## 3 Results
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Category** & **Test** & \multicolumn{2}{c}{**Time [s]**} & \multicolumn{1}{c}{**Power**} \\  & **Cache** & **Cloud** & **[W]** \\ \hline \multirow{8}{*}{Weather} & 1 & 0.048 & 7.903 & \multirow{8}{*}{3.15} \\  & 2 & 0.031 & 8.717 & \\  & 3 & 0.013 & 6.850 & \\  & 4 & 0.070 & 7.994 & \\  & 5 & 0.011 & 8.556 & \\  & 6 & 0.098 & 5.980 & \\  & 7 & 0.049 & 7.911 & \\  & 8 & 0.052 & 8.087 & \\  & 9 & 0.120 & 7.949 & \\  & 10 & 0.018 & 8.890 & \\ \hline \multirow{8}{*}{Places} & 1 & 0.061 & 2.762 & \multirow{8}{*}{3.21} \\  & 2 & 0.028 & 4.838 & \\  & 3 & 0.014 & 2.918 & \\  & 4 & 0.027 & 3.606 & \\  & 5 & 0.006 & 4.784 & \\  & 6 & 0.018 & 3.870 & \\  & 7 & 0.045 & 2.097 & \\  & 8 & 0.040 & 3.501 & \\  & 9 & 0.086 & 4.569 & \\  & 10 & 0.029 & 2.990 & \\ \hline \multirow{8}{*}{Hystory} & 1 & 0.011 & 3.789 & \multirow{8}{*}{3.13} \\  & 2 & 0.019 & 4.881 & \\  & 3 & 0.053 & 5.059 & \\  & 4 & 0.030 & 4.941 & \\  & 5 & 0.041 & 5.058 & \\  & 6 & 0.004 & 3.902 & \\  & 7 & 0.057 & 6.784 & \\  & 8 & 0.016 & 4.197 & \\  & 9 & 0.025 & 5.629 & \\  & 10 & 0.044 & 3.479 & \\ \hline \multirow{8}{*}{Math} & 1 & 0.012 & 5.780 & \multirow{8}{*}{3.15} \\  & 2 & 0.053 & 7.018 & \\  & 3 & 0.045 & 6.192 & \\  & 4 & 0.026 & 6.118 & \\  & 5 & 0.043 & 6.197 & \\  & 6 & 0.020 & 5.601 & \\  & 7 & 0.047 & 5.866 & \\  & 8 & 0.034 & 6.514 & \\  & 9 & 0.049 & 7.303 & \\  & 10 & 0.036 & 6.734 & \\ \hline \multirow{8}{*}{Characters} & 1 & 0.553 & 2.797 & \multirow{8}{*}{3.15} \\  & 2 & 0.642 & 3.025 & \\  & 3 & 0.721 & 2.122 & \\  & 4 & 0.517 & 3.288 & \\  & 5 & 0.740 & 3.121 & \\  & 6 & 0.597 & 2.614 & \\  & 7 & 0.608 & 3.580 & \\  & 8 & 0.396 & 4.319 & \\  & 9 & 0.679 & 2.743 & \\  & 10 & 0.705 & 3.316 & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of response times from cache and cloud per category. As seen in Table 4, the response times for each test in cache and from the Internet are different. Furthermore, when analyzing the total time of the tests with responses from the cache compared to the total time from the cloud, a significant difference is identified: 0.768 s vs. 25.675 s. This leads to a substantial difference in energy consumption, which will ultimately be reflected in monetary costs. Thus, based on the response times obtained from each part of the process and considering the power measured during the query tests using the digital meter, which averaged 3.15 W, and the nominal power, meaning the maximum power consumed by the Raspberry Pi, which would be 4 W, the energy consumption of the VA in its ON state was calculated. \[E[jules]=P[W]\times t[seconds] \tag{19}\]  
Different results were obtained in terms of energy consumption for both local and remote (Internet) queries. Additionally, these times were used to predict the initial VAs (GA and Copilot) for which the experimentally measured power was 3.8 W and 5.5 W for each device, and the power at maximum load was 4.8 W and 6.5 W, respectively. With these data, the energy consumption levels for such VAs are presented in Table 5. The energy is shown in joules for both the Raspberry Pi and the initial VAs. The calculations for the proposed prototype indicate a difference of 78.4 J in energy consumption between cache-based and cloud-based queries. This means that a cache query consumes only 2.95% of the energy required for a cloud-based query, clearly highlighting a significant reduction in energy usage.