# Wireless Communication Technologies for Safe Cooperative Cyber Physical Systems
## 3 Communication Technologies for SafeCOP Co-CPSs
### Hospital Application  
This use case will employ two different wireless protocols, namely Wi-Fi and XBee. The IEEE 802.11-based Wi-Fi protocol will primarily handle MiR100-to-camera communication. Wi-Fi infrastructure is already installed in some hospitals, and provides good coverage with relatively high data rates needed for transmission of live video streams. In addition, since both MiR100s are connected to the same network, non-safety related information and data will be transmitted between the MiR100s over the Wi-Fi connection. The Wi-Fi network can also be used for future communication between MiR100 and other hospital information systems of interest. For safety-critical MiR100-to-MiR100 communication, a small and inexpensive IEEE 802.15.4-based 2.4 GHz XBee-solution has been selected. This link will be used to safely coordinate and synchronize the movements of the two MiR100s. Although the over-the-air data rate of the XBee is limited to 256 kbps, this should be sufficient for this purpose.  
The proposed setup of the autonomous hospital beds illustrated also in Figure 1 has been considered in some previous works that we discuss below. In [53], the authors provide an experimental testbed with mobile robots that can receive their position through a centralized camera. The images are processed in a central PC unit, which is able to send the position information to each robot over ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation, where robots communicate to its neighbors only at event times. In [54], the authors provide a similar testbed setup that is used for localization and tracking using CMUcam3 modules mounted on static WSN nodes. A partially distributed approach was adopted and image segmentation was applied locally at each WSN camera node. The output of each WSN camera node, i.e., the location of the objects segmented on the image  
Figure 6: System architecture for the traffic management application through V2I cooperation.  
plane, is sent to a central WSN node for sensor fusion using an Extended Information Filter (EIF). To a similar direction, authors in [55] proposed a testbed setup, where the images captured synchronously by the cameras are processed at each node with the objective of extracting the essential information of the object. To cope with the usual low bandwidth of WSN, only this distilled information is sent through the WSN. The measures from all the cameras are integrated using information fusion methods such as maximum likelihood and extended Kalman filters. Finally, in [56], the authors also provide a cooperative control system of multiple robots using infrared cameras and image processing to facilitate the cooperative formation control. The above mentioned works are benchmarked in terms of distance among the mobile robots and their estimated location in a formation control. Due to the heterogeneity of the considered formation controls for each case, we can not compare their results. However, a general outcome is that localization errors could exist depending on demanding formation control and in case of traveling longer distances [57].