Challenge For Cities Research Articles

AI-Driven Predictive Analysis for Urban Traffic Management: A Novel Approach

Urban traffic management remains one of the most complex challenges of modern cities, with congestion, inefficiencies, and accidents costing billions of dollars annually and contributing significantly to pollution and stress. Current traffic management systems are often reactive rather than predictive, responding to congestion and incidents after they occur. This paper introduces a novel AI-driven predictive analysis framework for urban traffic management that leverages advanced machine learning (ML) algorithms and real-time data inputs. The system aims to not only manage existing traffic efficiently but to predict congestion, optimize traffic flows, and enhance computer safety proactively. We explore the integration of multiple data sources—such as GPS data, traffic cameras, IoT sensors, and social media feeds—into a cohesive AI model that learns and evolves. The goal is to create a fully autonomous traffic management system that adjusts dynamically to urban changes, improving overall city mobility, sustainability, and quality of life.

To be heard or not to be heard: Precarity in the lives of Turkish musicians in Paris and Istanbul

This phenomenological study explores Turkish musicians’ precarity experiences in Paris and Istanbul. Based on in-depth interviews conducted with 11 professional musicians in each city, it focuses on participants’ lived experiences and interpretations to understand how the precarity varies in these cities with different social policy tools available to musicians. The themes resulting from the data analysis indicate similar challenges in both cities, namely insufficient and low income, employment uncertainty, and informal work relations. Nevertheless, these problems manifest differently in each case. Musicians in Istanbul endure more severe consequences of precarity, lacking fundamental social rights. Hence, the essence of their precarity experience is a sense of invisibility, marginalization, and an unassured future. On the contrary, social policy measures, particularly the “Intermittence du Spectacle” regime tailored for intermittent performance workers in France, provide a significant safety net to mitigate the effects of precarity in the Paris case.

Spatio-Temporal Feature Extraction for Pipeline Leak Detection in Smart Cities Using Acoustic Emission Signals: A One-Dimensional Hybrid Convolutional Neural Network–Long Short-Term Memory Approach

Pipeline leakage represents a critical challenge in smart cities and various industries, leading to severe economic, environmental, and safety consequences. Early detection of leaks is essential for overcoming these risks and ensuring the safe operation of pipeline systems. In this study, a hybrid convolutional neural network–long short-term memory (CNN-LSTM) model for pipeline leak detection that uses acoustic emission signals was designed. In this model, acoustic emission signals are initially preprocessed using a Savitzky–Golay filter to reduce noise. The filtered signals are input into the hybrid model, where spatial features are extracted using a CNN. The features are then passed to an LSTM network, which extracts temporal features from the signals. Based on these features, the presence or absence of a leakage is determined. The performance of the proposed model was compared with two alternative approaches: a method that employs combined features from the time domain and LSTM and a bidirectional gated recurrent unit model. The proposed approach demonstrated superior performance, as evidenced by lower validation loss, higher validation accuracy, enhanced confusion matrices, and improved t-distributed stochastic neighbor embedding plots compared to the other models when tested on industrial data. The findings indicate that the proposed model is more effective in accurately detecting pipeline leaks, offering a promising solution for enhancing smart cities and industrial safety.

Study on the Influence of the Built Environment and Personal Attributes on Commuting Distance: A Case Study of the Tianjin Central Area Divided by TAZ Units

Long commuting distances pose a significant challenge for many large cities, undermining the principles of sustainable urban development. The factors influencing urban commuting distances among residents are complex and necessitate hierarchical analysis. This study uses Tianjin, one of China’s four municipalities, as a case study, employing transportation analysis zones (TAZ) as research units. We classify these units based on resident and working populations, extracting multiple built environment and personal attribute factors to establish a model that examines the influence of the job–housing balance. The analysis identifies 12 sub-items across two categories of influencing factors, with correlations tested through spatial analysis and linear regression. We found 28 positive associations and 35 negative associations. Notably, the job–housing relationship for the working population was generally more sensitive to changes than that of the resident population. At the TAZ level, personal attributes exerted a more significant influence on the job–housing balance than built environment factors, with commuting mode, life stage, age, and income level notably affecting commuting distances.

