# Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems
## 4 Economic Analysis
An example of such technology is the previously introduced TAI, which adapts the light intensity to traffic conditions. According to the lighting standards CEN/TR 13201 [8; 9; 10; 11; 12], the traffic intensity must be calculated over a recent period of time. However, the norm gives no specification about the duration of such period. Clearly, the shorter the time window, the more responsive the system is, which might potentially lead to higher energy savings. The drawback is that more frequent vehicular traffic assessments entail an increase of the communication traffic among luminaries as well as of the data processing burden. A common value is a 15 min interval [78]. According to case studies investigated in Poland [68], the expected energy saving due to TAI adopting a 15 min interval could reach 47% compared to a preset dimming schedule, which is about 33% of the overall cost per year per each streetlight. Similar results can be found in [79]. **LC operational cost. ** Clearly, the adoption of smart LCs introduces also some costs. In fact, LCs must be active 24 h a day, either because they also support additional IoT services or simply because they continuously listen to possible messages from the Control Center. Commercially available LCs have a global power consumption that varies between 1 W and more than 5 W (see [80; 81] for further readings). This is a very significant difference. In a (conservative) ten years perspective of the plant lifetime and considering, for instance, a medium town with 10 k streetlights, two extreme solutions might lead to a difference of about 3.5 GWh in the whole period. This corresponds to hundreds of thousands dollars/euro, which might be saved with a proper choice of the LC. Furthermore, in absolute economic terms, the saving generated by dynamic dimming is about 10 dollar/euro per year per each street light. Clearly, the operational cost of such feature cannot exceed the saving it provides. The thing is, though, that this functionality relies on frequent real-time communications (not only few bytes a day) whose cost should be carefully considered. In this regard, it appears very challenging to obtain from a telco operator the support for such an amount of data traffic with a yearly cost per each fixture significantly lower than the saving achieved by dynamically dimming the light. It follows that providing the LC with the dynamic dimming functionality calls for a proper choice of the communication technology, which might hardly be a third-party network (e.g., cellular), with the consequent fee. More in general, the choice of the communication technology requires a more comprehensive discussion, as different choices have different impacts on costs as well as on the smartness of the lighting service and the possibility to offer additional services (not related to public lighting), supported by the same communication infrastructure. This fundamental issue is thoroughly discussed in Section 5. **Overall economic balance. ** The San Diego case. ** As far as the cost of the whole infrastructure is concerned, a good reference is provided by the city of San Diego (USA), which recently replaced 14,000 of the city's more than 40,000 streetlights with energy-efficient LED lamps that can communicate with one another and operators and allow lighting adjustments to save energy. As reported in [82], _\"the price tag comes in at US $30 million, but it won't break the budget (...) because it will save 60 percent in the cost of powering the city's lights. Over the next 13 years, these savings will more than cover the hardware and cloud-computing services required for the streetlight IoT.\"_  
The reader may refer to the Annex IV (_\"Examples of Life Cycle Costing\"_) of [7] for other examples of city-wide installations, which are described providing the economic details (investment, saving, payback period,...).