr. Environ. Modell.Softw. Manag. Resources Limited Planet, R. Seppelt, A. A. Voinovr,S. Lange, and D. Bankamp, Eds., 2012.
44. Online]. Available: http://www.iemss.org/society/index.php/iemss-2012- proceedings
45. I. Clarke, Practical Geostastics. Columbus, OH, USA: Ecosse NorthAmer Llc, 1979.
46. Online]. Available: http://www.kriging.com/PG1979/
47. H. Wackernagle, Multivariate Geostatistics: An Introduction WithApplications. Berlin, Germany: Springer-Verlag, 1998.
48. G. Christakos, M. L. Serre, and J. Kovitz, "BME representation of particulatematter distributions in the state of California on the basis of uncertainmeasurements," J. Geophys. Res., vol. 106, no. D9, pp. 9717-9731,May 2001.
49. B. Ostro, J. M. Sanchez, C. Aranda, and G. S. Eskeland, "Air pollution andmortality," in Policy Research Working Paper 1453. Washington, DC,USA: The World Bank, 1995, pp. 1-40.
50. G. K. Batchelor, "Diffusion in a field of homogeneous turbulenceii. Therelative motion of particles," Math. Proc. Cambridge Philosop. Soc.,vol. 48, no. 2, pp. 345-362, Apr. 1952.
51. L. F. Richardson, "Atmospheric diffusion shown on a distance-neighbourgraph," Proc. R. Soc. Lond. A, vol. 110, no. 756, pp. 709-737, Apr. 1926.
52. M. Jamriska, T. DuBois, and A. Skvortsov, "Statistical characterisationof bio-aerosol background in an urban environment," Atmos. Environ.,vol. 54, pp. 439-448, Jul. 2012.
53. E. Yee and A. Skvortsov, "Scalar fluctuations from a point source in aturbulent boundary layer," Phys. Rev. E, vol. 84, no. 3, pp. 036306-1-036306-7, Sep. 2011.
54. A. Gunatilaka and R. Gailis, "High fidelity simulation of hazardousplume concentration time series based on models of turbulent dispersion,"in Proc. 15th Int. Conf. Inf. FUSION, Singapore, Jul. 9-12, 2012,pp. 1838-1845.
55. G. Boffetta, A. Celani, A. Crisanti, and A. Vulpiani, "Pair dispersionin synthetic fully developed turbulence," Phys. Rev. E, vol. 60, no. 6,pp. 6734-6741, Dec. 1999. (Pubitemid 129651494)
56. G. Christakos, Modern Spatiotemporal Geostatistics. New York, NY,USA: Dover, 2012.
57. BME Library, 2012.
58. Online]. Available: http://www.unc.edu/depts/case/BMELIB/