Abstract

Unmanned aerial vehicles (UAV), commonly called drones, are a growing field in computer technology with applications ranging from military to delivery systems. One of the foremost obstructions to the allowance of UAV journeys over populated areas or civilian airspace is the lack of sophisticated automated systems that detect UAV landing sites. In this paper, we propose a landing area detection system, based primarily on machine learning that focuses on determining drop-off points. Determining a prime drop site within a property is an important aspect of automated delivery systems. Our proposed method uses features such as the colour and texture of pixels to describe the characteristics of an area. These characteristics are employed by machine learning algorithms such as Support Vector Machine, to predict appropriate drop-off locations.

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