Modern Urban Environment Research Articles

INFORMATION SYSTEM OF STREET LIGHTING CONTROL IN A SMART CITY

Context. In the context of the rapid development of technologies and the implementation of the concept of smart cities, smart lighting becomes a key element of a sustainable and efficient urban environment. The research covers the analysis of aspects of the use of sensors, intelligent lighting control systems with the help of modern information technologies, in particular such as the Internet of Things. The use of such technologies makes it possible to automate the regulation of lighting intensity depending on external conditions, the movement of people or the time of a day. This contributes to the efficient use of electricity and the reduction of emissions into the atmosphere. Objective. The purpose of the paper is to analyze the procedures for creating an information system as a tool for monitoring and evaluating the level of illumination in a smart city with the aim of improving energy efficiency, safety, comfort and effective lighting management. The implementation of a smart lighting system for Lviv will help improve energy efficiency and community safety. Method. A content analysis of scientific publications was carried out, in which the results of research on the creation of street lighting monitoring systems in real urban environments were presented. The collection and analysis of data on street lighting in the city, such as energy consumption, illumination level, lamp operation schedules, and others, was carried out. Machine learning methods were used to analyze data and predict lighting needs. Using the UML methodology, the conceptual model of the street lighting monitoring information system was developed based on the identified needs and requirements. Results. The role of data processing technologies in creating effective lighting management strategies for optimal use of resources and meeting the needs of citizens is highlighted. The study draws attention to the challenges and opportunities of implementing smart lighting in cities, maximizing the positive impact of smart lighting on modern urban environments. The peculiarities of the development and use of an information system for controlling street lighting in a smart city are analyzed. The potential advantages and limitations of using the developed system are determined. Conclusions. The project on the creation of an information system designed to provide an energy-efficient lighting system in a smart city will contribute to increasing security, particularly, ensuring the safety of the community through integration with security systems, reducing energy consumption, through minimizing the electricity usage in periods when the need for lighting is not necessary. It has been determined that to implement an information system for remote monitoring and lighting control in a smart city, it is advisable to consider the possibility of using a complex lighting control system. Calculations were made on the example of Lviv for the city’s lighting needs. The use of motion sensors to determine the need to turn on lighting was analyzed. A conceptual model of the information system was developed using the object-oriented methodology of the UML notation. The main functionality of the information system is defined.

DSC-Net: Enhancing Blind Road Semantic Segmentation with Visual Sensor Using a Dual-Branch Swin-CNN Architecture.

In modern urban environments, visual sensors are crucial for enhancing the functionality of navigation systems, particularly for devices designed for visually impaired individuals. The high-resolution images captured by these sensors form the basis for understanding the surrounding environment and identifying key landmarks. However, the core challenge in the semantic segmentation of blind roads lies in the effective extraction of global context and edge features. Most existing methods rely on Convolutional Neural Networks (CNNs), whose inherent inductive biases limit their ability to capture global context and accurately detect discontinuous features such as gaps and obstructions in blind roads. To overcome these limitations, we introduce Dual-Branch Swin-CNN Net(DSC-Net), a new method that integrates the global modeling capabilities of the Swin-Transformer with the CNN-based U-Net architecture. This combination allows for the hierarchical extraction of both fine and coarse features. First, the Spatial Blending Module (SBM) mitigates blurring of target information caused by object occlusion to enhance accuracy. The hybrid attention module (HAM), embedded within the Inverted Residual Module (IRM), sharpens the detection of blind road boundaries, while the IRM improves the speed of network processing. In tests on a specialized dataset designed for blind road semantic segmentation in real-world scenarios, our method achieved an impressive mIoU of 97.72%. Additionally, it demonstrated exceptional performance on other public datasets.

Requirements for the modern urban environment: the case of Munich’s Viktualienmarkt food market

ABSTRACT This study considers and analyzes the challenges spurred by the COVID-19 spread in an urban environment under the example of Munich’s Viktualienmarkt food market operation. Its ultimate goal is to propose a comprehensive social distancing model for the German population in terms of food and economic activities under pandemic and post-pandemic conditions. As a result, the paper presented two dedicated models developed under current COVID-related safety measures. The first model was designed for food markets and involved the placement of a distancing grid with portable benches. The second model was designed for public eating facilities and involved the usage of isolated dining booths. The predicted effectiveness of the work of the food market and neighbouring eating facilities under the suggested solutions was investigated using the surveys addressed to the visitors of the studied area. The surveying process reaffirmed the necessity for advancing the development of innovative architectural concepts.

Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey

The integration of machine learning (ML), blockchain, and the Internet of Things (IoT) in smart cities represents a pivotal advancement in urban innovation. This convergence addresses the complexities of modern urban environments by leveraging ML’s data analytics and predictive capabilities to enhance the intelligence of IoT systems, while blockchain provides a secure, decentralized framework that ensures data integrity and trust. The synergy of these technologies not only optimizes urban management but also fortifies security and privacy in increasingly connected cities. This survey explores the transformative potential of ML-driven blockchain-IoT ecosystems in enabling autonomous, resilient, and sustainable smart city infrastructure. It also discusses the challenges such as scalability, privacy, and ethical considerations, and outlines possible applications and future research directions that are critical for advancing smart city initiatives. Understanding these dynamics is essential for realizing the full potential of smart cities, where technology enhances not only efficiency but also urban sustainability and resilience.

Incorporation mechanism of traditional Chinese garden elements in modern urban landscape design: an exploratory analysis based on grounded theory

ABSTRACT Following China’s reform and opening up in 1978, the image of European and American city construction has shaped China’s modern urban environment, but the creation of Chinese cities’ original intrinsic cultural landscape has been neglected. This leads to a break in the inheritance of garden culture in contemporary public and open urban landscape design. This study investigates the process of integrating traditional Chinese gardens into contemporary landscapes using grounded theory. In this study, In Vivo Coding is utilized to conduct a thorough analysis of textual materials through a three-step process: Open Coding, Axial Coding, and Selective Coding saturation test. The identified data are meticulously coded and summarized, culminating in the construction of a theoretical model. The study revealed that the incorporation of traditional Chinese garden elements in contemporary urban landscape design involves several key aspects: firstly, employing the traditional layout and spatial form of the entire design site; secondly, integrating modern public landscape design scenes with traditional garden design concepts to evoke a distinct Chinese ambiance; furthermore, utilizing both modern technology and materials alongside traditional techniques to create multi-dimensional elements within the site. The present study systematically synthesizes and examines the incorporation of traditional Chinese garden elements in contemporary urban design across six dimensions. This research offers a theoretical framework for the preservation of traditional garden culture and its integration into modern landscape, as well as furnishing mechanisms and methodologies for integrating traditional culture into contemporary landscape design practice. This research provides a valuable reference for preserving and practically implementing traditional garden elements in contemporary urban landscapes.

Traditional Regionalism or Modern Minimalism? Unveiling the Psychological Impact of Architectural Styles in Sustainable Urban Planning

Life satisfaction is one of the key indicators of people’s well-being. However, the choice between traditional regionalism and modern minimalism in urban planning remains controversial from a human-centered perspective. Using a sample of 438 respondents from Huangshan City in 2024, we explored the relationships between architectural style, general belongingness, social identity, and life satisfaction through structural equation modeling (SEM). The results indicate significant correlations among the four variables in the model, with general belongingness and social identity acting as mediators in the relationship between architectural style and life satisfaction. Furthermore, residents living in traditional regional architecture scored higher on the scales of general belongingness, social identity, and life satisfaction compared to those living in modern minimalist architecture. These findings provide new insights for urban planning, highlighting the importance of considering the potential psychological and social welfare impacts of architectural styles on residents during the design process. Additionally, they emphasize the value of preserving and promoting traditional regional architecture. This study provides empirical evidence for urban planners and architects, supporting the integration of more human-centered design principles into modern urban environments to enhance residents’ well-being.

Ensuring the stability of deep boilers of high-rise buildings

In today's conditions, the development of underground space can rightly be considered one of the most important and dynamic directions in civil and industrial construction at the worldlevel. In Ukraine, underground construction is important in connection with Russia's aggressive war. Underground and buried structures are most actively built in large cities and megacities. The main reasons for the need to use underground space in cities include the lack of free territories within historically formed buildings and requirements for urban infrastructure development. Today, the underground space is used not onlyfor the placement of engineering communicationsand transport facilities, but also for the construction of public complexes, multi-story underground garages and parking lots, shopping centers, as well asburied parts of residential and office buildings. Structural solutions for underground and buried structures, as well as their construction methods, depend on spatial planning solutions, purpose, depth of laying, engineering-geological, climatic and seismic construction conditions, surface loads, and the proximity of other buildings and buildings. Today, the maximum depth of pits designed inurban conditions usually do not exceed 25-30 m, and the number of underground floors is five to six. Given the growing demand for underground space, especially in densely populated areas, designers and engineers face a number of challengesthat require innovative approaches and modern technologies. This includes the use of the latest methods of geotechnical modeling, the use of highquality materials that ensure the durability and safety of structures, and the implementation of effective water drainage and waterproofing systems. Particular attention should be paid to safety issues during the construction and operation of underground structures, as they may be exposed to natural and man-made factors, such as groundwater, soil movement, and seismic activity. An important aspect is also the provision of comfortable conditions for people using underground facilities, which includes ventilation, lighting and evacuation routes. Scientific research and the experience of international projects demonstrate that the correct use of underground space can significantly increase the efficiency of the use of urban areas, contribute to the steady development of cities and improve the quality of life of their residents. Investments in underground construction are becoming more and more justified in view of the long-term benefits and theneed to adapt to the conditions of the modern urban environment. In general, underground construction is an important direction that has significant potential for development and improvement in the future, responding to the challenges of time and contributing to the development of modern infrastructure.

