Shipping activities, oil production and transport in the sea, oil handled in harbors, construction and exploitation of offshore oil and gas pipelines have a number of negative impacts on the marine environment and coastal zone of the seas. In 2004-2014 we elaborated several operational satellite monitoring systems for oil and gas companies in Russia and performed integrated satellite monitoring of the ecological state of coastal waters in the Baltic, Black, Caspian, and Kara seas, which included observation of oil pollution, suspended matter, and algae bloom at a fully operational mode. These monitoring systems differ from the existing ones by the analysis of a wide spectrum of satellite, meteorological and oceanographic data, as well as by a numerical modeling of oil spill transformation and transport in real weather conditions. Our experience in the Baltic Sea includes: (1) integrated satellite monitoring of oil production at the LUKOIL-KMN Ltd. D-6 oil rig in the Southeastern Baltic Sea (Kravtsovskoe oil field) in 2004-2014; (2) integrated satellite monitoring of the “Nord Stream” underwater gas pipeline construction and exploitation in the Gulf of Finland (2010-2013); (3) numerical modeling of risks of oil pollution caused by shipping along the main maritime shipping routes in the Gulf of Finland, the Baltic Proper, and in the Southeastern Baltic Sea; (4) numerical modeling of risks of oil pollution caused by oil production at D-6 oil rig and oil transportation on shore via the connecting underwater oil pipeline.

Communication network structure for V2G systems is considered on the bases of ISO/IEC 15118 standard. If WPT technology is used and vehicles are in motion wireless data transfer network must present and restrictions for data packets delivery exist. We analyze requirements of compensation process for WPT-V2G network. For standard wireless technologies 802.11 the estimations of delays of packets are made. Analytical and simulation model for packets delay estimations is proposed. The specifications for physical layer IEEE 802.11 a/b/g/n are under consideration. The data from the models are compared with field experiments.

The paper is devoted to using ground penetrating radar (GPR) for the detection of tree roots in an urban area, since GPR allow detect the hidden objects in non invasive way. It is necessary exactly to know the growth direction, thickness and depth of the roots of the tree to confidently assert about the tree root influence on the technical condition of engineering objects and structures: of the buildings, of pavements, of roadway, of engineering communications and etc. The aim of the given research was experimentally to evaluation the possibilities of detection of tree roots in an urban area with the use of GPR on frequency 400 MHz and of algorithms of secondary processing of GPR signals. Results of interpretation of radar profile and evacuation of soil around tree show the possibility of detection of the tree roots and the determination of their parameters using one or two radar concentric profiles.

Smart safety helmets equipped with vision systems are emerging as powerful tools for industrial infrastructure inspection. This paper presents a comprehensive state-of-the-art review of such VSLAM-enabled (Visual Simultaneous Localization and Mapping) helmets. We surveyed the evolution from basic helmet cameras to intelligent, sensor-fused inspection platforms, highlighting how modern helmets leverage real-time visual SLAM algorithms to map environments and assist inspectors. A systematic literature search was conducted targeting high-impact journals, patents, and industry reports. We classify helmet-integrated camera systems into monocular, stereo, and omnidirectional types and compare their capabilities for infrastructure inspection. We examine core VSLAM algorithms (feature-based, direct, hybrid, and deep-learning-enhanced) and discuss their adaptation to wearable platforms. Multi-sensor fusion approaches integrating inertial, LiDAR, and GNSS data are reviewed, along with edge/cloud processing architectures enabling real-time performance. This paper compiles numerous industrial use cases, from bridges and tunnels to plants and power facilities, demonstrating significant improvements in inspection efficiency, data quality, and worker safety. Key challenges are analyzed, including technical hurdles (battery life, processing limits, and harsh environments), human factors (ergonomics, training, and cognitive load), and regulatory issues (safety certification and data privacy). We also identify emerging trends, such as semantic SLAM, AI-driven defect recognition, hardware miniaturization, and collaborative multi-helmet systems. This review finds that VSLAM-equipped smart helmets offer a transformative approach to infrastructure inspection, enabling real-time mapping, augmented awareness, and safer workflows. We conclude by highlighting current research gaps, notably in standardizing systems and integrating with asset management, and provide recommendations for industry adoption and future research directions.