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PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks

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Smart Objects and Technologies for Social Good (GOODTECHS 2017)

Abstract

Discretization is one of the most efficient mathematical approaches to simplify (optimize) a system by transforming a continuous domain into its discrete counterpart. In this paper, by adopting space discretization, we have modified the previously proposed solution called PdUC (Pollution-driven UAV Control), which is a protocol designed to guide UAVs that monitor air quality in a specific area by focusing on the most polluted areas. The improvement proposed in this paper, called PdUC-D, consists of an optimization whereby UAVs only move between the central tile positions of a discretized space, avoiding to monitor locations separated by small distances, and whose actual differences in terms of air quality are barely noticeable. Experimental results show that PdUC-D drastically reduces convergence time compared to the original PdUC proposal without loss of accuracy.

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References

  1. Seaton, A., Godden, D., MacNee, W., Donaldson, K.: Particulate air pollution and acute health effects. Lancet 345(8943), 176–178 (1995)

    Article  Google Scholar 

  2. McFrederick, Q.S., Kathilankal, J.C., Fuentes, J.D.: Air pollution modifies floral scent trails. Atmos. Environ. 42(10), 2336–2348 (2008)

    Article  Google Scholar 

  3. Alvear, O., Zamora, W., Calafate, C., Cano, J.-C., Manzoni, P.: An architecture offering mobile pollution sensing with high spatial resolution. J. Sens. 2016 (2016)

    Google Scholar 

  4. Adam-poupart, A., Brand, A., Fournier, M., Jerrett, M., Smargiassi, A.: Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy’LUR approaches. Environ. Health Perspect. 970(January 2013), 1–19 (2014)

    Google Scholar 

  5. Pujadas, M., Plaza, J., Teres, J., Artıñano, B., Millan, M.: Passive remote sensing of nitrogen dioxide as a tool for tracking air pollution in urban areas: the madrid urban plume, a case of study. Atmos. Environ. 34(19), 3041–3056 (2000)

    Article  Google Scholar 

  6. Eisenman, S.B., Miluzzo, E., Lane, N.D., Peterson, R.A., Ahn, G.-S., Campbell, A.T.: Bikenet: a mobile sensing system for cyclist experience mapping. ACM Trans. Sens. Netw. (TOSN) 6(1), 6 (2009)

    Google Scholar 

  7. André, M.: The artemis European driving cycles for measuring car pollutant emissions. Sci. Total Environ. 334, 73–84 (2004)

    Article  Google Scholar 

  8. Alvear, O., Calafate, C.T., Hernández-Orallo, E., Cano, J.-C., Manzoni, P.: Mobile pollution data sensing using UAVs. In: The 13th International Conference on Advances in Mobile Computing and Multimedia (2015)

    Google Scholar 

  9. Alvear, O.A., Zema, N.R., Natalizio, E., Calafate, C.T.: A chemotactic pollution-homing UAV guidance system. In: 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 2115–2120. IEEE (2017)

    Google Scholar 

  10. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2016)

    Google Scholar 

  11. Stein, M.L.: Statistical Interpolation of Spatial Data: Some Theory for Kriging. Springer, New York (1999). https://doi.org/10.1007/978-1-4612-1494-6

    Book  MATH  Google Scholar 

  12. Alvear, O., Zema, N.R., Natalizio, E., Calafate, C.T.: Using UAV-based systems to monitor air pollution in areas with poor accessibility. J. Adv. Transp. 2017 (2017)

    Google Scholar 

  13. United States Environmental Protection Agency. Air Quality Index Available (2015) http://cfpub.epa.gov/airnow/index.cfm?action=aqibasics.aqi

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Acknowledgment

This work has been partially carried out in the framework of the DIVINA Challenge Team, which is funded under the Labex MS2T program. Labex MS2T is supported by the French Government, through the program “Investments for the future” managed by the National Agency for Research (Reference: ANR-11-IDEX-0004-02). This work was also supported by the “Programa Estatal de Investigación, Desarrollo e Innovación Orientada a Retos de la Sociedad, Proyecto I+D+I TEC2014-52690-R”, the “Programa de becas SENESCYT de la República del Ecuador”, and the Research Direction of the University of Cuenca.

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Correspondence to Oscar Alvear .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Alvear, O. et al. (2018). PdUC-D: A Discretized UAV Guidance System for Air Pollution Monitoring Tasks. In: Guidi, B., Ricci, L., Calafate, C., Gaggi, O., Marquez-Barja, J. (eds) Smart Objects and Technologies for Social Good. GOODTECHS 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 233. Springer, Cham. https://doi.org/10.1007/978-3-319-76111-4_38

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  • DOI: https://doi.org/10.1007/978-3-319-76111-4_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-76110-7

  • Online ISBN: 978-3-319-76111-4

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