# IoTactileSim: A Virtual Testbed for Tactile Industrial Internet of Things Services
## 4 Discussion and Future Work Directions  
In our previous work [23], we analyzed the different haptic gloves and investigated how data processing increased the latency in the haptic communication loop and proposed a low-latency haptic open glove (LLHOG). Contrary to previous work, the focus of this paper is to provide network infrastructure to transmit haptic traffic between operator and teleoperator and simulate delay-sensitive and loss-intolerant tactile IIoT applications. However, there are various industry 4.0 applications under use cases class C, such as fleet management, tactile-driven logistics, cooperative robotics, and motion control, which demand higher QoS and QoE. To allow these real-time applications, the utilization of edge computing is required. Therefore, there is a need for edge-based network systems with native machine learning parts to provide the QoS and QoE requirement provisioning for these applications. In this regard, as a future, an edge-based ITE is developed as a tactile support engine to enable the ability for the user to train and deploy machine learning models at the edge to ensure QoS and QoE. The conceptual diagram to design and deploy the trained model on ITE is illustrated in Figure 14.  
In future work, more practical challenges regarding tactile IIoT in the real-world scenario need to be considered. As discussed above, providing required QoS and QoE in the real-time complex industrial application is more challenging than simulation analysis. Therefore, we indented to test the proposed IoTactileSim in real-time physical IIoT scenarios and demonstrate the real-world experiment design overview in Figure 15. On the master side, we utilized the LLHOG, which consists of the rotary position sensors with a min-max scaling filter to send haptic data. The bionic robot hand, which consists of Arduino  
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline \multirow{2}{*}{**Applications**} & \multicolumn{5}{c}{**IIoT Use Cases and Requirements**} \\ \cline{2-7}  & **Cycle Time** & **Message Size** & **Data Rate** & **Latency** & **Packet Loss Rate** \\ \hline \multicolumn{7}{c}{Control loop motion control} \\ \hline Machine tools & & & & & \\ Packaging machines & 0.5\(\sim\)2 ms & 20\(\sim\)50 Bytes & 1\(\sim\)10 Mbps & 0.25\(\sim\)1 ms & 10\({}^{-9}\)\(\sim\)10\({}^{-8}\) \\ Printing machines & & & & & \\ \hline \multicolumn{7}{c}{Remote control} \\ \hline Process automation & & & & & \\ Process monitoring & & & & & \\ Process maintenance & & & & & \\ Fault reporting & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Tactile IIoT use cases requirements specifications and characteristics supporting by proposed IoTactileSim.  
Figure 14: Conceptual architecture of ITE in IoTactileSim.  
and servo controllers, is used at the slave side. The specification, sample code, and documentation are available at the official website ([[https://wiki.dfrobot.com/](https://wiki.dfrobot.com/)]([https://wiki.dfrobot.com/](https://wiki.dfrobot.com/)), accessed on 30 November 2021 ). The proposed IoTactileSim connects the LLHOG and bionic robot hand to develop a closed control loop. The ITE is also integrated with the proposed IoTactileSim to monitor the network dynamics and guarantee the QoS and QoE requirements for tactile IIoT applications.