City Infrastructure Research Articles

Energy Modeling for Electric Vehicles Based on Real Driving Cycles: An Artificial Intelligence Approach for Microscale Analyses

This paper presents the process of creating a model for electric vehicle (EV) energy consumption, enabling the rapid generation of results and the creation of energy maps. The most robust validation indicators were exhibited by an artificial intelligence method, specifically neural networks. Within this framework, two predictive models for EV energy consumption were developed for winter and summer conditions, based on actual driving cycles. These models hold particular significance for microscale road analyses. The resultant model, for test data in summer conditions, demonstrates validation indicators of an R2 of 86% and an MSE of 1.4, while, for winter conditions, its values are 89% and 2.8, respectively, confirming its high precision. The paper also presents exemplary applications of the developed models, utilizing both real and simulated microscale data. The results obtained and the presented methodology can be especially advantageous for decision makers in the management of city roads and infrastructure planners, aiding both cognitive understanding and the better planning of charging infrastructure networks.

Securing the smart city: A review of cybersecurity challenges and strategies

In the era of rapid urbanization and technological advancement, the emergence of smart cities promises innovative solutions to urban challenges. However, the integration of various technologies into urban infrastructures also exposes cities to unprecedented cybersecurity threats. This review presents a comprehensive review of the cybersecurity challenges faced by smart cities and explores the strategies to mitigate these risks. Smart cities leverage interconnected networks of sensors, devices, and systems to enhance efficiency, sustainability, and citizen services. Yet, this interconnectedness creates a complex attack surface vulnerable to cyber threats. One of the primary challenges is the diverse range of IoT devices deployed across smart city infrastructures, often lacking robust security mechanisms. These devices are susceptible to exploitation by cybercriminals for malicious activities, such as data breaches, sabotage, and surveillance. Moreover, the interconnected nature of smart city systems amplifies the potential impact of cyberattacks, posing significant risks to critical infrastructure, public safety, and privacy. Threat actors can exploit vulnerabilities in interconnected systems to disrupt essential services, manipulate data, or even cause physical harm. As smart cities rely on data-driven decision-making, the integrity and confidentiality of data become paramount concerns. To address these challenges, various cybersecurity strategies have been proposed and implemented. These strategies encompass a multi-layered approach, integrating technical solutions, regulatory frameworks, and collaboration among stakeholders. Technical measures include encryption, authentication mechanisms, intrusion detection systems, and secure software development practices. Additionally, implementing robust access controls and network segmentation can limit the scope of potential attacks. Furthermore, regulatory initiatives play a crucial role in enhancing cybersecurity standards and promoting compliance among smart city stakeholders. Establishing clear guidelines for data protection, privacy rights, and incident response protocols is essential to safeguarding citizens' interests. Collaboration among government agencies, private sector partners, academia, and cybersecurity experts fosters information sharing and collective defense against emerging threats. Securing smart cities against cybersecurity threats requires a concerted effort to address the multifaceted challenges posed by interconnected technologies. By implementing comprehensive strategies encompassing technical measures, regulatory frameworks, and collaborative approaches, smart cities can mitigate risks and foster a resilient and secure urban environment for all citizens.

A Systematic Review on Human Thermal Comfort and Methodologies for Evaluating Urban Morphology in Outdoor Spaces

The exponential growth of urban populations and city infrastructure globally presents distinct patterns, impacting climate change forecasts and urban climates. This study conducts a systematic review of the literature focusing on human thermal comfort (HTC) in outdoor urban environments. The findings indicate a significant surge in studies exploring HTC in open urban spaces in recent decades. While historically centered on Northern Hemisphere cities, there is a recent shift, with discussions extending to various metropolitan contexts in the Southern Hemisphere. Commonly employed urban categorization systems include Sky View Factor (SVF), Height × Width (H/W) ratio, and the emerging Local Climate Zones (LCZs), facilitating the characterization of urban areas and their usage. Various thermal indices, like Physiological Equivalent Temperature (PET), Predicted Mean Vote (PMV), Universal Thermal Climate Index (UTCI), and Standard Effective Temperature (SET), are frequently utilized in evaluating external HTC in metropolitan areas. These indices have undergone validation in the literature, establishing their reliability and applicability.