Reprogramming Heritage: An Approach for the Automatization in the Adaptative Reuse of Buildings

This article introduces a methodology for a novel data-driven computational model aimed at aiding public administrations in managing and evaluating the adaptative reuse of buildings while tackling ecological and digital challenges. Drawing from the 2030 Agenda for Sustainable Development, the study underscores the significance of innovative approaches in harnessing the economic potential of data. Focusing on Barcelona’s Ciutat Vella district, the research selects five historic public buildings for analysis, strategically positioned to spur local entrepreneurship and counteract tourism dominance. Through an extensive literature review, the article identifies a gap in computational models for building adaptative reuse and proposes a methodological framework that integrates data collection, processing, and computational modelling, underscored by GIS technology and open data sources. The proposed methodology for a computational algorithm aims to systematise spatial characteristics, assess programmatic needs, and optimise building usage, while addressing challenges such as data integration and quality assurance. Ultimately, the research presents a pioneering approach to building adaptative reuse, aimed at fostering sustainable urban development and offering replicable insights applicable to similar challenges in other cities.

Sustainable urban digital innovation: A socio-technical competency-based approach to evaluation

This study explores the leadership competencies required in practice by city planners and managers in smart city projects focusing on environmental urban sustainability. Although the literature notes that urban technologies and their capabilities can help address sustainability challenges in cities, there is a lack of studies exploring the competency requirements necessary to foster leadership capacity. This paper identifies leadership competencies within four real-world case studies in the urban built environment, guided by a socio-technical competency framework (DC2-CF). The selected case studies represent a diverse set of city planning purposes, geographic regions, various levels of spatial scale, and socio-technical elements of digital innovation. In these case studies, city managers exhibit specific competencies to develop digital innovation projects that uphold and advance urban sustainability. The study demonstrates the relevance and practical application of DC2-CF as a valuable tool to identify competency needs for local public, private, and community stakeholders throughout diverse stages of the urban digital innovation process. The findings suggest the complex relationship between competencies and project delivery, stressing variations in how they are utilised across various projects. Drawing from these key results, this paper provides practical recommendations for city professionals, guiding them in leading climate-friendly and sustainable urban digital innovation.

A városi önvezetőjármű-felkészültség kulcstényezőinek meghatározása strukturált szöveg- és tartalomelemzéssel = Investigating Autonomous Vehicle Readness of Cities: A Structured Text and Content Analysis

The process of urban integration of autonomous vehicles is posing increasing challenges for many cities today. Based on the growing number of autonomous vehicle tests on urban roads, it seems that the urban presence of these vehicles requires only minimal preparation from cities. However, their widespread adoption, integration, and effective and safe operation at the urban level require substantial preparation. This study aims to synthesize the factors found in the literature using software-supported structured text and content analysis. Based on our results, we identified nine main factors and twenty-seven key elements that could be crucial in supporting the future mass adoption of autonomous vehicles in urban areas. With our work, we hope to contribute to a deeper understanding of urban autonomous vehicle readiness and the identification of measures necessary to achieve it.

Land price, government debt, and land-use efficiency in the coastal cities of China under the constraint of land scarcity

Land scarcity poses a significant challenge for coastal cities in supporting sustainable urban development. This study quantifies the Land Scarcity Index (LSI) for 51 Chinese coastal cities from 2008 to 2018, revealing a phased increase and a transition to high scarcity levels. The findings reveal significant differences in the land price dynamics and fragmentation between commercial-residential and industrial land plots. Under LSI constraints, both commercial-residential and industrial land plots exhibit a trend of decreasing plot areas and increasing prices. We further explore the threshold effects of local government debt (LGD) on urban land-use efficiency, demonstrating that high LGD and LSI exacerbate the price scissors gap, adversely affecting land-use efficiency. Our findings show that, when LGD exceeds 10.43%, increased commercial-residential land prices enhance land-use efficiency, whereas below this threshold, they hinder it. Similarly, the land price scissors (LPS) gap between commercial-residential and industrial land negatively impacts land-use efficiency when LGD exceeds 14.59%. This study provides valuable insights into optimizing land fiscal policies, improving urban land-use efficiency, and addressing the challenge of land scarcity in China's coastal cities.

