# Smart Parking: A Literature Review from the Technological Perspective
## 3 Smart Parking Solutions
### Types of Sensors
#### 3.1.1 Camera  
An approach for information retrieval is by using the video cameras of parking lots, which have the ability to process images by themselves without the aid of external devices or algorithms. This allows controlling many vehicles with one piece of equipment. This approach also leads to the creation of a new part of the system focused on receiving and processing those images. For this scenario, a common technique is the use of wide-angle cameras together with a classification algorithm to detect the parking lines and establish the status of a space, as described in [73]. Moreover, an approach that involves rearward cameras is described in [63]. The main purpose of this work is to help drivers parking in a selected spot by using a touch screen. This approach is composed of three steps: bird's-eye view construction, guideline recognition, and identification of parking separating lines. The authors propose a novel approach to operate with real-time images. This semiautomatic initiative has good performance and does not require hardware modifications according to the authors. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & & \multicolumn{5}{c}{**Sensor Type**} \\ \hline
**Reference** & **Camera** & **Ultrasonic** & **Cellular Sensors** & **Infrared** & **Radar** & **Other** & **Magnetometer** \\ \hline
[60] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[61] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[62] & \(\blacklozenge\) & \(\blacklozenge\) & - & - & - & - & - \\ \hline
[63] & \(\blacklozenge\) & - & - & - & - & - & - \\ \hline
[64] & - & \(\blacklozenge\) & - & - & - & - & - \\ \hline
[65] & - & \(\blacklozenge\) & - & - & - & - & - \\ \hline
[66] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[67] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[68] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[69] & - & - & \(\blacklozenge\) & - & - & - & - \\ \hline
[70] & - & - & - & - & - & - & \(\blacklozenge\) \\ \hline
[71] & - & - & - & \(\blacklozenge\) & - & - & - \\ \hline
[72] & - & \(\blacklozenge\) & - & - & - & - & - \\ \hline
[73] & \(\blacklozenge\) & - & - & - & - & - & - \\ \hline
[74] & \(\blacklozenge\) & - & - & - & - & - & - \\ \hline
[75] & - & - & - & - & - & \(\blacklozenge\) & - \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._Likewise, it is possible to use common outdoor cameras to improve the accuracy of detection by training the algorithm with images taken in different weather conditions [74]. The authors also describe another solution, which involves storing an image of the area taken from a camera in a database together with the coordinates of each space, and then comparing the stored image with the images that are sent in real-time to establish if a parking lot has been occupied or not. In this scenario, it is important to consider that when video cameras are used outside, efficiency can be reduced due to weather conditions, even if the training phase was performed with images of several weather conditions. However, when it comes to indoor parking lots, this can be a viable option since images are not affected by weather conditions. Images are stored into a database along with the coordinates of each one of the parking lots, and can be compared with images that are being sent on real-time to determine if a slot is occupied or not. There are other solutions where users are involved to establish parking slots occupancy through cameras installed in their vehicles as stated in [56]. This proposal pretends to help drivers to avoid parking in illegal places by offering a real-time system. The authors use event recorders to collect information. The technique used to determine vacancy of a space is static image streaming. In this system, drivers generate a parking request through a mobile Android application, and the response contains location of the place. The mobile application also collects information through the camera. The system collects and process images and videos to determine and suggest an available parking space.