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A Discretized Approach to Air Pollution Monitoring Using UAV-based Sensing

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Abstract

Recently, Unmanned Aerial Vehicles (UAVs) have become a cheap alternative to sense pollution values in a certain area due to their flexibility and ability to carry small sensing units. In a previous work, we proposed a solution, called Pollution-driven UAV Control (PdUC), to allow UAVs to autonomously trace pollutant sources, and monitor air quality in the surrounding area. However, despite operational, we found that the proposed solution consumed excessive time, especially when considering the battery lifetime of current multi-rotor UAVs. In this paper, we have improved our previously proposed solution by adopting a space discretization technique. Discretization is one of the most efficient mathematical approaches to optimize a system by transforming a continuous domain into its discrete counterpart. The improvement proposed in this paper, called PdUC-Discretized (PdUC-D), consists of an optimization whereby UAVs only move between the central tile positions of a discretized space, avoiding monitoring locations separated by small distances, and whose actual differences in terms of air quality are barely noticeable. We also analyze the impact of varying the tile size on the overall process, showing that smaller tile sizes offer high accuracy at the cost of an increased flight time. Taking into account the obtained results, we consider that a tile size of 100 × 100 meters offers an adequate trade-off between flight time and monitoring accuracy. Experimental results show that PdUC-D drastically reduces the convergence time compared to the original PdUC proposal without loss of accuracy, and it also increases the performance gap with standard mobility patterns such as Spiral and Billiard.

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Acknowledgements

This work was partially supported by the “Programa Estatal de Investigación, Desarrollo e Innovación Orientada a Retos de la Sociedad, Proyecto I+D+I TEC2014-52690-R”, 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), the “Programa de becas SENESCYT de la República del Ecuador”, and the Research Direction of the University of Cuenca.

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Authors and Affiliations

  1. Department of Electrical Engineering, Electronics and Telecommunications, Universidad de Cuenca, Av. 12 de Abril, S/N, Cuenca, Ecuador

    Oscar Alvear

  2. Department of Computer Engineering, Universitat Politècnica de València, Camino de Vera, S/N, 46022, Valencia, Spain

    Oscar Alvear, Carlos T. Calafate, Enrique Hernández-Orallo, Juan-Carlos Cano & Pietro Manzoni

  3. IFSTTAR, COSYS, Univ Lille Nord de France, F-59650, Villeneuve d’Ascq, France

    Nicola Roberto Zema

  4. CNRS, Laboratoire Heudiasyc, Sorbonne Universités, Université de Technologie de Compiègne, 57 Avenue de Landshut, CS 60319, 60203, Compiegne Cedex, France

    Enrico Natalizio

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  1. Oscar Alvear
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  2. Carlos T. Calafate
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  3. Nicola Roberto Zema
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  5. Enrique Hernández-Orallo
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  6. Juan-Carlos Cano
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  7. Pietro Manzoni
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Correspondence to Oscar Alvear.

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Alvear, O., Calafate, C.T., Zema, N.R. et al. A Discretized Approach to Air Pollution Monitoring Using UAV-based Sensing. Mobile Netw Appl 23, 1693–1702 (2018). https://doi.org/10.1007/s11036-018-1065-4

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