# Monitoring Perishable Commodities Using Cellular IoT:
## 3 Results and Discussion
### Comparison with Other Dataloggers  
During the test with the other two dataloggers mentioned in Section 2.7, the data were also successfully recorded on the server. The trial lasted 24 h and the comparative results are represented in Figure 14 for temperature and relative humidity.  
As the graphs depict, it was verified that the trends of all the dataloggers in the measured parameters were the same, which was the main objective of this test. The maximum, minimum and mean absolute and relative errors, together with their medians and standard deviations, as well as the RMSE, can be seen in Table 7, where the first two columns refer to temperature values and the last two to relative humidity values. Errors in the trends were very low (median absolute error of 0.54 \({}^{\circ}\)C and 3.5% RH, as well as RMSE of 0.68 \({}^{\circ}\)C and 4.5% RH), which confirms that the system performed well in terms of the temperature and relative humidity measurements, which are the most important  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Consumption Type** & **Value** \\ \hline Average current & 7.91 mA \\ \hline Maximum current & 436.21 mA \\ \hline Average current during Deep Sleep & 379.87 \(\mu\)A \\ \hline Average current during activity with communication & 113.42 mA \\ \hline Average current during activity without communication & 77.16 mA \\ \hline Average current during an accelerometer event & 13.18 mA \\ \hline Power consumption & 29.26 mW \\ \hline Energy in a month & 21.07 Wh \\ \hline \hline \end{tabular}
\end{table}
Table 6: Power consumption values of the datalogger.  
parameters for monitoring food quality while being recorded in the cloud. As mentioned above, once the similarity of trends with other dataloggers is verified, the accuracy of the device is determined by the accuracy of its sensors.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Error Type**} & \multicolumn{2}{c}{**Temp. Ref.**} & \multicolumn{2}{c}{**R.H. Ref.**} \\ \cline{2-5}  & **Parkside** & **Tinytag** & **Parkside** & **Tinytag** \\ \hline Maximum absolute error & 1.36 \({}^{\circ}\)C & 1.63 \({}^{\circ}\)C & 7.05\% RH & 11.65\% RH \\ \hline Minimum absolute error & 0.0060 \({}^{\circ}\)C & 0.0249 \({}^{\circ}\)C & 0.0932\% RH & 0.0622\% RH \\ \hline Maximum relative error & 1.88 & 1.26 & 0.33 & 0.51 \\ \hline Minimum relative error & 0.0390 & 0.0212 & 0.0029 & 0.0020 \\ \hline Mean absolute error (MAE) & 0.56 \({}^{\circ}\)C & 0.60 \({}^{\circ}\)C & 3.22\% RH & 4.25\% RH \\ \hline Median absolute error & 0.48 \({}^{\circ}\)C & 0.60 \({}^{\circ}\)C & 3.02\% RH & 3.98\% RH \\ \hline Standard deviation absolute error & 0.40 \({}^{\circ}\)C & 0.28 \({}^{\circ}\)C & 2.12\% RH & 2.92\% RH \\ \hline Mean relative error & 0.81 & 0.46 & 0.13 & 0.19 \\ \hline Median relative error & 0.82 & 0.40 & 0.11 & 0.14 \\ \hline Standard deviation relative error & 0.41 & 0.26 & 0.10 & 0.14 \\ \hline Root mean square error (RMSE) & 0.69 \({}^{\circ}\)C & 0.67 \({}^{\circ}\)C & 3.85\% RH & 5.15\% RH \\ \hline \hline \end{tabular}
\end{table}
Table 7: Absolute, relative and root mean square errors.  
Figure 14: Comparative results of the different dataloggers: (**a**) temperature; (**b**) relative humidity.  
Figure 13: Temperature, relative humidity, CO\({}_{2}\) concentration and battery voltage evolution during the preliminary testing stage inside the refrigerator and freezer.