# IoT-Enabled Smart Sustainable Cities: Challenges and Approaches
## 4 Smart and Sustainable Urban Mobility
* Safety: fatalities and injuries are drastically reduced. A smart city will be equipped with a monitoring system composed by a heterogeneous capillary sensor network [131] for targeting the reduction of the traffic within city limits, in which one of the first goal is to block vehicles in entering some zones of the city, in case of needs or based on permissions released to drivers (e.g., inside Limited Traffic Zone). This can be made by spreading sensors around the city and closing the entrance in case pollution exceeds properly set thresholds. Therefore, the definition of these policies and their corresponding data processing can be delegated _on-Edge_ (building a sort of \"network-of-networks\" monitoring a sector of the municipality and, thus, relieving each single sensing node from this processing task) as well as _on-Cloud_ (\"logically\" centralizing the decision process). In both cases, AI-based algorithms can be embedded in powerful processing nodes, as well as exploiting the potentialities of cooperative processing--shared among the involved nodes, while a logically-centralized rules definition allows to implement a plan based on the smart city's overall situation awareness. Another infrastructure which can improve the smartness of a city is associated with the deployment of several sensors to survey acoustic pollution and people flows inside the city limits. Both these monitoring systems can be spread in the smart city as a sensory network useful to retrieve information on noise levels in certain critical areas of the city itself, such as areas with high attendance in certain hours (e.g., pub areas frequented by young people) and along one of the main routes for city traffic. In fact, these systems allow to identify which are the most critical moments, giving this essential information to the municipality for planning future interventions in terms of organizing events. Figure 12: Mobility models applicable in a smart city [127]. Another hot topic on which a smart city may demonstrate to target a sustainable mobility is on boosting the utilization of electrical vehicles inside its city limits: this holds for both public and private transportation, as discussed in Section 3.7. With regard to the _public_ case, the replacement of the public transport's vehicle fleet with electric vehicles is encouraged, thus reducing pollution emissions [132] (e.g., as detailed in Section 3.8, particulate matter, PM\({}_{10}\), PM\({}_{2.5}\), NO\({}_{x}\), O\({}_{3}\), CO, CO\({}_{2}\), CH\({}_{4}\), and N\({}_{2}\)O) and reducing oil-powered vehicles, thus providing citizens several benefits (e.g., ticket price's reduction). Instead, with reference to _private_ transportation, the provision of recharging stations for electrical vehicles improve the citizen's awareness in buying electrical vehicles, especially for those whose habitual travels are inside the city limits. Moreover, this allows to build an integrated network of recharging stations on top of which the municipality can define new services, such as an overall infrastructure for paying the electricity refill, obtaining at the same time a reward based on the usage of electrical vehicles (e.g., to be discounted from the taxes to be payed by the citizen). An additional valuable deployment for supporting the aforementioned topics regards the smart monitoring of parking slots for different types of vehicles [133]. This can take place through a network of heterogeneous sensors, partly embedded in the asphalt and partly through the utilization of optical devices, while data processing can be performed, as for previously mentioned scenarios, both locally and remotely. In the _first_ case, it can be required to send only few aggregated data: this can require the adoption of low-power and low data rate transmission protocols (e.g., LoRa), in order to reach edge nodes without the need of cellular (e.g., LTE-4G/5G) or IEEE 802.11 connectivity.