Road discrepancies such as potholes and road cracks are often present in our day-to-day commuting and travel. The cost of damage repairs caused by potholes has always been a concern for owners of any type of vehicle. Thus, an early detection processes can contribute to the swift response of road maintenance services and the prevention of pothole related accidents. In this paper, automatic detection of potholes is performed using the computer vision model library, You Look Only Once version 3, also known as Yolo v3. Light and weather during driving naturally affect our ability to observe road damage. Such adverse conditions also negatively influence the performance of visual object detectors. The aim of this work was to examine the effect adverse conditions have on pothole detection. The basic design of this study is therefore composed of two main parts: (1) dataset creation and data processing, and (2) dataset experiments using Yolo v3. Additionally, Sparse R-CNN was incorporated into our experiments. For this purpose, a dataset consisting of subsets of images recorded under different light and weather was developed. To the best of our knowledge, there exists no detailed analysis of pothole detection performance under adverse conditions. Despite the existence of newer libraries, Yolo v3 is still a competitive architecture that provides good results with lower hardware requirements.

Potholes pose a significant problem for road safety and infrastructure. They can cause damage to vehicles and present a risk to pedestrians and cyclists. The ability to detect potholes in real time and with a high level of accuracy, especially under different lighting conditions, is crucial for the safety of road transport participants and the timely repair of these hazards. With the increasing availability of cameras on vehicles and smartphones, there is a growing interest in using computer vision techniques for this task. Convolutional neural networks (CNNs) have shown great potential for object detection tasks, including pothole detection. This study provides an overview of computer vision algorithms used for pothole detection. Experimental results are then used to evaluate the performance of the latest CNN-based models for pothole detection in different real-world road conditions, including rain, sunset, evening, and night, as well as clean conditions. The models evaluated in this study include both conventional and the newest architectures from the region-based CNN (R-CNN) and You Only Look Once (YOLO) families. The YOLO models demonstrated a faster detection response and higher accuracy in detecting potholes under clear, rain, sunset, and evening conditions. R-CNN models, on the other hand, performed better in the worse-visibility conditions at night. This study provides valuable insights into the performance of different CNN models for pothole detection in real road conditions and may assist in the selection of the most appropriate model for a specific application.

The aim of this article is to describe estimates of data difficulty and aspects of the data viewpoint within Vehicle-to-Infrastructure (V2I) communication in the Smart Mobility concept. The historical development of the database system’s architecture, that stores and processes a larger amount of data, is currently sufficient and effective for the needs of today’s society. The goal of vehicle manufacturers is the continual increase in driving comfort and the use of multiple sensors to sense the vehicle’s surroundings, as well as to help the driver in critical situations avoid danger. The increasing number of sensors is directly related to the amount of data generated by the vehicle. In the automotive industry, it is crucial that autonomous vehicles can process data in real time or can locate itself in precise accuracy, for the decision-making process. To meet these requirements, we will describe HD maps as a key segment of autonomous control. It alerts the reader to the need to address the issue of real-time Big Data processing, which represents an important role in the concept of Smart Mobility.

Public trust is essential for credible and consistent state security policy, defense operations, and communications. In the twenty-first century, the social context of security has expanded significantly, necessitating that society acquire credible and up-to-date security knowledge. This article examines the relationship between the UN Sustainable Development Goals (SDGs) and national security actors within the rule-of-law framework, focusing on how the trust factor influences goal fulfilment. The study uses a normative analysis of sustainable development goals, emphasizing the social pillar and its connections to national security institutions. It highlights the importance of continuous, trust-based communication between the public and social partners, reflecting transparency and accountability. The integration of sustainability into national security strategies—particularly concerning climate change and energy security—is explored through the strategies of NATO member states. The article also discusses the mutual reinforcement between social stability, economic stability, and national security, emphasizing that achieving the SDGs enhances national security, and vice versa. This comprehensive approach fosters effective, long-term solutions by integrating the SDGs into the national security framework, ultimately promoting social trust and stability.

Для авторитетной и последовательной политики государственной безопасности, обороны и связи с общественностью необходимо общественное доверие. В XXI веке социальный контекст безопасности заметно расширился, что обусловило необходимость достоверных и актуальных знаний о безопасности для общества. В статье рассмотрена взаимосвязь целей устойчивого развития ООН и субъектов национальной безопасности в условиях верховенства права, при особом внимании к важности доверия для достижения этих целей. В исследовании использован нормативный анализ целей устойчивого развития, с акцентом на социальную составляющую и её связь с институтами национальной безопасности. Отмечена важность постоянного доверительного взаимодействия общества с социальными партнёрами, при условии прозрачности и подотчётности. Включение принципов устойчивого развития в стратегии национальной безопасности, особенно для изменений климата и энергетической безопасности, изучено на примере стратегий стран НАТО. В статье также показана взаимосвязь и взаимозависимость социальной стабильности, экономической стабильности и национальной безопасности, и отмечено, что достижение целей устойчивого развития укрепляет национальную безопасность, и наоборот. Такой комплексный подход ведёт к эффективным, долгосрочным решениям на основе включения целей устойчивого развития в систему национальной безопасности, в конечном счёте способствуя доверию и стабильности в обществе.