Autonomous Detection of Mosquito-Breeding Habitats Using an Unmanned Aerial Vehicle
| Autor: | Viviane Alves, Gabriel Araújo, Thiago de M. Prego, Henrique Alves, Amaro A. de Lima, Tayana M. Dias, Roberto Pontes, Lucas Pinheiro |
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| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
biology Computer science business.industry fungi Feature extraction 02 engineering and technology Aedes aegypti medicine.disease_cause biology.organism_classification Edge detection Random forest 03 medical and health sciences 020901 industrial engineering & automation 0302 clinical medicine Test set medicine Global Positioning System 030212 general & internal medicine Chikungunya Geographic coordinate system business Cartography |
| Zdroj: | 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE). |
| Popis: | Every year, thousands of people die from diseases such as dengue fever, chikungunya, and zika. This public health problem is more evident in developing countries. All these illnesses have the same source in common: a mosquito scientifically known as Aedes Aegypti. In cities, the majority of mosquito-breeding habitats are man-made: bottles, tires, barrels, pots or any stagnant water. This paper proposes an innovative system to aid in determining mosquito-breeding habitats location by employing computer vision tools on aerial images. Tires and regions with stagnant water were selected as objects of study. For this, a dataset was created containing video sequences and telemetry data from an unmanned aerial vehicle (UAV) and the respective manual annotation in different scenarios. The features extracted from the videos (through HSV color space, histograms, and edge detection) were used to train a random forest classifier, resulting in an accuracy higher than 99% in the test set. The system is also capable of automatically determining the GPS coordinates of the possible mosquito breeding location with similar precision to commercial GPS equipment. |
| Databáze: | OpenAIRE |
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