Public transportation plays a crucial role in our lives, and the road network is a vital component in the implementation of smart cities. Recent advancements in AI have enabled the development of advanced monitoring systems capable of detecting anomalies in road surfaces and road signs, which, if unaddressed, can lead to serious road accidents. This paper presents an innovative approach to enhance road safety through the detection and classification of traffic signs and road surface damage using advanced deep learning techniques. This integrated approach supports proactive maintenance strategies, improving road safety and resource allocation for the Molise region and the city of Campobasso. The resulting system, developed as part of the Casa delle Tecnologie Emergenti (House of Emergent Technologies) Molise (Molise CTE) research project funded by the Italian Minister of Economic Growth (MIMIT), leverages cutting-edge technologies such as Cloud Computing and High Performance Computing with GPU utilization. It serves as a valuable tool for municipalities, enabling quick detection of anomalies and the prompt organization of maintenance operations

翻译：公共交通在我们的生活中扮演着至关重要的角色，而道路网络是智慧城市建设中的关键组成部分。人工智能的最新进展使得开发先进的监控系统成为可能，这些系统能够检测路面和道路标志的异常，若未及时处理，可能导致严重的交通事故。本文提出了一种创新方法，通过使用先进的深度学习技术对交通标志和路面损伤进行检测与分类，从而提升道路安全性。这一综合方法支持主动维护策略，有助于改善莫利塞地区和坎波巴索市的道路安全与资源分配。所开发的系统作为由意大利经济发展部（MIMIT）资助的莫利塞新兴技术中心研究项目的一部分，利用了云计算和基于GPU的高性能计算等前沿技术。该系统为市政部门提供了一个宝贵的工具，能够快速检测异常并及时组织维护作业。