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.

翻译：过去几年来,对没有驾驶的汽车的兴趣明显增加;自然,对准确和可靠的物体定位和绘图系统的需求比以往任何时候要高。这样一个系统必须在其近距离内向用户提供准确的信息。以前的许多研究工作已经探索了在智能运输系统环境下实施这种高度动态的绘图系统的各种可能办法,但很少人讨论过它是否适用于其他5G纵向和服务。在这一篇文章中,我们首先描述动态地图的概念。然后我们介绍其结构和不同组成部分,在创建时空动态地图系统时采用的方法。之后,我们提出不同的设想,即这一相当新的现代技术可以用于其他5G服务,特别是UAV地球屏障服务,最后,我们测试物体探测模块并讨论结果。