## 6 Mobile Sensing Networks in the Smart City  
As it has been presented in previous sections, UANs comprise fixed sensor and actuator nodes. However, there exists a family of emerging networking paradigms that exploit sensing, computing and  
Figure 6: Economic cost estimate of each UAN class, based on Table 3 pricing data.  
communication resources available on mobile devices, such as personal consumer electronics equipment (most notably, smartphones) or in-vehicle systems, for data collection and processing [50, 51]. We refer to this category of networks as Mobile Sensing Networks (MSNs).  
MSNs can complement and cooperate with UANs to enable Smart City applications [52]. UANs provide the solution for the subset of Smart City applications that require the deployment of fixed sensor nodes in specific locations, such as garbage container occupancy sensors, underground humidity sensors in green zones, leak/breakdown sensors in utility infrastructure or security sensors in restricted access zones. Otherwise, MSNs may enhance UAN operation, by providing additional sensed data. However, MSNs alone cannot offer reliable and predictable data collection, as discussed in subsequent paragraphs. Table 4 shows the Smart City applications enabled by UANs or MSNs.  
In comparison to UANs, MSNs exhibit a few significant advantages. MSN devices are less resource-constrained than the usual mote-type of UAN sensor nodes. On the other hand, billions of MSN units (either mobile devices or connected vehicles) are already _deployed_, _i.e._, are located in close proximity of their human users, which may reduce fixed sensor node deployment costs [50]. However, MSNs introduce additional challenges and complexity. Predicting the resources (e.g., energy or bandwidth) that may be needed to carry out a given task, and even whether the task itself can be performed, is difficult. Further, challenges arise in dense scenarios, due to wireless bandwidth limitations, which require techniques for efficient channel utilization [51]. Finally, MSNs rely on the willingness of the users to contribute to data collection, and require more complex processing operations to mitigate the intrinsic low reliability of the collected data (e.g., a smartphone measuring light levels might be temporarily in the user's pocket).  
The devices of a MSN may use radio interfaces such as IEEE 802.11 variants or cellular (e.g., 3G/4G) to communicate between themselves or to transmit data via the Internet to a Smart City management center, where the data can be processed and stored. Data obtained by both UANs and MSNs can potentially be combined in the management center to enrich the overall data collection, decision and actuation process.  
We divide MSNs in smartphone-centric MSNs and vehicle-centric MSNs (the latter are also known as Vehicular Sensor Networks, VSNs). The next two subsections focus on these two MSN classes, respectively.  
\begin{table}
\begin{tabular}{c c c} \hline  & **UANs** & **MSNs** \\ \hline
**Garbage collection** & Yes & No \\
**Lighting control** & Yes & Yes \\
**Green zone management** & Yes & No \\
**Environmental control** & Yes & Yes \\
**Parking availability** & Yes & Yes \\
**Street traffic** & Yes & Yes \\
**Utility infrastructure** & Yes & No \\
**Security** & Yes & No \\ \hline \end{tabular}
\end{table}
Table 4: Smart City applications enabled by UANs or MSNs. Note that MSNs alone cannot offer reliable and predictable data collection. The list of applications is the same as the one in Table 1.