# Applications of Wireless Sensor Networks: An Up-to-Date Survey
## 2 Main WSN Applications
### Urban Applications
#### 2.6.3 Transportation Systems  
The transportation of vehicles within the urban environment is an important factor for the safety and proper function of public roads. In the modern era various researchers have proposed many systems in the transportation domain, which by utilizing WSNs can improve the safety of roads and provide information during the use of them by drivers. Below we present some relative WSN applications applied in the transportation domain. In [54] the authors describe a WSN application for VANETs. This application using Secure Multimedia Broadcast Framework (SMBP) is to monitor a persons' way of driving by utilizing a  
Figure 17: A depiction of the various setups where WSNs can be deployed [48]. processing unit on the vehicle, which analyzes data, collected from the sensors in order to calculate the cost of the driver's insurance. The described system is utilized in order to determine how much the driver detects nearby vehicles, drives with caution, follows the traffic law, or uses a mobile device. The sensing system includes a static sensor board that provides the sensed data via cellular network to the control center and a Global Position System/Universal Mobile Telecommunications System (GPS/UMTs) module in order to connect to the Internet. The basic configuration of SMBP is depicted in Figure 18.  
In [55] a system is proposed, which analyzes the performance of a vehicle on the road by utilizing a telematics WSN. The system utilizes deployed sensor nodes on the road and a sink node on the roadside. The sensors nodes detect the passing vehicles and transmit data to the sink node. Furthermore, when an event occurs a packet is created, the sink node implements a timestamp to it and forwards it to the com node, which utilizes a level-based static routing protocol. Next, the com node forwards this packet to the user, which analyzes the provided information in order to determine various metrics of the road such as a vehicle's speed, lane vehicle density etc. A depiction of the overall system configuration is shown in Figure 19.  
In recent years, various WSN have been deployed within cities resulting in the formation of small WSN based islands. In [56] the authors describe an integration of these existing islands deployed along the roadside, in order to be utilized for post-accident management and to prevent accidents. Furthermore, the authors utilize two wireless standards i.e., IEEE 802.15.4 and IEEE 802.11p due to the need for separate roadside sensor units. In order to prevent accidents, the WSN islands constantly detect road conditions and transmit information to the vehicles passing by the area, which aggregate  
Figure 19: A graphical depiction of the WSN based transportation monitoring system [55]. Figure 18: A representation of the Secure Multimedia Broadcast Framework (SMBP) [54]. these data. Then the vehicle that has this information, transmits warning messages to nearby vehicles in order for the data to be disseminated along the road. The post-accident gathered information is restricted, by the authors, in order to be used only by authorized personnel such as insurance companies, criminological teams, or other authorities. Moreover, according to the authors, the post-accident management can function properly by communicating with the WSN islands on the roadside, without the use of VANETs. The overall system operation is illustrated in Figure 20.  
The researchers of [57], presented a mechanism that controls the speed of a vehicle by utilizing an infrastructure-to-vehicle communication via WSNs. In the described system the traffic lights utilize long-range RFID tags, which can measure a vehicle's speed and communicate with the vehicle's onboard RFID tags, to avoid collisions. The onboard RFID tags are able to provide feedback to actuators, which can change the longitudinal speed by controlling various parameters of the vehicle such as braking and throttling. Furthermore, the authors created a fuzzy logic algorithm enabling the automatic control of the vehicle.