Choice of unmanned aerial vehicles for identification of mosquito breeding sites

Abstract

The disordered urban growth that may favour the emergence of the Aedes aegypti mosquito in cities is a problem of increasing magnitude in middle- and high-income countries in the tropical part of the world. Currently, the World Health Organization (WHO) considers the control and elimination of Ae. aegypti a world-wide high priority as it is the main vector of many rapidly spreading viral diseases, dengue in particular. A major difficulty in controlling the proliferation of this vector is associated with identification of the breeding sites. The use of Unmanned Aerial Vehicles (UAVs) can be an efficient alternative to manual search because of high mobility and the ability to overcome physical obstacles, particularly in urban areas where it can offer close-up images of potential breeding sites that are difficult to reach. The objective of this study was to find a way to select the most suitable UAV for the identification of Ae. aegypti habitats by providing images of potential mosquito breeding sites. This can be accomplished by a Multiple-Criteria Decision Method (MCDM) based on an Analytical Hierarchy Process (AHP) for the evaluation of weights of the criteria used for characterizing UAVs. The alternatives were analyzed and ranked using the Fuzzy Set Theory (FST) merged with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The methodology is explained and discussed with respect to identification and selection of the most appropriate UAV for aerial mapping of Aedes breeding sites.

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Published
2020-06-17
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Original Articles
Keywords:
Aedes Aegypti, Unmanned Aerial Vehicle, MCDM, Fuzzy Set Theory, Fuzzy TOPSIS, Brazil
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How to Cite
Aragão, F. V., Cavicchioli Zola, F., Nogueira Marinho, L. H., de Genaro Chiroli, D. M., Braghini Junior, A., & Colmenero, J. C. (2020). Choice of unmanned aerial vehicles for identification of mosquito breeding sites. Geospatial Health, 15(1). https://doi.org/10.4081/gh.2020.810