Building Smart City Drone for Graffiti Detection and Clean-up

Shuqin Wang, Jerry Zeyu Gao, Weiyi Li, Yanning Li, Kaixuan Wang, Shengqiang Lu

Abstract: Graffiti on buildings and bridges are oftentimes an eyesore. Those on road symbol signs can even pose safety risks to motorists. Not only is graffiti cleaning costly, it also disrupts normal traffic. Graffiti is a widespread problem in many cities in the U.S. This paper proposes a machine learning approach to unmanned aerial vehicle (UAV) graffiti detection and removal. Our solution builds on the smart city framework. The proposed solution is expected to lower graffiti cleaning cost and minimize impact on city traffic.