# IoT-Based Patient Movement Monitoring: The Post-Operative Hip Fracture Rehabilitation Model
## 5 IoT System Performance
### IoT System Performance Testing
These also decrease as the time interval rate increases, as this provides enough time for the data transmission to occur successfully. **Experiment 2:** In the second experiment, all five nodes are active and attached to the human subject at five different body locations (hip, thigh, ankle, waist, and chest), during a slow walking activity movement. Figure 8 represents the wearable edge and gateway edge packet loss comparative analysis when all the nodes are active and transmitting data to the coordinator. From the analysis, it can be seen that an average packet loss of 1% has been observed when FFT-based computation is performed at the wearable sensor level. In contrast, at the gateway edge level, the packet loss is quite high, i.e., 74% when the data transmission rate is 1 s. However, as the time interval rate increases to 2, 3, and 4 s, the percentage packet loss % also reduces to 70, 67, and 62%, respectively. Figure 7: Average packet loss analysis for a static five-node network at the gateway edge level. Increasing the number of nodes significantly influences the size of packet loss when detailed data are communicated. In summary, the main reason for no or minimal packet loss at the wearable sensor edge level is because the final data are compressed into one communication transaction of 16 bytes which does not overload the communication system during the transmission process. On the other hand, at gateway edge level, data are not completely compressed and require 128 communication transactions with a data packet size of 12 bytes to be transmitted. Therefore, all the 128 readings are required to be received by the gateway for the FFT process to be accurate. Missing one or more readings out of the 128 would affect the FFT process and hence end up discarding a complete set of data collected at the specified interval. As a result of such losses, an increase in the percentage of packet loss was observed for all the nodes and across all the networks at the gateway edge level. Considering the radio packet transmission and computational processing occurring at the wearable and gateway edge levels, analyzing the wearable device energy consumption and how long it would last at four different time intervals chosen in the packet loss analysis is essential. Since the Microduino modules can run on 3.3 V, the wearable device is powered with a \(\
icefrac{{1}}{{2}}\) AA rechargeable battery of 1000 mAh at 3.7 V with a cut-off voltage of 2.75 V. The battery selection is random in order to cover a day. Figure 9 represents the wearable and gateway edge energy consumption at four different time intervals, i.e., 1, 2, 3, and 4 s. The results show that at the wearable edge level, the current consumption for all time intervals ranges from 20 to 24 mA. However, at the gateway edge level, it ranges from 25 to 30 mA. Therefore, the gateway edge current consumption is higher compared to the wearable edge because 128 communication transactions with a data packet size of 12 bytes are continually transmitted. Figure 8: Average packet loss when acquired data are processed and compressed at the wearable edge or gateway edge for an active five-node network. Processing at the wearable sensor age offers significant improvement in terms of system performance.