# Survey of Smart Parking Systems
## 8 Conclusions  
The study was based on finding evidence of the types of SPS, the VDT that these systems use, the algorithms and methods that they apply, and the stage of development of each work. The research was divided into four features. By applying a formal methodology of searching for and selecting papers, we obtained a set of 274 works published between January 2012 and December 2019. The result of this survey was the classification of the types of SPS for vehicles that exist in the literature. It is important to mention that this work presented an analysis of how SPS relate to VDT, as well as an exhaustive study of the types of algorithms that these systems implement, allowing us to group and classify these characteristics. Finally, a classification was made that allowed us to determine the stage of development of the works analyzed are in. It was possible to observe how the number of publications increased per year (see Table 8) over the range of years analyzed. Among the total 274 articles, 132 were published in the last three years (January 2017-December 2019). Based on the results, in relation to SPS type, most applications were PRS and PGIS. In addition, there are growing alternatives that implemented crowdsourcing techniques where users are the players within the system as they feed information to it in real time. Furthermore, when investigating the VDT applied to the SPS, it was observed that ORS sensors predominated the papers found in the literature. This solution can be expensive in middle- to large-sized cities because of the large the number of parking slots they have to monitor. However, other proposals like CS or DFTP, such as parking meters or systems implemented by the government for parking control, can be truly effective low-cost solutions for an intelligent parking system. Dynamic algorithms were the most predominant algorithms or methods used. This type of algorithm can react to changes in variables because they can change over time; however, if this happens, the use of resources due to processing can be used inefficiently, unlike, for example, real-time algorithms which, although more complex to implement, have a much more powerful and efficient performance. Finally, in terms of the stage of development of the work found, 50% of the systems proposed were simulated while 48% were merely proposals, and only 2% of the applications among the 274 articles selected were implemented. In conclusion, it can be determined that the applications proposed by SPS have great potential, as there is a wide variety of types and a wide range of algorithms and methods that can be implemented. This problem is very new given that the largest number of articles were published in the last four years (see Table 8). This study can serve as a starting point for future research on the subject. Section 7 discussed some of the gaps and open issues identified during our research, leaving an analysis of several aspects that involve the issue of SPS. As future work, we will propose the development consist of a PGIS-type SPS to be simulated in a public parking environment of a city. This system will be developed with a real-time algorithm, based on drivers' preferences, which will establish a multi-target function for choosing the most optimal parking slot according to those preferences. The algorithm will also allow the re-planning of routes according to what happens in the context. Conceptualization, M.G.D.O., R.F., and S.A.; funding acquisition, R.F. ; investigation, M.G.D.O., R.F., and S.A.; methodology, M.G.D.O. and S.A.; supervision, R.F. and S.A.; writing--original draft, M.G.D.O. ; writing--review and editing, M.G.D.O., R.F., and S.A. All authors read and agreed to the published version of the manuscript. This work was funded by the DURSI consolidated research group Smart IT Engineering and Services (SITES) (ref. 2017 SGR-1551), Institute of Informatics and Applications at the University of Girona, and by a PhD scholarship (M.D.) by the National Council for Scientific and Technical Research (CONICET), Argentina.