The main goal of this paper is to present new possibilities for the detection and recognition of different categories of electric and conventional (equipped with combustion engines) vehicles using a thermal video camera. The paper presents a draft of a possible detection and classification system of vehicle propulsion systems working with thermal analyses. The differences in thermal features of different vehicle categories were found out and statistically proved. The thermal images were obtained using an infrared thermography camera. They were utilized to design a database of vehicle class images of passenger vehicles (PVs), vans, and buses. The results confirmed the hypothesis that infrared thermography might be used for categorizing the vehicle type according to the thermal features of vehicle exteriors and machine learning methods for vehicle type recognition.
Smart and automated maintenance could make the system and its parts more sustainable by extending their lifecycle, failure detection, smart control of the equipment, and precise detection and reaction to unexpected circumstances. This article focuses on the analysis of data, particularly on logs captured in several Czech tunnel systems. The objective of the analysis is to find useful information in the logs for predicting upcoming situations, and furthermore, to check the possibilities of predictive diagnostics and to design the process of predictive maintenance. The main goal of the article is to summarize the possibilities of optimizing system maintenance that are based on data analysis as well as expert analysis based on the experience with the equipment in the tunnel. The results, findings, and conclusions could primarily be used in the tunnels; secondarily, these principles could be applied in telematics and lead to the optimization and improvement of system sustainability.
Many smart city applications work with calculated position and time using the Global Navigation Satellite System (GNSS) signals for enhanced precision. However, there are many places where the availability of GNSS is limited, e.g., road tunnels, which are an essential part of transport infrastructure. Tunnels also require greater attention and greater importance of approaches to ensure the safety and security aspects of traffic. The safety, distribution of information, awareness, and smooth traffic can also be ensured by V2X applications, but the current position is also needed. An experimental analysis of data connection and communication availability was performed in the Blanka tunnel (Prague) and its surroundings. The main objective of the work was to find and clearly describe the tunnel blind spots, with an emphasis on communication between cars and potentially between cars and infrastructure. This article summarizes the evaluation results of the V2X tunnel experimental test, the outputs from the analysis of these blind spots, and it provides a future perspective and suggestions that make tunnels smart by using advanced positioning approaches.
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