  The past few years have witnessed a remarkable rise in interest in
driver-less cars; and naturally, in parallel, the demand for an accurate and
reliable object localization and mapping system is higher than ever. Such a
system would have to provide its subscribers with precise information within
close range. There have been many previous research works that have explored
the different possible approaches to implement such a highly dynamic mapping
system in an intelligent transportation system setting, but few have discussed
its applicability toward enabling other 5G verticals and services. In this
article we start by describing the concept of dynamic maps. We then introduce
the approach we took when creating a spatio-temporal dynamic maps system by
presenting its architecture and different components. After that, we propose
different scenarios where this fairly new and modern technology can be adapted
to serve other 5G services, in particular, that of UAV geofencing, and finally,
we test the object detection module and discuss the results.
