| Summary: | Urban environments are filled with buildings, trees, and other forms of infrastructure. This results in Radio Frequency (RF) signals encountering many obstacles in its path when transmitted from a transmitter to a receiver. It is, therefore, difficult to try to predict and model radio frequency signal propagation in an urban environment.
With the advancement of Artificial Intelligence (AI) in recent years and the development of more powerful models, researchers have begun using AI to model RF signal propagation in an urban environment. To develop an accurate AI model, it needs to be trained with Ground Truths. Data collection of Ground Truths requires setting up of RF equipment and moving them to different locations to gather many and diverse RF measurements. As the RF equipment are bulky and heavy, the process of data collection is physically demanding. This project proposes a solution by developing a robot to transport the RF equipment around during data collection. A Graphical User Interface was also developed to provide users with the means to control the movements of the robot.
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