## 2 Materials and Methods
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Air Quality Parameters** & \multicolumn{2}{c}{**Sources**} & \multicolumn{2}{c}{**Health Effects**} & **Regulatory Limits** \\ \hline Carbon Monoxide (CO) & \(\bullet\) & Combustion Processes: & \(\bullet\) & Headaches, Dizziness, Nausea: \\  & Vehicle engines, industrial combustion. & \(\bullet\) & Symptoms of low to moderate exposure. & \\ Carbon Monoxide (CO) & \(\bullet\) & Wildfires: Natural sources contribute during wildfires. & \(\bullet\) & Impaired Cognitive Function: \\  & \(\bullet\) & Tobacco Smoke: A significant indoor source. & \(\bullet\) & High concentrations can lead to more severe effects. & Stringent limits to minimize the risk of adverse health effects. \\ \hline \hline \end{tabular}
\begin{tabular}{c c c c} \hline \hline \multirow{4}{*}{Particulate Matter (PM2.5)} & \(\bullet\) & Combustion: Vehicle exhaust, industrial processes. & \(\bullet\) & Respiratory Issues: Asthma, bronchitis, cardiovascular problems. & \\  & \(\bullet\) & Natural Sources: Dust storms, wildfires. & \(\bullet\) & Premature Death: Long-term exposure associated with increased mortality. & Strict standards to protect public health. \\ \hline \hline \multirow{4}{*}{Total Volatile Organic Compounds (TVOC)} & \(\bullet\) & Industrial Processes: Paints, solvents, manufacturing. & \(\bullet\) & Eye, Nose, and Throat \\  & \(\bullet\) & Combustion: Vehicle emissions. & \(\bullet\) & Irritation: Common symptoms of exposure. & \\  & \(\bullet\) & Building Materials: Some materials release VOCs. & \(\bullet\) & Headaches, Dizziness: Short-term effects. & Standards Vary: Different compounds may have \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._DIP: High-level modules, such as data processing and storage components, do not depend on low-level modules. Instead, both depend on abstractions. This approach allows flexible integration of different sensors and data transmission methods, which allows us to have the possibility to work with different types of sensors and provide the data in real-time. The standard principles of SOLID are upgraded according to the specific purpose of the system--animal barn. For this reason, additional architectural techniques are used such as the following:  
* Data processing and storage techniques where the data processing and storage architecture follows a layered approach. * Local processing: Raspberry Pi running OpenHAB collects and processes data locally, providing immediate responses and control functions. * Long-term storage: Another Raspberry Pi configured as an SQL server stores historical data and retrieves data every few seconds, allowing easy deployment of machine learning models to assess, classify, and predict air quality, air pollutants, and consequences. Additionally, this dual storage approach applies in the event of an internet connection outage or other event, the data are stored locally, and when the connection is restored, it is sent to the cloud. * Cloud integration: Data are also transmitted to the My OpenHAB cloud, allowing remote access and monitoring through a unified user interface. It also allows remote control of the entire system and activation of additional functionalities. What is more, the system supports automation rules that trigger responses to specific air quality conditions, improving its functionality and user experience. * Data validation and calibration are precisely applied where each sensor undergoes rigorous calibration to ensure accuracy. Validation experiments are conducted to verify the reliability of the collected data, ensuring that the system performance meets the required standards. The calibration considers the height and width of the barn, and the height of the place where the device is placed (distance from water facilities, fans, windows, doors--entrance--exit and places for feeding and cleaning animals).