The current paper describes a complex measurement system of the vehicle emissions which is based on electrochemical sensors for nitrogen oxides (NOx), carbon monoxide (CO) and sulfur dioxide (SO 2 ), photoionization detector (PID) for measurement of the volatile organic compounds (VOCs) levels and particulate matter (PM) sensor. The measurement data are displayed on an intelligent HMI LCD/TFT display with UART interface and capacitive touch screen and are written on SD card. Simultaneously all data are transferred to a remote server via GSM/GPRS modem or Bluetooth connection for real-time analysis.

This paper presents a thermographic analysis of a street junction within an urban road network, focusing on identifying thermal load sources generated by vehicle traffic—an increasingly significant environmental concern for urban populations. The study explores the application of thermographic methods at urban intersections and the creation of thermal maps. These approaches support the advancement of intelligent transport systems, aligning with smart city initiatives aimed at optimizing traffic flow management. Additionally, the findings provide potential for assessing the conditions of both road transport infrastructure and vehicles. By adopting this comprehensive perspective for monitoring urban environments and transportation systems, cities can enhance overall quality of life and public well-being. The results emphasize the value of conducting broad-scope studies, suggesting that combining ground-based and aerial thermal imaging leads to more informed decision-making. Doi: 10.28991/CEJ-2025-011-05-02 Full Text: PDF

This article focuses on the topic of using unmanned aerial vehicles and modern software solutions and systems in the study of pastures, using aerial photography and aerial photogrammetry.

The present study considers the possibility of developing an integrated system for monitoring the basic parameters of the braking system of cars in operation during the braking process. The main parameters determining the braking efficiency of cars are the temperature of the brake system elements and the brake fluid pressure. Experimental studies and developments have been carried out to determine the temperature of the car's brake discs during braking.

This study is a continuation of our study on grassland survey using aerial photography, focusing here on a multi-point survey using distributed thermographic sensors and performing area-of-interest scanning in order to collect a large database, enable statistical processing and monitoring of the state and parameters of pastures.

The degradation of pastures and meadows is a global problem with a wide range of impacts. It affects farmers in different ways, such as decreases in cattle production, milk yield, and forage quality. Still, it also has other side effects, such as loss of biodiversity, loss of resources, etc. In this study, the degradation of a semi-natural pasture near the village of Obichnik, Bulgaria, was evaluated using machine learning algorithms, and an unmanned aerial vehicle (UAV) obtained visual spectrum images. A high-quality (HQ) orthomosaic of the area was created and numerous regions of interest were manually marked for training and validation purposes. Three machine learning algorithms were used—Maximum likelihood, Random trees (RT), and Support Vector Machine (SVM). Furthermore, object-based and pixel-based approaches were utilized. The obtained results indicate that the object-based RT and SVM models provide significantly better accuracy, with their Cohen’s Kappa reaching 0.86 and 0.82, respectively. The performed classification showed that approximately 61% of the investigated pasture area is covered with grass, which indicates light-to-medium degradation.