Options for adaptation of depressive industrial territories of large cities

The article discusses the issue of adaptation of former industrial buildings in industrial areas. The world experience of transforming industrial heritage is analyzed, the features of working with these objects are revealed, taking into account their historical value and the recorded legislative status of the cultural heritage object. Options for adaptation of depressed industrial areas have been identified, depending on the degree of influence and intervention both in the architectural appearance of the building and its space-planning structure, and in its urban planning characteristics: restoration with adaptation, new non-capital construction, reconstruction, new capital construction. Models for adaptation of industrial heritage sites in the urban environment are proposed, depending on the interaction of the industrial territory with the city infrastructure.

Transport investments and the changing space economy in Kumasi, Ghana

In many African cities, major public transport investments result in mixed land use decisions by private residents. The economic and planning implications of these private land-use decisions are not fully understood; and hence not taken advantage of. Using Kumasi, the second largest city in Ghana, this study explores the range of land use changes and space economy along the Asokwa By-pass and Interchange project, implemented between 2008 and 2011. While not establishing causality, the paper juxtaposes the space economy along the corridor prior to its commencement with existing land uses; to examine perceived and real changes recorded. Adopting a combination of qualitative and quantitative data collection methods including institutional consultations and survey of 290 household participants and 20 business operators, the paper observes rapid emergence of economic uses; conversion of obsolete buildings into shopping arcades; and reclamation of unused lands. Beyond providing improved access and mobility, urban transport investments in cities in sub-Saharan Africa could be leveraged for value capture and revenue mobilisation towards the management of the infrastructure provided. This calls for a re-examination of the role of urban transport investments in sustainable city planning and infrastructure management in sub-Saharan Africa.

Smart Healthcare Management Model for Proactive Patient Monitoring

The rapid development of Artificial Intelligence (AI) is leading urban centers to employ AI technologies to improve efficiency and solve urban problems. This research proposes a Centralized System Model for Smart Cities (CSMSC) that centralizes AI-oriented data acquisition, processing, and decision-making. CSMSC uses real-time sensor networks for data collection, sophisticated AI algorithms for nuanced data interpretation, and unified storage for streamlined information management. Additionally, CSMSC integrates AI-based analyzers to autonomously produce alerts, evaluate their urgency, and decide upon suitable responses, enabling quick and targeted city interventions. The paper combines field evidence with theoretical frameworks to highlight the transformative potential of cognitive sensing and machine learning in smart city development. Recent studies have shown that AI on edge is revolutionizing the infrastructure of smart cities by bringing advanced intelligence and real-time analytics closer to the data source. AI on edge enables real-time decision-making, reduces latency, optimizes bandwidth usage, and enhances privacy and security. The potential benefits of using data analytics in smart cities are significant, and future research should focus on developing new algorithms and tools to analyze data and explore new IoT and machine-learning applications.

Anomaly Detection of IoT Cyberattacks in Smart Cities Using Federated Learning and Split Learning

The swift proliferation of the Internet of Things (IoT) devices in smart city infrastructures has created an urgent demand for robust cybersecurity measures. These devices are susceptible to various cyberattacks that can jeopardize the security and functionality of urban systems. This research presents an innovative approach to identifying anomalies caused by IoT cyberattacks in smart cities. The proposed method harnesses federated and split learning and addresses the dual challenge of enhancing IoT network security while preserving data privacy. This study conducts extensive experiments using authentic datasets from smart cities. To compare the performance of classical machine learning algorithms and deep learning models for detecting anomalies, model effectiveness is assessed using precision, recall, F-1 score, accuracy, and training/deployment time. The findings demonstrate that federated learning and split learning have the potential to balance data privacy concerns with competitive performance, providing robust solutions for detecting IoT cyberattacks. This study contributes to the ongoing discussion about securing IoT deployments in urban settings. It lays the groundwork for scalable and privacy-conscious cybersecurity strategies. The results underscore the vital role of these techniques in fortifying smart cities and promoting the development of adaptable and resilient cybersecurity measures in the IoT era.

