# Real-Time Human Activity Recognition on Embedded Equipment: A Comparative Study
## 5 Results of Implementation
### Implementation on Raspberry Pi and Comparison with Desktop PC
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Hardware Architecture** & **Processing Time** & **Memory Space** \\ \hline PC (Windows OS) & mean PT = 0.113 & mean memory = 138.71 \\  & min PT = 0.015 & min memory = 75.65 \\  & max PT = 3.852 & max memory = 149.83 \\ \hline \hline \multirow{3}{*}{PC (Linux OS)} & mean PT = 0.091 & mean memory = 99.9 \\  & min PT = 0.020 & min memory = 97.14 \\  & max PT = 2.580 & max memory = 107.69 \\ \hline \hline \multirow{3}{*}{Raspberry Pi 3 B+} & mean PT = 0.423 & mean memory = 119.78 \\  & min PT = 0.102 & \\  & max PT = 11.43 & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Performance Analysis of Hardware Architectures for Test Period 4 November 2010 to 7 November 2010 from 4 November 2010 00:03:50.209589 to 7 November 2010 10:37:00.414579.  
memory usage of the Windows PC is close to that of a Raspberry Pi. Windows tends to consume more resources than Linux. Windows operating systems often require more memory and system resources to run efficiently. Linux is characterized by its ability to run on relatively modest hardware, which often results in lower memory usage. This memory does not have the same order of magnitude as the MCUs. The simulation results on a Raspberry Pi and PC with Windows and Linux OS ensure that:  
* _Performance Efficiency_--The fact that the processing time is consistently within the specified constraint (i.e the processing time should be less than the delta time between events), indicates that the system is performing well in terms of speed. The average processing time is significantly below the maximum allowable time. It suggests a good margin of efficiency. * _Effectiveness under normal operating conditions_--In this work, the system's effectiveness is evaluated only under normal conditions. Such scenarios where the system operates continuously for an extended duration such as cases where activities last longer than expected or how the system responds to unexpected events are not studied because they are not the objective of this paper. * _Stability and Reliability_--The absence of memory failures (i.e., the risk that the program, at certain times, cannot obtain from the hardware the memory resources it needs) is a positive sign for system stability. It suggests that the system is handling the data processing without encountering memory-related issues. In addition, there are no warning messages or errors in the logs during the tests. The absence of errors is a good sign of system reliability. In fact, when we implement the algorithm on an MCU with C language or with MP, an error message is displayed when a memory overflow is made at time t. This is not the case for an implementation on a Raspberry Pi or a PC. * _Delta Time Consideration_--Since the processing time is less than the delta time between events, it means that the system can keep up with the pace of incoming events. This is crucial for real-time or near-real-time applications. * _Scalability_--The experience shows that when varying the quantity of data processed from period 1 to period 2, the system performance remained consistent, which suggests that the system might be scalable. This means it can handle increased loads without a proportional decrease in performance. We conclude that the system meets the specified constraint and does so consistently across different conditions. It is generally a positive sign. This means that the system is robust and capable of handling the specified workload.