  Collapsing of structural buildings has been sighted commonly and the presence
of potential faults has proved to be damaging to the buildings, resulting in
accidents. It is essential to continuously monitor any building for faults
where human access is restricted. With UAVs (Unmanned Aerial Vehicles) emerging
in the field of computer vision, monitoring any building and detecting such
faults is seen as a possibility. This paper puts forth a novel approach where
an automated UAV traverses around the target building, detects any potential
faults in the building, and localizes the faults. With the dimensions of the
building provided, a path around the building is generated. The images captured
by the onboard camera of the UAV are passed through a neural network system to
confirm the presence of faults. Once a fault is detected, the UAV maneuvers
itself to the corresponding position where the crack is detected. The
simulation is done with ROS(Robot Operating System) using the AirSim
environment which initializes ROS Wrappers and provides an integrated interface
of ROS and AirSim to work with, The UAV is simulated in the same.