RESEARCH OF THE IMPACT OF VERNACULAR AREAS ON SUSTAINABLE DEVELOPMENT OF URBAN TERRITORIES

The relevance of the research is stipulated by the need to maximise the involvement of residents in the processes of management and development of the city's territories, which will create a comfortable, convenient and modern urban environment with maximum consideration of the interests and needs of users of the city's infrastructure. The research aims to analyse modern approaches to urban planning, taking into account the needs of the population living in the area, as a component of sustainable development of a modern city, using geoinformation technologies and open geospatial data, such as geotags. These issues are discussed in the context of urban amenities and attractiveness from the point of view of an average resident. To meet the basic needs related to improving the level and comfort of living, it is proposed to divide the territory into vernacular areas. This type of territorial division differs significantly from administrative districts. The research was conducted on the example of a city with a population of over a million people - Kharkiv. The principles of vernacular area formation within the existing urban territory are defined, and the origin of this concept is considered in retrospect. The relationship between vernacular areas and the population mentality through habitus is considered.

CREATION AND USE OF GEOSPATIAL DATA FOR MORPHOMETRIC ANALYSIS OF URBAN DEVELOPMENT USING GEOGRAPHIC INFORMATION TECHNOLOGIES

The modern urban environment requires an integrated approach to management and development that takes into account various aspects of urban development and quality of life. This article discusses the use of geoinformation technologies for the creation and use of a geospatial database in the context of urban development analysis and morphometric indicators. It emphasises the importance of collecting, analysing and using geodata for effective urban planning and development. The article discusses various aspects of the use of geographic information systems in urban planning, including remote sensing for collecting geospatial data, analysis of morphometric indicators of urban development, development of recommendations for improving the urban environment and creation of urban plans based on the analysis of these data. The article highlights the main advantages of using geoinformation technologies in urban planning, such as increased accuracy and speed of data processing, the ability to comprehensively analyse geospatial information and simplify decision-making. The results of the study can be useful for city authorities, architects, planners and other stakeholders involved in the development and management of the urban environment. The use of geoinformation technologies in urban planning can contribute to the sustainable development of cities and improve the quality of life of their residents by making the planning process more efficient and transparent. The role of geoinformation technologies in the creation and use of a geospatial database for the analysis of urban development and morphometric indicators was investigated. In particular, the main aspects of creating a geospatial database, the use of geographic information systems in the collection and processing of geodata, as well as the analysis and application of morphometric indicators in urban planning were considered.

Enhancing secret key distribution through advanced color modulation in visible light communication

Visible light communication (VLC) has emerged as a dynamic area of research poised to revolutionize high-speed wireless communication. VLC technology uses light-emitting diodes (LEDs) within existing infrastructure to emit light within the visible spectrum. VLC complements traditional radio frequency (RF) communications, addressing its inherent limitations and drawbacks. To navigate the demands of modern urban environments, VLC systems must prioritize secure data transmission, accessibility, and economic feasibility, particularly within the framework of smart cities. We introduce what is to our knowledge a novel privacy-enhanced VLC system for optical wireless communication. Leveraging color data modulation techniques and the intricacies of a hyperchaotic three-dimensional map, this innovative approach ensures robust security. By employing diverse LED colors for data transmission and exploiting the unpredictable mathematical properties of hyperchaotic maps, enhanced privacy is achieved. The performance of the proposed system was rigorously evaluated through various tests, manipulating initial control parameters of the encryption process with the hyperchaotic map, as well as adjusting message length and content. Tests were conducted over a 1 m connection distance at a symbol transmission rate of 2 baud. Remarkably, the proposed system demonstrated high accuracy in message recovery, achieving a symbol error rate (SER) of only 0.02 at an incident optical power of 22 µW. We highlight the critical importance of precise decryption parameter values in the proposed method, demonstrating the necessity for accuracy within the range of 10−15 for each decryption parameter; it underscores the indispensability of meticulous parameter calibration to ensure the correct decryption of transmitted symbols. These results pave the way for applications where absolute security is imperative, particularly in smart city environments, such as for key distribution purposes.