Generative artificial intelligence: a proactive and creative tool to achieve hyper-segmentation and hyper-personalization in the tourism industry

Purpose The purpose of this paper is to explore how GenAI can help companies achieve a higher level of hyper-segmentation and hyper-personalization in the tourism industry, as well as show the importance of this disruptive tool for tourism marketing. Design/methodology/approach This paper used the Web of Science and Google Scholar databases to provide updated studies and expert authors to explore GenAI in the tourism industry. Analysing hyper-segmentation and hyper-personalization modalities through GenAI and their new challenges for tourists, tourism cities and companies. Findings Findings reveal that GenAI technology exponentially improves consumers’ segmentation and personalization of products and services, allowing tourism cities and organizations to create tailored content in real-time. That is why the concept of hyper-segmentation is substantially focused on the customer (understood as a segment of one) and his or her preferences, needs, personal motivations and purchase antecedents, and it encourages companies to design tailored products and services with a high level of individual scalability and performance called hyper-personalization, never before seen in the tourism industry. Indeed, contextualizing the experience through GenAI is an important way to enhance personalization. Originality/value This paper also contributes to enhancing and bootstrapping the literature on GenAI in the tourism industry because it is a new field of study, and its functional operability is in an incubation stage. Moreover, this viewpoint can facilitate researchers and companies to successfully integrate GenAI into different tourism and travel activities without expecting utopian results. Recently, there have been no studies that tackle hyper-segmentation and hyper-personalization methodologies through GenAI in the tourism industry.

Exploring the Spatiotemporal Heterogeneities in Urban Vitality Through Scalable Proxies from Mobile Data

Jane Jacob’s concepts of urban vitality and diversity have become prevailing urban planning philosophies in most countries for making cities more livable. Recent changes in demographics and the impacts of COVID-19 have exacerbated the economic and social challenges that cities commonly face, particularly spatiotemporal heterogeneities. Being able to understand these heterogeneities in scalable approaches is fundamental to tackling these challenges in cities. Therefore, this article aims to provide a new form of scalable estimation of urban vitality by using the de facto population. Instead of merely adopting static statistical information such as morphological characteristics in areas, we leverage dynamic factors such as internal mobility flows and energy use intensity as proxies for the spatiotemporal dynamics of indoor and outdoor behaviors of crowds. In this way, we combine dynamic attributes and static features to describe the patterns of urban vitality, which are directly related to spatiotemporal dynamics in urban places. We utilize GNSS-based mobile data and building energy usage intensity as dynamic proxies along with static data such as land use mix and age distribution. To better capture spatial heterogeneity, we use a Multiscale Geographically Weighted Regression (MGWR) model to identify the relationships between the de facto population and the dynamic and static factors. Drawing from the factors determining urban vitality, this article provides policy implications for alleviating spatiotemporal urban imbalances. These data-driven implications can fill the technical knowledge gaps in establishing planning strategies for achieving urban sustainability while enhancing overall subjective livability.