Learn to Bet: Using Reinforcement Learning to Improve Vehicle Bids in Auction-Based Smart Intersections.

With the advent of IoT, cities will soon be populated by autonomous vehicles and managed by intelligent systems capable of actively interacting with city infrastructures and vehicles. In this work, we propose a model based on reinforcement learning that teaches to autonomous connected vehicles how to save resources while navigating in such an environment. In particular, we focus on budget savings in the context of auction-based intersection management systems. We trained several models with Deep Q-learning by varying traffic conditions to find the most performance-effective variant in terms of the trade-off between saved currency and trip times. Afterward, we compared the performance of our model with previously proposed and random strategies, even under adverse traffic conditions. Our model appears to be robust and manages to save a considerable amount of currency without significantly increasing the waiting time in traffic. For example, the learner bidder saves at least 20% of its budget with heavy traffic conditions and up to 74% in lighter traffic with respect to a standard bidder, and around three times the saving of a random bidder. The results and discussion suggest practical adoption of the proposal in a foreseen future real-life scenario.

Review and Analysis of City Strategic Management Systems

Strategic city management systems serve for information and analytical support of decision makers. Models of urban systems based on the agent-based approach and system dynamics are highly accurate, allow real-time monitoring of the urban environment, timely preparation for possible emergencies, and also choose the best ways to develop the city's infrastructure. Research in this area is very relevant today: dozens of models have been proposed that describe almost all urban processes. However, the question of systematization of these models remains open. In this paper, an overview of the existing city management systems implemented using the methods of system dynamics and the agent approach is made. The description of the latest researches of foreign authors in the field of agent-based modeling is given.

River restoration in the urban landscape as a turning point in culture and hydropolitics: Narrations and case studies for the challenges of the 21 st century

The purpose of this article is an interdisciplinary and cross-domain analysis of the idea of restoration of watercourses in urban landscapes. We refer to publications from the field of urban studies, ecohydrology and ecological humanities. In the first part of the article, we define the problem range and analyse the narrations of the artistic projects of the recent period dealing with blue infrastructure in cities. Next, we review case studies illustrating good practice in urban spaces involving the so-called urban-river concept. These examples will allow us to identify benefits to be found for cities, especially in the field of the fight on climate change. The article aims to outline possible solutions for the urban landscape, including opportunities to enrich the urban culture and identity.

Sustainable Smart City Technologies and Their Impact on Users’ Energy Consumption Behaviour

Sustainable smart cities (SSCs) target decarbonisation by optimising energy consumption through the emerging capabilities of technology. Nevertheless, the energy consumption behaviour of end users has the potential to compromise the effectiveness of technological interventions, reflecting the importance of active social engagement in realising decarbonisation goals. Although extensive research exists on energy consumption behaviour, little is known about how technology engagement affects it, the nature of these technologies, and their role in SSC. The paper aims to identify, categorise, and investigate the smart technologies that impact household energy consumption behaviours and their integration into the larger SSC system. Following a systematic review of 60 articles from the Scopus database (2013–2023), the study found 45 smart technologies cited, with 49% affecting efficiency behaviour and 51% affecting curtailment behaviour. While these technologies inform the city administration level in the SSC framework, the role of end users remains unclear, suggesting a technocratic approach. The study proposes the Sustainable Smart City Network to facilitate a grassroots approach, identifying five key domains: government policies, smart technology adoption, smart technology engagement, smart city infrastructure, and urban sustainability. The study provides an original contribution to knowledge by unveiling the key technologies affecting energy consumption behaviour and outlining the pragmatic requirements for achieving decarbonisation through a grassroots approach.