A BLOCKCHAIN FRAMEWORK FOR SMART AND CYBER-RESILIENT CITIES

The transition of urban environments into smart cities brings forth unprecedented challenges and vulnerabilities in the face of cyber threats. In response, this study presents a pioneering Blockchain Framework tailored to fortify smart cities against evolving cyber risks. Embracing decentralization and immutability inherent in blockchain technology, the framework addresses the shortcomings of centralized systems, thereby enhancing security and resilience. The primary objective of the framework is to in still trust, mitigate cyber risks, and ensure uninterrupted services within the dynamic urban landscape. By leveraging blockchain's distributed ledger capabilities, the framework establishes a robust foundation for securely managing and validating critical urban data and transactions. Furthermore, its decentralized architecture minimizes single points of failure, reducing the susceptibility of smart city infrastructures to malicious attacks and disruptions. This innovative approach represents a significant stride towards the development of cyber-resilient infrastructures for smart cities, safeguarding against potential threats and vulnerabilities. By fostering trust, bolstering security measures, and promoting continuity of services, the Blockchain Framework serves as a cornerstone in fortifying the resilience of modern urban environments amidst the rapid pace of technological advancement and urbanization. Keywords: Mitigate Cyber Risks , Blockchain Framework , Smart cities , Dynamic urban landscape

Enhancing Emergency Vehicle Detection: A Deep Learning Approach with Multimodal Fusion

Emergency vehicle detection plays a critical role in ensuring timely responses and reducing accidents in modern urban environments. However, traditional methods that rely solely on visual cues face challenges, particularly in adverse conditions. The objective of this research is to enhance emergency vehicle detection by leveraging the synergies between acoustic and visual information. By incorporating advanced deep learning techniques for both acoustic and visual data, our aim is to significantly improve the accuracy and response times. To achieve this goal, we developed an attention-based temporal spectrum network (ATSN) with an attention mechanism specifically designed for ambulance siren sound detection. In parallel, we enhanced visual detection tasks by implementing a Multi-Level Spatial Fusion YOLO (MLSF-YOLO) architecture. To combine the acoustic and visual information effectively, we employed a stacking ensemble learning technique, creating a robust framework for emergency vehicle detection. This approach capitalizes on the strengths of both modalities, allowing for a comprehensive analysis that surpasses existing methods. Through our research, we achieved remarkable results, including a misdetection rate of only 3.81% and an accuracy of 96.19% when applied to visual data containing emergency vehicles. These findings represent significant progress in real-world applications, demonstrating the effectiveness of our approach in improving emergency vehicle detection systems.

Experiences of living with overweight/obesity and early type 2 diabetes in Singapore—a qualitative interview study

ObjectivesTo understand the lived experience of adults with overweight/obesity and early type 2 diabetes in a modern urban environment, and the interrelations among the various aspects of these experiences and...

Enhanced Surveillance: Developing a Computer Vision-based CCTV Footage Analysis Tool for Improved Vehicle Number Plate Recognition

Abstract: Smart parking systems serve as integral components in augmenting the efficiency and sustainability of modern urban environments. Nonetheless, prevailing systems predominantly rely on sensors to monitor parking space occupancy, entailing substantial installation and maintenance costs while offering limited functionality in tracking vehicle movement within parking lots. To confront these challenges head-on, our solution introduces a multistage learning-based approach, capitalizing on the existing surveillance infrastructure within parking facilities and a meticulously curated dataset of Saudi license plates. Our approach amalgamates YOLOv5 for license plate detection, YOLOv8 for character detection, and a novel convolutional neural network architecture tailored for enhanced character recognition. We illustrate the superiority of our approach over single-stage methods, achieving an impressive overall accuracy of 96.1%, a notable advancement from the 83.9% accuracy of single-stage approaches. Furthermore, our solution seamlessly integrates into a web-based dashboard, facilitating real-time visualization and statistical analysis of parking space occupancy and vehicle movement, all accomplished with commendable time efficiency. This endeavor underscores the potential of leveraging existing technological resources to bolster the operational efficiency and environmental sustainability of smart cities. By harnessing the power of machine learning and computer vision, our work exemplifies a paradigm shift towards smarter and more adaptive urban infrastructure