Reimagining urban waste management: Addressing social, climate, and resource challenges in modern cities

Governments worldwide are seeking better solutions for solid waste management. Thermal treatment projects are presented as quick fixes for rising waste challenges, without addressing the limitations of incineration. Currently, there is a rise in proposals for thermal treatment technologies in developing countries. Scrutiny of the risks and impacts of these alternatives is necessary due to social, climate, and resource considerations. Energy from waste incineration is considered fossil energy since about half of the CO2 emissions come from fossil polymers in the waste. From a sustainability perspective, landfilling is a short-term option for materials currently unsuitable for recycling. Landfills act as bioreactors, producing valuable biogas, and serve as “resource banks,” storing unrecyclable resources until better recycling techniques are developed. In developing countries manual labor is abundant and material sorting and landfilling are more valuable and have a lower climate and resource footprint. This paper offers a novel, integrated perspective of waste management in view of poverty reduction, climate change and resource conservation.

Innovative Circular Biowaste Valorisation—State of the Art and Guidance for Cities and Regions

The management of the organic fraction of municipal solid waste (OFMSW), also called urban biowaste, and urban wastewater sludge (UWWS) represents a challenge for cities and regions, which want to adopt innovative urban bioeconomy approaches for their treatment and production of high-added-value products beyond the traditional anaerobic digestion (AD) and compost. This adoption is often restricted by the availability and maturity of technologies. The research object of this manuscript, based on the findings of EU Horizon 2020 project HOOP, is the identification of state-of-the-art circular technologies for material valorisation of OFMSW and UWWS, following a novel screening methodology based on the scale of implementation (tested at least at pilot scale). The screening resulted in 25 technologies, which have been compared and discussed under a multidisciplinary assessment approach, showing their enabling factors and challenges, their current or potential commercial status and their compatibility with the traditional technologies for urban biowaste treatment (composting and AD). The bioproducts cover market sectors such as agriculture, chemistry, nutrition, bioplastics, materials or cosmetics. Therefore, the results of this review help project promoters at city/region level to select innovative technologies for the conversion of OFMWS and UWWS into high value products.

Municipal Solid Waste Management System: A Study of Aligarh City, Uttar Pradesh, India

Municipal solid waste management (MSWM) is a significant environmental challenge in Indian cities, including Aligarh. Inadequate handling of municipal solid waste (MSW) poses risks to public health and the environment. Studies indicate that approximately 90% of MSW in India is improperly disposed of in open dumps and landfills, leading to various ecological and health issues. A detailed examination of Aligarh's waste management system was conducted to assess the quantity, characteristics, and sustainable management options for its municipal waste. Findings from the study show that private collectors handle about 430 tons of waste per day in Aligarh, but neither residents nor collectors engage in waste segregation at the source. The combined collection efficiency of A2Z Private Limited and the Aligarh Municipal Corporation is estimated to be around 70%. Due to the high organic content in the waste, its energy potential remains untapped. Currently, about 80% of the collected waste is disposed of in open dumps, as Aligarh lacks a sanitary landfill. This study highlights the current state of municipal solid waste management in Aligarh focusing on the quantity, quality, and management strategies in Aligarh. Methodology: For this study, Aligarh, a medium-sized city with a population of roughly 8.7 lakhs, which is located 130 kilometres from Delhi, India's capital, was chosen. A thorough assessment of the literature was done to create a theoretical framework. Visits to fields were carried out to gather basic data and comprehend the city's SWMS, including interaction During interviews with several municipality employees and executives in charge of SWM and citizens of the city. A procedure was created to examine the sources, calculate the amounts, and ascertain the waste streams' makeup. Findings: Despite their best efforts, the local municipality's limited resources do not allow for the effectiveness of the solid waste management system in Aligarh. On the outskirts of the city, waste is frequently disposed of in open or low-lying regions without using the correct scientific or engineering techniques.

Noise without noise? Art interventions in a Southeast Asian city

The experimental music community Jogja Noise Bombing based in the Indonesian city of Yogyakarta has for more than a decade experimented with pop-up performances of harsh noise played on DIY instruments in urban spaces. These urban spaces, however, tend themselves to be very "noisy". Since 2018 we have followed these performances online and through fieldwork in Indonesia with an ongoing curiosity that stays with the trouble of noise. We are attracted to the context of these performances because they challenge us to answer a series of paradoxical questions: what is noise aesthetics in a place where everything is "noisy" and where this noisiness, furthermore, does not seem to be experienced as a problem or provocation? Can one even speak of "noise" if it is not unwanted? The social aesthetics of Indonesian harsh noise music in its specific attunement to the soundscapes of the Indonesian city challenges Western conventional ontologies of noise and ideas of the relationship between "objective" noise and aesthetic performances of noise such as noise music in several ways.

