A Machine Learning Approach for Identifying Mosquito Breeding Sites via Drone Images

Dengue is one of the deadly and fast spreading diseases in Sri Lanka. The female Aedes mosquito is the dengue vector and these mosquitoes breed in clear and non-flowing water. The Public Health Inspectors (PHIs) are tasked with detecting and eliminating such water collection areas. However, they face the problem of detecting potential breeding sites in hard-to-reach areas. With the technological development, the drones come as one of the most cost effective unmanned vehicles to access the places that a man cannot access. This paper presents a novel approach for identifying mosquito breeding areas via drone images through the distinct coloration of those areas by applying the Histogram of Oriented Gradients (HOG) algorithm. Using the HOG algorithm, we detect potential water retention areas using drone images.