# Temporal Variations Dataset for Indoor Environmental Parameters in Northern Saudi Arabia
## 4 Dataset Description
By analyzing the data, we can determine if the current lighting system provides adequate illumination throughout the space or if there are areas that experience excessive brightness or darkness. This information can be vital in optimizing lighting systems to reduce energy consumption and improve occupant comfort. In summary, the light sensor data collected within a range of 0 to 820 lux provided a comprehensive understanding of the illumination conditions in  
Figure 4: Collected data visualization. the monitored environment. This information is essential for assessing the performance of lighting systems, identifying correlations between lighting conditions and other environmental variables, and informing the design and optimization of energy-efficient and comfortable indoor spaces. In this study, we also collected data from altitude and pressure sensors to understand the monitored area's environmental conditions better. The altitude sensor data provided 1020 to 1040 m above sea level measurements, while the pressure sensor data ranged from 89,450 to 89,650 Pascals. Analyzing these data points enables us to draw correlations between altitude and atmospheric pressure changes, offering valuable insights into environmental dynamics. The altitude sensor utilized in our data acquisition system offered accurate elevation readings, capturing fluctuations in the monitored area's altitude over the data collection period. The recorded altitude range of 1020 to 1040 m provides a comprehensive representation of the vertical shifts in the environment, which can be further analyzed for potential impacts on other variables or phenomena. Simultaneously, the pressure sensor measured atmospheric pressure with high precision, capturing values from 89,450 to 89,650 Pascals. Atmospheric pressure is a critical variable influencing various environmental aspects, such as weather patterns and air quality. By examining the pressure sensor data, we can gain insights into potential correlations between changes in atmospheric pressure and other environmental parameters, further enriching our dataset and analysis. The combined analysis of altitude and pressure sensor data offers a complete understanding of the environmental conditions in the monitored area. By identifying trends and relationships between altitude, atmospheric pressure, and other physical variables, we can develop a comprehensive picture of the environmental dynamics at play, enabling more informed decision-making and potentially uncovering new avenues for optimization and improvement. Therefore, our data collection efforts encompassed altitude and pressure sensor data, providing a holistic view of the environmental conditions in the monitored area. By analyzing these data points and exploring the relationships between altitude, atmospheric pressure, and other environmental variables, we can glean valuable insights and improve our understanding of the complex interactions at play in the natural environment. The sensor data distribution offers valuable insights into the patterns and variations observed in the collected readings within the specified range. By analyzing this distribution, we can better understand the temperature dynamics within the monitored environment and assess the performance of the sensor data. To visualize the data distribution, we can use a histogram, which divides the data into bins representing intervals and plots the frequency of readings within each interval. This graphical representation provides a clear overview of the distribution's shape, central tendency, and dispersion. Upon examination of the sensors' data distribution, several key observations can be made:  
* Central Tendency: By evaluating the mean, median, and mode of the dataset, we can determine the central tendency of the temperature readings. This provides insight into the typical or \"average\" temperature observed within the monitored environment.