## 4 IoT-Enabled Traffic-Aware Telemedicine Architecture (ITTA)
### Wearable-Device-based Monitoring Algorithm for Edge Device (WDMA-Edge)
When viewed from the perspective of data type, our experiments demonstrate that in the case of PR, AODV faces much lower loss compared to GPSR during late evening as well as night. Ironically, when the density is lowest (104 vehicles), during early morning, the loss increases again. Such a pattern is not observed for other data types, where lower loss is seen only during high vehicular density. The reason for this may be the difference in the traffic model. PR traffic has a packet size of 250 bytes per sec, whereas audio has 500 bytes per sec and ECG has 3000 bytes per sec (300 bytes every 0.1 s). These experiments demonstrate that for lesser packet size, AODV performs better than GPSR, provided that the inter-packet interval is less than a second. **Scenario 1**: _Variability of delay with respect to different routing protocols and message types._

Considering the delay experienced in Scenario 1, we observe that GPSR gives the best performance throughout the day, except during late evening when, ironically, all the other routing mechanisms provide a much better performance compared to GPSR. During late evening, GPSR results in higher delay for PR and ECG. The delay with AODV is also within acceptable limits, as per the QoS requirements in Table 3, except during evening, when it becomes very high for ECG. This might be due to the fact that even though the size of the ECG packet is 300 bytes, the frequency of transmission is very high. As can be seen from Table 8 and Figure 6, on average, GPSR gives the lowest delay in this scenario amongst the three routing mechanisms. From the perspective of node density, it can be noted that AODV does not perform well in the case of higher densities, such as 664 (mid-day) and 726 (evening). The reason for this might be the high network overhead created due to control messages when a very high number of nodes are present. Flooding shows the worst performance on average and GPSR shows a consistently low delay, except during late evening, when the delay is seen to increase by 500 times, as seen in Tables 8-10. From the perspective of data type, flooding always shows a spike in the delay (more than 500 times) during morning and mid-day, when the vehicular density is on the higher side (517 and 664). At the same time, for the highest density of 726 during evening, flooding does not record much difference in performance, whereas AODV does show an increase. In the case of ECG, this increase is 15 times more than audio and 577 times more than PR. In fact, in the case of ECG, AODV shows an increase in delay 40% of the time compared to the other data types. This happens most when the density is either very low (104) or very high (726). The reason for this increase is the high frequency of sending ECG data. Figure 5: Packet loss ratio (PLR) experienced by each data type in Scenario 1. **Scenario 2**: _Variability of packet loss ratio with respect to different routing protocols and message types._

In this scenario, AODV provides very good results throughout and the packet loss using the protocol is extremely low and almost non-existent. Especially in the case of ECG, the loss ratio is very low, recording a maximum of 1% in most cases. Figure 7 shows the PLR throughout the whole day in the case of Scenario 2. Based on Figure 7 and Table 9, it is clear that when the vehicular density is very high, during evening (726), the PLR faced by AODV is the lowest. GPSR also shows an improvement in the PLR during this time of the day. In fact, except for evening, GPSR faces very high packet loss during all other times. It is observed that the placement of stationary nodes in the scenario has immensely helped in improving the PLR. From the perspective of data type, if the inter-packet interval is low and packet size is low, then the PLR is also low. PR packets have a lower size compared to ECG (250 and 300 bytes). However, the PLR of ECG is much lower, since the interval is one-tenth of PR when AODV is used.