FinTech in City Management

This study examines how FinTech is influencing modern urban governance and how these technologies are helping to address global urban challenges.It was found that in the modern city, FinTech is used to optimize the provision of public services, and mobile applications and online platforms allow city residents to easily pay bills for these services and monitor costs. FinTech is also an important catalyst for reforms in the field of urban transport systems, through mobile applications today you can order a taxi, monitor the movement of urban transport, pay for fares, manage traffic flows, which makes public transport more accessible and convenient for city dwellers. All this allows you to avoid traffic jams and improve public safety.The functional determinacy between modern financial technologies and city management is established, the opportunities provided by FinTech for optimizing city infrastructure management processes are revealed. Cases of how cities can use financial technologies to solve their problems and improve the quality of communal services are analyzed. The problem of implementing FinTech solutions for effective management decision-making with an analysis of public opinion is revealed. The importance of taking into account the financial stability of cities when using innovative financial solutions for the development of modern cities is emphasized. Attention is focused on the development of innovations and new financial opportunities for cities and their residents when using technologies to improve the quality of life of citizens and the development of the local economy.

Energy Management System of Luminosity Controlled Smart City Using IoT

INTRODUCTION: With the escalating rates of urbanization, there is a pressing need for enhanced urban services. The concept of smart cities, leveraging digital technologies, offers a promising solution to elevate urban living. The integration of Internet-of-Things (IoT) in urban infrastructure, particularly on highways, opens avenues for novel services and cross-domain applications through Information and Communication Technologies. However, the efficient functioning of an IoT-enabled smart city necessitates careful energy resource management.
 OBJECTIVES: Propose a Highway Lighting System (HWLS) integrating IoT technologies to enhance urban services, focusing on significant energy savings and real-time environmental parameter monitoring.
 METHODS: To achieve the objective of enhancing urban services through the proposed Highway Lighting System (HWLS), the system was designed and implemented by integrating cutting-edge sensors, communication links, and the Blynk IoT app. The deployment involved incorporating IoT technologies for real-time monitoring of air quality, air moisture, and soil moisture, alongside a fault identification system using GSM and GPS modules.
 RESULTS: The proposed HWLS demonstrates significant energy savings, consuming only 37.6% of the original power consumption. The incorporation of IoT technologies facilitates real-time monitoring of environmental parameters, enabling informed decision-making for urban service optimization. The fault-finding system, utilizing GSM and GPS modules, enhances the reliability of the lighting system.
 CONCLUSION: In conclusion, the Highway Lighting System (HWLS) represents a novel approach to smart city infrastructure, particularly in the context of urban lighting. The integration of IoT technologies not only contributes to energy savings but also enhances the overall efficiency of urban services. The proposed system's ability to monitor environmental parameters and identify faults demonstrates its potential for sustainable urban development and improved quality of life.

A Digital Transformation Framework for Smart Municipalities

Smart cities, as defined by Sustainable Development Goal 11, strive to make cities more inclusive, safe, resilient, and sustainable. Digital technologies addresses urbanisation concerns, such as rising energy use, pollution, waste disposal, and social inequities. The Internet of Things (IoT) and data-driven technologies are essential drivers, with a focus on infrastructure and decision-making in smart cities and municipalities. Digital Transformation (DT) is a prerequisite for becoming a Smart Municipality. The research objective of this paper is to investigate the role of digital technologies in improving urban processes, focusing on Smart City dimensions for municipalities, namely smart governance, environment, living, and technology. Municipalities in South Africa, particularly in the Eastern Cape, used digital adoption to boost productivity and skill development. However, the need for standardised DT principles presents problems for transitioning municipalities into data-driven organisations. The paper also examines the global energy issue and how smart cities can contribute to energy solutions. Finally, the paper addresses the following research question: ‘How can lessons learned from the Eastern Cape Municipalities digital adoption be scaled to other developing nations facing similar challenges in energy management and urban planning?’ Using a survey method, it provides guidelines in the DT framework, offering empirical insights into Smart Municipality digitalisation.