The ways to improve the facade architecture of 1970s typical residential buildings

A significant part of the 1970s housing stock of large cities of the Russian Federation is in need of renovation. However, there is no renovation programme for the 9-storey panel housing stock, unlike the 5-storey housing stock, which is now being developed in Moscow. It is proposed to solve the problem of modernisation of facades of typical residential buildings without resettlement of tenants by minimal architectural means, which can contribute to the formation of a favourable modern urban environment in these old quarters. Possible solutions are offered on the basis of modern and historical world experience in panel house-building.

The design of small architectural forms in the development of urban spaces based on Komi culture

The article examines a modern direction in the development of public spaces that includes the cultural code of the region and cultural identity in modern urban environment design. This is an important issue considering academic urban space projects in the educational process and work with urban communities. The article demonstrates a case of design pattern implementation based on Komi culture in relation to small architectural forms for the public space «Playground under the Clock» in Syktyvkar.

Urbo-ecological characteristics of the formation of green architecture in the conditions of sustainable development

The article defines the main problems and prospects for the development of the concept of “green” architecture in the context of sustainable development. In the process of identifying the main problem, the relevance of the research was determined. Having conducted a thorough analysis of the current state of green architecture formation in the conditions of sustainable development, it was found that green architecture is multi-vector and includes energy-efficient, ecological and economic aspects, while the impact on the environment is minimal. The main trends in the development of "green" architecture were identified, which gave the opportunity to apply their role in the formation of a modern urban environment in terms of increasing the energy efficiency of buildings, the use of solar energy, "green" technologies and the latest materials. Based on the conducted research, the main principles of "green" architecture were defined: the principle of energy efficiency manifests itself in such design and construction, in which heat consumption, both for heating and for cooling, is reduced to a minimum; the principle of sound orientation using solar energy as the main source of light and heat; the principle of inclusiveness, where the urban environment is designed for the comfortable stay of people from all walks of life; the principle of environmental friendliness includes a harmonious combination of the urbanized and natural environment; the principle of autonomy represents the possibility of architectural and urban planning objects to function autonomously in critical situations.

Enhancing Urban Data Analysis: Leveraging Graph-Based Convolutional Neural Networks for a Visual Semantic Decision Support System.

The persistent increase in the magnitude of urban data, combined with the broad range of sensors from which it derives in modern urban environments, poses issues including data integration, visualization, and optimal utilization. The successful selection of suitable locations for predetermined commercial activities and public utility services or the reuse of existing infrastructure arise as urban planning challenges to be addressed with the aid of the aforementioned data. In our previous work, we have integrated a multitude of publicly available real-world urban data in a visual semantic decision support environment, encompassing map-based data visualization with a visual query interface, while employing and comparing several classifiers for the selection of appropriate locations for establishing parking facilities. In the current work, we challenge the best representative of the previous approach, i.e., random forests, with convolutional neural networks (CNNs) in combination with a graph-based representation of the urban input data, relying on the same dataset to ensure comparability of the results. This approach has been inspired by the inherent visual nature of urban data and the increased capability of CNNs to classify image-based data. The experimental results reveal an improvement in several performance indices, implying a promising potential for this specific combination in decision support for urban planning problems.

Advanced Smart Grid Architecture for Sustainable Energy Integration in Modern Urban Environments

Advanced Smart Grid Architecture for Sustainable Energy Integration in Modern Urban Environments

E-Challan Based Intelligent Assistance System for Smart City

Traffic management and enforcement of road safety regulations have become increasingly crucial in modern urban environments, as the number of vehicles on the roads continues to surge. With the rise in traffic violations, particularly signal disobedience, there is a pressing need for innovative solutions that can efficiently detect and penalize offenders while reducing the burden on law enforcement personnel. The E-Challan System harnesses the power of cutting-edge computer vision techniques, most notably Automatic Number Plate Recognition (ANPR), to accurately capture and decipher vehicle number plates in real- time. High-resolution cameras strategically positioned at traffic junctions and signal intersections actively monitor passing vehicles, automatically detecting those that violate traffic signals. Upon successful identification of a signal violation, the E-Challan System promptly generates an electronic challan, or e-challan, containing detailed information about the violation, such as the date, time, and location of the incident. This comprehensive documentation serves as indisputable evidence of the offense and provides an essential legal foundation for imposing fines on violators. with an Auto Debit Fine mechanism.