# Temporal Variations Dataset for Indoor Environmental Parameters in Northern Saudi Arabia
## 4 Dataset Description  
In this research, we generated a comprehensive dataset tailored for classification problems. The dataset comprises 31 individual files, each corresponding to a day in July 2022. To preserve the privacy of the data and people, several measures were taken while gathering data, which included anonymization of the data. There was no need to obtain informed consent from the participants since it was in one of the author's homes and followed data minimization principles. These steps were taken to comply with General Data Protection Regulation (GDPR) [58] and local data protection laws [59]. To maintain consistency and ensure the relevance of the data, each file contains approximately 288 records, representing data collected over 24 h. The chosen sensors in the data acquisition system were programmed to capture data every 5 min. This sampling rate was determined through a thorough dataset analysis, revealing that most significant changes in the critical variables occur over extended periods. The 5 min intervals were sufficient for capturing relevant and meaningful data without overloading the system or generating excessive storage requirements. Once the data was collected, we combined all 31 files into a single, consolidated dataset containing 8910 records. This comprehensive dataset comprises six columns, each representing a different data type: time, integer, and decimal values. Including multiple data types allow for a more robust and versatile dataset that can be utilized across various classification problems. Table 3 in the research paper presents a dataset sample, showcasing several records and their respective values across the six columns. This table offers a snapshot of the data's structure and format, clearly representing the information collected during the research. The standard range for temperature in the office room was between 29.3 \({}^{\circ}\)C and 40.2 \({}^{\circ}\)C, while relative humidity ranged from 10% to 25%. To ensure the accuracy and reliability of the data, the temperature and humidity sensors were calibrated with precision. The calibration process and its results are depicted in Figure 4, providing a clear understanding of the sensor's performance and measurement capabilities. The data highlights the fluctuating nature of these physical variables and the impact of external factors such as air conditioning, providing valuable insights for further analysis and optimization of office environments. The pressure variable averaged 89,448, and the altitude feature averaged 1039. The measurements were conducted in an office room, where the light is sometimes turned off, so the minimum degree of change in the sensor is zero. In contrast, the light sensor data collected during this research provided valuable insights into the illumination conditions within the monitored environment. The sensor used in this study could measure light intensity within a range of 0 to 820 lux. This range effectively captures various lighting conditions, from complete darkness to bright indoor lighting scenarios. Throughout data collection, the light sensor recorded illumination levels at regular intervals, enabling us to analyze fluctuations and trends in the lighting conditions. By examining these data points, we could identify periods of low and high illumination, which may correspond to different times of the day, occupancy patterns, or changes in the natural light entering the space. The light sensor data also allowed us to investigate potential correlations between illumination levels and other variables, such as temperature and humidity. For instance, we could examine whether increased light intensity leads to a rise in temperature or a change in humidity levels. This information can be crucial in understanding indoor environmental quality and implementing appropriate control strategies for lighting and HVAC systems. Furthermore, the light sensor data can be used to assess the effectiveness of existing lighting systems and inform the design of new or improved systems.