## 4 IoT-Enabled Traffic-Aware Telemedicine Architecture (ITTA)
### Wearable-Device-based Monitoring Algorithm for Edge Device (WDMA-Edge)
\begin{table}
\begin{tabular}{l l l l l l l l l l} \hline
**Research Works** & **LBS** & **A** & **B** & **C** & **QoS** & **V2V/V2I** & **D** & **E** & **F** \\ \hline
[29] & & & ✓ & & ✓ & & & & ✓ \\
[48] & ✓ & & & ✓ & & & & ✓ & \\
[49] & & ✓ & & & ✓ & & & & \\
[50] & & & ✓ & & ✓ & & & & ✓ & \\
[30] & & & ✓ & & ✓ & & & ✓ & \\
[31] & & ✓ & & & & & & ✓ & ✓ \\
[51] & & & ✓ & ✓ & & & & & ✓ \\
[52] & & ✓ & ✓ & & & & & ✓ & \\
**ITTA** & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline \end{tabular} \({}^{\text{A}}\) Real-time health monitoring; \({}^{\text{B}}\) Multi-level health risk assessment; \({}^{\text{C}}\) Data transmission from mobile ambulance; \({}^{\text{D}}\) Adaptive routing; \({}^{\text{E}}\) Cloud storage/processing; \({}^{\text{F}}\) Medical scoring for patients in transit.

\end{table} 
Table 4: Comparison of existing telemedicine architectures with IITA. \begin{table}
\begin{tabular}{l l} \hline
**Features** & **Simulation Parameter Specifics** \\ \hline Communication Technology & WiFi (802.11) \\ Length of Road Stretch & 6 km \\ Geographic and Spatial Division (km) & Rural-2, Sub Urban-2, Urban-2 \\ Temporal Slots & Details in Table 6 \\ Speed & 60 kmph (rural), 40 kmph (suburban), 20 kmph (urban) \\ QoS Parameters & Details in Table 3 \\ Inter-packet interval & 1 s/0.1 s \\ Data type and Packet Size in Bytes & PR—250; Audio—500; ECG—300 \\ Routing mechanisms & Flooding, AODV, GPSR \\ \hline \end{tabular}
\end{table} 
Table 5: Simulation parameters. _Scenario 2--Ad Hoc Networking with Vehicles and Stationary Relay Nodes (V2I):_ Here, to compensate for the non-availability of the required density of vehicles in specific regions, additional stationary relay nodes are provided in specific regions, along with vehicles in the road stretch. The densities of these nodes are varied on a spatio-temporal basis based on the time slot and the expected region of the traversal, as represented in Table 6. Scenario 2 is represented in Figure 4.

A new approach of machine learning modelling for establishing the communication through VANETs is presented [53]. The communication system architecture considered for this simulation caters to both of the above-mentioned scenarios. The simulation gives the provision to choose sender, receiver, intermediate nodes and their communication technology. Ambulances are chosen as the sender for this simulation study along with a VANET-based telemedicine architecture, with IEEE 802.11 as the radio access technology (RAT) [54; 55; 56]. The mobile ambulances are simulated to traverse through different types of traffic scenarios experienced in rural, suburban, and urban areas, totalling a 6 km road stretch. The key parameters chosen for the simulation are shown in Table 5.

Figure 3: Representation of Scenario 1. ### Experimental Design and Performance Analysis

To derive the dynamic variability in vehicular density, a field survey was conducted for a stretch of 15 km highway road network in Mysore, India. The road stretch was chosen to provide the insights of traffic experiences in rural, suburban, and urban areas. The survey was performed at multiple selected locations across the road network. The total number of vehicles traversing through those locations for a specific time period, a period of several days, was collected. Based on the survey, a unique set of seven temporal durations and the corresponding vehicular density for a two-kilometer road stretch for different regions were derived. These details, presented in Table 6, are used for the simulation experimentation. Nevertheless, the architectures, frameworks, and algorithms suggested in the manuscript are relevant across a wide range of geographical regions. In the simulation, the vehicles are modelled to move at different velocities [57; 58] in different regions, such as 60 kmph in rural regions, 40 kmph in suburban regions, and 20 kmph in urban regions, based on the field survey. The ambulance was simulated to move at a velocity of 80 kmph, since an emergency vehicle is allowed to traverse at higher velocities.