This paper examines the environmental conditions of two high-traffic streets in a northern latitude located city with a population of 250,000 using a multisensory electronic device controlled by an Internet of Things platform. Measurement data from April to October 2024 was analyzed. A noise level dataset was compiled with a frequency of one measurement every 15 min. The identified changes in noise levels at different times of day in the analyzed months are presented. Significant noise levels were identified and processed statistically in the R programming environment using basic functions by comparing two independent samples. The reliability of differences in statistical indicators was assessed using the Shapiro-Wilks and Fisher tests. The arithmetic means were determined using the Student’s t-test and the Student’s t-test with Welch’s correction. The Wilcoxon-Mann–Whitney test was applied to cases where the sample deviated from normality. The resulting Boxplot diagrams are presented, allowing for comparison of the distributions of values from different samples. The “Smart Ecosystems” hardware and software system has been developed and tested to identify the times of significant peak noise impacts. The research findings contribute to the development of environmental monitoring tools and a scientifically based approach to managing the acoustic environment of modern cities.