Alcohol availability and affordability in three constituent entities of the Russian Federation

Aim. To analyze availability and affordability of alcoholic beverages in Russian cities.Material and methods. We assessed the actual state of urban infrastructure in the Arkhangelsk, Tver and Sverdlovsk regions. Data were collected in three districts of Arkhangelsk, three districts of Tver, three districts of Yekaterinburg and Revda, where participants of the Epidemiology of Cardiovascular Diseases and their Risk Factors in Regions of Russian Federation-3 (ESSE-RF3) study (2021) lived. The study objects were elements of the city infrastructure where alcoholic beverages were sold. To assess the infrastructure, special software was developed to collect and analyze the necessary data using Open Street Maps. Data were collected from January to March 2022.Results. In total, 1180 alcohol-selling outlets were identified in the study areas: in Arkhangelsk — 450, in Yekaterinburg and Revda — 444, and in Tver — 286. Mainly alcoholic beverages in Sverdlovsk and Tver regions can be purchased in the alcohol section of a grocery store (n=260, 58,6% and n=185, 41,4%, respectively), and in the Arkhangelsk region — in a specialized liquor stores (n=263, 58,4%). The median number of alcohol stores located within a radius of 1000 m from the place of residence of the ESSE-RF3 participant was 33, and within a radius of 400 meters — 8. In Arkhangelsk, the alcohol was sold in a grocery store located in the same building as the college branch. In the Sverdlovsk region, the nearest alcohol store was located at a distance of 50 m from the kindergarten, in the Tver region — 44 m from the college. A 0,5 liter bottle of vodka was sold below the price floor in 55,1% of specialized liquor stores in the Sverdlovsk region and in 66,8% of such liquor stores in the Tver region.Conclusion. As a result of the study, availability and affordability of alcoholic beverages in Arkhangelsk, Tver, Yekaterinburg and Revda was assessed. The findings reflect the high availability of alcohol and indicate the need for interventions at both the national and local government levels. The used method of collecting and analyzing data demonstrated sufficient research effectiveness and can be recommended for wider use.

A climate-impact-related transport infrastructure risk assessment for the City of Cape Town

Climate-related severe weather events pose a threat to transport infrastructure. Damage to transport infrastructure, in turn, threatens access to socio-economic opportunities (such as employment, healthcare and education). The aim of this paper is to quantify the volume of transport infrastructure at risk of weather-related hazards in the City of Cape Town, and to estimate the direct economic value thereof. Geographical Information Systems are used to overlay areas that are highly exposed to climate-related threats on the city's transport network and infrastructure, enabling the identification and quantification of the volume of infrastructure at risk. Cost estimates for the rehabilitation or reconstruction of this infrastructure obtained from various experts in the South African transport arena are applied to calculate the economic value of the infrastructure at risk. In total, the transport infrastructure at high risk in the case city is valued at R20 billion. Fires and coastal flooding pose the greatest threat. The analysis presented can inform planners and decision-makers on how to improve the resilience and where to reduce the vulnerability of transport infrastructure in the city.

The Economic Impact and Application Challenges of IoT Technology in Smart Home and Infrastructure

This paper takes an in-depth look at the Internet of Things (IoT) and its transformative impact on smart homes and infrastructure. It delves into the evolution of IoT technology, its economic impact, the challenges it poses, and strategies to overcome them, supported by real-world case studies. The paper begins with an overview of the historical development of the IoT, tracing its roots from basic automation to complex connected systems in homes and cities. The paper highlights how the IoT is evolving, integrating into our daily lives and reshaping the way we interact with our living and working environments. The report takes a broad look at the economic impact of the IoT, revealing how it is revolutionizing market dynamics by increasing efficiency, reducing costs and creating new business opportunities. The analyses include data-driven insights into smart home energy efficiency and smart city infrastructure operational efficiency. In addition, the report discusses the impact that the proliferation of IoT will have on the job market and skills requirements. Addressing the challenges faced by IoT, the paper identifies key areas, including technical barriers such as interoperability and security, social issues such as privacy and digital divide, and environmental issues such as e-waste and sustainability. The paper proposes comprehensive strategies and solutions involving policy reforms, technological advances, and co-operation between the public and private sectors. The paper presents practical examples of IoT applications through a series of case studies that illustrate successes and challenges in different regions and sectors. These case studies provide valuable insights into the real-world applications and outcomes of IoT technologies. Finally, the paper summarises the discussion on IoT, highlighting its potential to significantly improve the quality of life and the efficiency of urban systems. It emphasises the need for a balanced approach to address the complexities and responsibilities associated with IoT advances to ensure a sustainable and equitable technological future.

