Street lighting characterizes many smart city initiatives around the world. In fact, significant savings can be achieved by not only replacing traditional luminaires with low-power LEDs, but also providing streetlights with smart light controllers and network connectivity, allowing the introduction of a sensible light intensity management and reduction of maintenance costs. Moreover, if designed with a far-looking view, smart lighting infrastructure could also support city-wide Internet of Things services, becoming key enablers of the smart city revolution, also in the 5G perspective. In this paper, we provide a thorough discussion on network architectures and communication technologies that could be adopted for smart public lighting applications, showing their benefits and downsides. Starting with significant activity on research, implementation and in-field testing, we also outline the steps required for the deployment of a smart public lighting infrastructure, each discussed in accordance with the network topology considered. Finally, we introduce some additional services that a smart public lighting infrastructure could support and discuss the benefits that would arise from integration with the upcoming 5G cellular network.

This paper addresses the growing importance of efficient street lighting management, driven by rising electricity costs and the need for municipalities to implement cost-effective solutions. Central to this study is the UNI 11248 Italian regulation, which extends the European EN 13201-1 standard introduced in 2016. These standards provide guidelines for designing, installing, operating, and maintaining lighting systems in pedestrian and vehicular traffic areas. Specifically, the UNI 11248 standard introduces the possibility to dynamically adjust light intensity through two alternative operating modes: (a) Traffic Adaptive Installation (TAI), which dims the light based solely on real-time traffic flow measurements; and (b) Full Adaptive Installation (FAI), which, in addition to traffic measurements, also requires evaluating road surface luminance and meteorological conditions. In this paper, we first present the general architecture and operation of an FAI-enabled lighting infrastructure, which relies on environmental sensors and a heterogeneous wireless communication network to connect intelligent, remotely controlled streetlights. Subsequently, we examine large-scale, in-field FAI infrastructures deployed in Vietnam and Italy as case studies, providing substantial measurement data. The paper offers insights into the measured energy consumption of these infrastructures, comparing them to that of conventional light-control strategies used in traditional installations. The measurements demonstrate the superiority of FAI as the most efficient solution.