## 4 Results
### Data Profiling  
Data profiling is a crucial step in the development of a multi-sensor device as it ensures the quality, consistency, calibration, and reliability of the collected data. By thoroughly examining the datasets, we can identify and address issues such as missing values, data anomalies, and formatting inconsistencies, which could otherwise compromise the accuracy of the device's outputs. Profiling also supports understanding the data's underlying patterns, enabling better calibration of sensors and more informed decision making during subsequent analysis. Ultimately, this process lays the foundation for building a robust multi-sensor system, essential for delivering precise, accurate, and actionable insights. Table 4 presents data profiling of the collected data from the developed multi-sensor device. \begin{table}
\begin{tabular}{l c} \hline \hline Sensor: SI7021 & Measure: Temperature \\ \hline Missing values & 15.1\% \\ Mean & 21.97 \({}^{\circ}\)C \\ Standard deviation & 6.99 \({}^{\circ}\)C \\ Minimum & 5.0 \({}^{\circ}\)C \\ Median & 21.0 \({}^{\circ}\)C \\ Maximum & 46.0 \({}^{\circ}\)C \\ \hline Sensor: SI7021 & Measure: Humidity \\ \hline Missing values & 14.5\% \\ Mean & 63.26\% \\ Standard deviation & 8.45\% \\ Minimum & 35.0\% \\ Median & 64.0\% \\ Maximum & 99.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Profiling the collected data from the developed multi-sensor device. Figure 2: (**a**) General view of the multi-sensory system; (**b**) an inside look after a year of operation in a real environment of the barn. \begin{table}
\begin{tabular}{l c} \hline \hline Sensor: SJ7021 & Measure: Dew point \\ Missing values & 14.5\% \\ Mean & 15.44 \({}^{\circ}\)C \\ Standard deviation & 5.28 \({}^{\circ}\)C \\ Minimum & \(-\)1.0 \({}^{\circ}\)C \\ Median & 16.0 \({}^{\circ}\)C \\ Maximum & 32.0 \({}^{\circ}\)C \\ \hline Sensor: SDS0X1 & Measure: PM2.5 \\ \hline Missing values & 14.5\% \\ Mean & 6.18 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Standard deviation & 5.98 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Minimum & 0.0 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Median & 5.00 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Maximum & 128.0 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ \hline Sensor: SDS0X1 & Measure: PM10 \\ \hline Missing values & 14.5\% \\ Mean & 13.45 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Standard deviation & 13.12 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Minimum & 1.0 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Median & 10.0 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ Maximum & 348.0 \(\mathrm{\SIUnitSymbolMicro g}\mathrm{/}\mathrm{m}^{3}\) \\ \hline Sensor: CCS811 & Measure: TVOC \\ \hline Missing values & 14.5\% \\ Mean & 981.0 ppb \\ Standard deviation & 1230.36 ppb \\ Minimum & 0.0 ppb \\ Median & 529.0 ppb \\ Maximum & 29,206.0 ppb \\ \hline Sensor: CCS811 & Measure: eCO\({}_{2}\) \\ \hline Missing values & 14.5\% \\ Mean & 1902.74 ppm \\ Standard deviation & 813.67 ppm \\ Minimum & 400.0 ppm \\ Median & 1856.0 ppm \\ Maximum & 32,768.0 ppm \\ \hline Sensor: ADS1115 & Measure: \(\mathrm{NH}_{3}\) \\ \hline Missing values & 14.5\% \\ Mean & 17,815.0 \\ Standard deviation & 1271.61 \\ Minimum & 9618 \\ Median & 17,853 \\ Maximum & 19,877 \\ \hline Sensor: ADS1115 & Measure: \(\mathrm{H}_{2}\mathrm{S}\) \\ \hline Missing values & 14.5\% \\ Mean & 15,376.38 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: _Cont._The data collected from various sensors provide valuable insights into the conditions in the barn monitored over time. Some missing data were observed because, during the operation of the multi-sensor module, interruptions occurred due to communication breaks in data transmission, primarily caused by power outages related to weather disturbances such as storms. However, once communication was restored, data collection resumed seamlessly.