Cartographies of infrastructural imaginations: mapping ecological utopias and dystopias in the Global South

This article provides the reader with a theoretical framework and a method of representing cities called cartographies of infrastructural imaginations. The study employs mapping methods from the fields of architecture, urban geography and visual cultures. The research inquires about the role of cartography in the analysis of discourses that define policies of water supply, food distribution and land-use regulation, which are three environmental challenges in cities. How can we identify and situate the urban actors that attend to such challenges in cities from the Global South? The research is empirically grounded in Mexico City, Shanghai and Bangalore, urban settlements with a history of colonial occupation in previous centuries. Their foreign interventions still shape urban imaginaries of these cities. The method of blending photographic analysis with maps aims to offer objective precision of geographical data and subjective street-level views of local stories. The intention is to understand where the infrastructural ideas come from, and how imaginaries flow to communicate visions about the development of the city. A central task here is to frame how power structures interact and represent their interests via utopian and dystopian narratives.

Ride-Hailing vs. Fixed-Route: Preferences of the Transit-Dependent Populations in U.S. Urbanized Areas

Transportation inequality poses significant challenges in car-dependent cities in the US, especially for Transit-Dependent Populations (TDPs) who rely on public transportation to meet their travel requirements. Research indicates that despite the rapid growth of ride-hailing services like Uber, TDPs primarily depend on conventional transit options such as buses and metros. This study differentiates between two classifications of ride-hailing services: Private Ride-hailing (PRH), represented by platforms like Uber and Lyft, where individuals hire and pay for their rides, occasionally sharing the journey with guests; and ride-sharing (RS), like UberPool, which allows users to divide travel expenses. However, a more profound comprehension is necessary to clarify why TDPs show a preference for one mode of transportation over another and the factors that influence their decision-making. This study utilises Structural Equation Modelling (SEM) to examine the direct and indirect relationships between explanatory and outcome variables, while investigating modal preferences and usage frequency in 48 densely populated urban areas in the US (N = 384). TDPs choose to use transportation services like Uber because of their effectiveness in reducing both travel and waiting time, in contrast to traditional Fixed-Route Transit Services (FRTS), which are relatively less efficient. TDPs’ inclination towards PRH leads to a greater dependence on ride-hailing services, whereas a preference for FRTS reduces this dependence. Significantly, the study demonstrates that TDPs’ modal preferences are not only influenced by their socioeconomic status or rational decision-making, but also by the complex interaction between these factors. These findings provide valuable information for policymakers who want to evaluate the sustainability of ride-hailing services for TDPs and effectively tackle transportation inequalities.

Editorial: Desarrollo urbano y energía en el contexto de ciudades intermedias sostenibles

Sustainability-oriented urbanism proposes strategies to address environmental, social, and economic challenges in intermediate cities. Within the framework of the Sustainable Development Goals (SDGs), this issue of CienciAmérica highlights the importance of sustainability in cities. The energy transition of cities is necessary and represents an opportunity to promote sustainable investments, in line with SDG 7 (affordable and clean energy) and SDG 13 (climate action). Similarly, sustainable urban planning, in line with SDG 11 (sustainable cities and communities), promotes the circular economy through proper waste management, thereby reducing environmental impacts and promoting economic sectors and job creation. On the other hand, education for a culture of sustainability, in line with SDG 4 (Quality Education), is essential to create a society that is aware and proactive in protecting the environment. This volume also includes sustainable technology, innovation and economic competitiveness, key aspects in the implementation of SDG 9 (Industry, Innovation and Infrastructure). Finally, this edition calls on governments, businesses, organizations and citizens to work together to build a sustainable future, where sustainability and the economy are intrinsically linked to ensure the sustainable functioning of cities.

