# Sensor Reliability in Cyber-Physical Systems Using Internet-of-Things Data: A Review and Case Study
## 5 IoT LiDAR-based Collaborative Mapping - A Case Study  
The IoT sensor network chosen to evaluate the CPS-based co-simulation framework is composed of virtual and real LiDAR sensors [28]. An Ibeo Lux LiDAR 4-layer sensor was used with the following specifications: horizontal field of 120 deg, horizontal step of 0.125 deg., vertical field of 3.2 deg., vertical step of 0.8 deg., range of 200 m, and an update frequency of 12.5 Hz. As previously mentioned, the sensor network to be evaluated is composed of IoT sensors. The sensor network therefore has IoT capabilities connected to its computing nodes. These nodes are on-board computers integrated in an autonomous vehicle with a wireless communication interface between them.  
The particular implementation of the CPS-based co-simulation framework, the LiDAR-based collaborative map is based on a co-simulation framework between two different software systems, designed in [90]. However, the contribution of this study is to include the real part in the co-simulation framework. This framework consists mainly of a computer-aided system to enable efficient interaction between the virtual scenario with virtual nodes setting in the simulation tool of Webots for automobile 8.6 [91] and an external application development for the computing nodes in the real scenario. The scenario in this particular case, in which the vehicles are represented as nodes, is as follows. A real vehicle (in a real scenario) and three virtual vehicles in the simulated scenario are detecting obstacles. Both kinds of vehicles share the position, object type and size of the obstacles (e.g., pedestrian, trees on the road and another vehicle). This is possible thanks to the IoT LiDAR network using an IoT obstacle  
Figure 3: Conceptual flowchart showing the operation of a reliability co-simulation framework with CPS computing nodes and IoT sensors.  
detection application (see Section 4.1), created in run time. Figure 4 shows the detailed diagram of the implementation of the LiDAR-based collaborative map using the CPS-based framework approach.  
As mentioned above, the exchange of information packets between the local nodes with the main or global node is possible thanks to the use of a communication protocol using a UDP (User Datagram Protocol) as the transport layer and a Wi-Fi 802.11p as the physical layer. The visualization of the co-simulated vehicle (real node) in the 3D virtual scenario in the Webots simulation tool is also possible. An example of the execution of the co-simulation architecture can be seen in Figure 5.  
Figure 4: Detailed diagram of the implementation of the LiDAR-based collaborative map approached through a CPS-based co-simulation framework.  
Figure 5: Data interchange between LiDAR sensors in (virtual and real) driving assistance scenarios in Webots for automobiles.  
In addition, another application implemented in the IoT LiDAR-based collaborative map is the LiDAR self-testing methodology incorporated in each local computing node (autonomous vehicle), in order to evaluate the reliability of each IoT sensor in the network that will be described in Section 5.2.