# Smart Parking: A Literature Review from the Technological Perspective
## 6 Conclusions  
Based on the reviewed literature, there are a few solutions where LPWAN technologies are used for smart parking implementations, but the most reviewed research papers used LR-WPAN technologies, specifically, ZigBee. Anyhow, there is a trend in using LPWAN solutions as shown in the findings discussed before.  
There are several types of sensors that can deploy a smart parking solution. The conditions that dictate using one or another sensor are tied to technological advantages, budget, type of solution, and weather. Our research identified that in terms of technological advantages, there are four particular features that should be considered, those are: invasive, ease of installation, sensors per slot and detection autonomy. Those features would help to identify the ideal sensor to be used in any smart parking system.  
Network security implementations are not a concern at the moment of the deployment of a solution, although it could become an issue for the potential misuse of the transmitted information and the reliability of the system. From the client/end-user perspective, the great majority of solutions focused on devices capable of connecting to the Internet because it allows the system to expand to a great variety of gadgets. Sensors used for retrieving information in smart parking solutions must have real-time and automatic data collection. As a result, almost every implementation described in the reviewed papers used some kind of sensor. Although smart parking systems generate a lot of data, several implementations did not implement or propose prediction algorithms from the retrieved data.  
In terms of future work, one way to improve this survey is to increase the number of reviewed papers and focus on a specific system to narrow the field. The review focused more on smart parking implementations capable of working on street and inside. In addition, we plan to perform a comparative analysis about the effectiveness of LPWAN or LR-WPAN on Smart Parking to propose a formal method to select a sensor based on its technical features and the aim pursued.  
Conceptualization, S.G.Y. and J.J.B.; data curation, J.S. and J.L.L.; methodology, J.J.B. and S.G.Y.; investigation, J.S., J.L.L., A.U., D.P., J.J.B.; resources, S.G.Y. and J.J.B; writing-original draft preparation, J.S., J.L.L., A.U., D.P., J.J.B.; writing-review and editing, J.J.B., S.G.Y., R.A.; visualization, J.S., J.L.L., A.U., D.P.; supervision, J.J.B. and S.G.Y.; project administration, S.G.Y.; funding acquisition, S.G.Y.  
The authors gratefully acknowledge the financial support provided by the Escuela Politecnica Nacional, for the development of the project PIJ-17-08--\"Disefo e implementacion de un Sistema de parqueadero inteligente\".  
The authors declare no conflicts of interest.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & \multicolumn{3}{c}{**Features**} \\ \hline
**Protocol** & **Protocol Type** & **Range** & **Network Topology** & **Spectrum** \\ \hline \multirow{2}{*}{LoRaWAN} & \multirow{2}{*}{Long-Range} & 5 km (urban) & \multirow{2}{*}{Star} & \multirow{2}{*}{Free} \\  & & 20 km (rural) & & \\ \hline \multirow{2}{*}{NB-IoT} & \multirow{2}{*}{Long-Range} & 1 km (urban) & \multirow{2}{*}{Star} & \multirow{2}{*}{Licensed} \\  & & 10 km (rural) & & \\ \hline ZigBee & Short-Range & 10 m–100 m & Mesh & \\ \hline IEE802.15.4 & Short-Range & 10 m & Mesh & \\ \hline \hline \end{tabular}
\end{table}
Table 7: Sensor networking features.