Seasonal influences on preferences for urban blue-green spaces: Integrating land surface temperature into the assessment of cultural ecosystem service value

Rapid urbanization has triggered conflicts between blue–green space and other city infrastructure, challenging urban planning efforts to improve city residents' well-being. Cultural ecosystem services (CESs) improve mental and physical wellness by offering access to blue–green space via aesthetic or recreational experiences, but these offerings fluctuate; seasonal differences and contributing factors are unclear. We divided urban green space representation into Changfeng Park (CF) in the city core district, Miracle Park (QJ) in the nearby suburb, and Wusong Paotaiwan Wetland Park (WPW) in the far suburb. We combined social media data regarding CESs with the SolVES model and innovatively considered land surface temperature (LST) as an environmental factor affecting CESs. The study demonstrated that (1) seasonal changes significantly influence CES provision in WPW and QJ via landscape dynamics and landscape-related cultural activities. In the more universally designed CF Park, CES seasonal variations were smaller. (2) LST affected CES experiences at both spatial and temporal scales, with higher degrees of influence in summer and in the WPW, potentially due to Shanghai's seasonal high temperatures and humidity and unique landscape features, respectively. (3) These findings can help create seasonally-adaptable blue–green areas that satisfy the demands of urban residents.

Economic value of the hot-day cooling provided by urban green and blue space

Increasing high temperatures due to climate change are exacerbated by urban heat island effects, resulting in a range of human health and economic impacts. The green and blue infrastructure (GBI) in cities that underpins nature-based solutions (NBS) can help alleviate hot-day temperatures. In this study we bring together multiple data sources to evaluate the cooling benefit provided by urban GBI in terms of avoided losses in labour productivity, for eleven City Regions in Great Britain, over a ten-year period. We defined the urban extent to include the green (woodland, grassland and parks, gardens) and blue (rivers and canals, lakes and ponds) features within cities, and derived aggregate cooling factors for urban areas in each City Region, applying additional cooling factors to buffer zones around larger GBI features. We collated gridded meteorology data to assess the number of hot-days exceeding 28 °C Wet Bulb Globe Temperature in each City Region over the period 2008–2017, and applied response functions to evaluate loss of worker productivity for ten economic sectors. For the GBI features (aggregated adjacent features >200 m2), gardens make up the biggest component (26% of urban extent) closely followed by grassland and parks (24%), with woodland at 6%. The aggregate cooling factor of GBI ranged from 0.64 – 0.89 °C across the eleven City Regions. The economic benefit of cooling was greatest for London, due to its greater exposure to hot days, and its greater contribution to the economy than other City Regions. In the hottest year of 2015, the cooling benefit in London was £ 13.97 m. The cooling benefit varied considerably from one year to the next, depending on meteorology, and will increase under climate change.

Global disparities in urban green space use during the COVID-19 pandemic from a systematic review

The COVID-19 pandemic disrupted urban resilience and challenged the use of urban green space (UGS). Previous studies lack consensus on whether UGS use increased or decreased during and after lockdowns and how this related to policy, economic conditions and UGS types. In a systematic review, we screened >3,000 articles in 5 languages, identifying 177 articles on UGS use changes in 60 countries. The cities studied show diverging changes in UGS use. Generally, decreases occurred where COVID-19 policies were stricter and the gross domestic product per capita was lower, including in most of the few studied areas of the Global South. All studies on private gardens and 60% on forests and other natural areas showed increases, while 77% of studies conducted on public parks indicated decreased use. The global disparity in UGS use was exacerbated during the COVID-19 pandemic, demonstrating the need to enhance green infrastructure for healthy cities and to extend it beyond public parks.