Internet of Things (IoT) Driven Water Management System for Efficient Level Control

Water is an essential and valuable resource in daily life, making its conservation crucial to prevent adverse effects. Storing water for domestic, industrial, agricultural, and other purposes is particularly important. Safe drinking water is increasingly becoming polluted due to the growing population and their demands for urbanization and industrialization. At the household level, some people leave electric water pumps running and either go to work or sleep, forgetting to turn off the pumps when the water container is full. This highlights the need for a reliable and continuous water supply. IoT plays a significant role in environmental monitoring, particularly in disaster management, early warning systems, and environmental data analytics. One major challenge in urban cities is water management, especially with the rapid growth of urbanization, necessitating sustainable urban development plans. To address these issues, we propose a "Water Level Monitoring System" solution. This paper presents an IoT-based water monitoring system for real-time applications. The system's sensors measure the water level in the tank, and the data is sent to a cloud server, allowing users to view it on a remote dashboard. This system can be used efficiently by both homeowners and industrial users, as well as other water utilities.

Assessing multiple ecosystem services in 708 European urban areas

ABSTRACT Nature is increasingly recognized for its potential to address societal challenges in cities, through the delivery of ecosystem services (ES). However, large-scale assessments quantifying this potential are rare. In this study, we modelled five ES (local temperature regulation, flood control, global climate regulation, habitat maintenance, and human interaction with nature) across 708 European urban areas. Using a supply-demand approach, we assessed ES delivery: the extent to which ES supply was sufficient to meet the corresponding societal demands. We found that ES delivery varied both spatially and between ES. On average, nearly 50% of the demand was fulfilled, with the highest values for habitat maintenance (81 ± 15%; mean ± SD), flood control (65 ± 13%), and human interaction with nature (59 ± 15%) and much lower values for local temperature regulation (23 ± 28%) and global climate regulation (16 ± 28%). We further found positive pairwise correlations between all ES (Spearman’s ρ from 0.15 to 0.65), with the strongest correlation between habitat maintenance and global climate regulation. Variation in ES delivery across the urban areas was mainly related to differences in the share of green space and the size of the urban areas, whereby ES delivery was positively related to both. Our broad-scale comparative assessment can serve as a starting point for more sophisticated model-based assessments quantifying the full potential of urban nature to meet societal demands across large areas, for example by including a broader set of ES and accounting for city-specific demands.

Advancing urban sustainability transitions: A framework for understanding urban complexity and enhancing integrative transformations

Rapid urbanization and industrialization with their negative repercussions draw attention to the need for urban sustainability. This research built on the urban systems understanding linked with resource utilization, environmental effects, people-environment interactions, and adaptive management by integrating quantitative modelling of urban metabolism with a qualitative investigation into human responses. A hybrid methodology was applied in a typical industrial city of Jinchang, China, which exemplified a model of how complex urban dynamics link to and inform sustainability transitions. The study found that Jinchang City had taken on an unsustainable trajectory underpinned by continuous growth of material consumption, whereas a potential for sustainability transitions was also observed in decoupled negative material outputs, improved material efficiency, and environment regeneration collectively. The challenges in industrial cities have been framed in terms of development model lock-in, conceptual and institutional constraints, innovation and human capital deficiencies, and governance failure. The research proposed a government-led transformation system that integrates multi-level and multi-perspective transformations and management employing discipline insights to facilitate urban sustainability transitions. This involves governance, economic and technological innovations, social transformations, and implementations, in which urban governance and public engagement are essential elements for adapting to undesirable difficulties and exploring locally appropriate strategies. This research provided a theoretical and empirical basis along with scientific and policy implications, which contributed to the developing interdisciplinary knowledge on the understanding of complex urban systems and provided insights into real-world sustainability solutions.