Search

This paper presents a concept of the air quality monitoring system design and describes a selection of data quality analysis methods. A high level of industrialisation affects the risk of natural disasters related to environmental pollution such as e.g. air pollution by gases and clouds of dust (carbon monoxide, sulphur oxides, nitrogen oxides). That is why researches related to the monitoring this type of phenomena are extremely important. Low-cost air quality sensors are more commonly used to monitor air parameters in urban areas. These types of sensors are used to obtain an image of the spatiotemporal variability in the concentration of air pollutants. Aside from their low price , which is important from a point of view of the economic accessibility of society, low-cost sensors are prone to produce erroneous results compared to professional air quality monitors. The described study focuses on the analysis of outliers as particularly interesting for further analysis, as well as modelling with machine learning methods for air quality assessment in the city of Lublin.

This article aims to show the possible energy savings in intelligent building installations due to the use of programmable mechanical multifunctional buttons. Two monostable buttons were placed, the pressing of which triggered the entire sequence of programmed actions and procedures. The consumption of electricity from the period before and after the assembly of the buttons was compared. The measured effects of using the buttons have shown that the energy consumption has decreased by approximately 7.5 kWh per month. The low installation costs and benefits resulting from the use of such a solution make it a cost-effective and a very convenient solution.