Urban Smart Research Articles

Analysis of machine learning methods applied to financial problems

With machine learning being widely used in many fields. In this paper, we study how machine learning methods can be used to make predictions in financial problems and analyze the applications.Machine learning is a branch of artificial intelligence that enables computer systems to learn from data and make decisions or predictions without being explicitly programmed at every step. Machine learning models are trained on large amounts of data to discover patterns and relationships in the data and use these patterns to make predictions or perform tasks. The purpose of this post is to illustrate the role machine learning plays in dissertation research.Machine learning can also be used for smart urbanization, industrial automation, fintech, healthcare, agricultural modernization, cybersecurity, etc. For example, extracting valuable information and knowledge from large amounts of data to help businesses and organizations make better decisions. By analyzing historical data, machine learning can predict future trends and behaviors, such as stock prices, house prices, weather, etc.

Comparison of Intelligent Community Design from the Perspective of Modernization--Shenzhen and Singapore as examples

With the continuous advancement of modernization, globalization, and urbanization, smart communities have received widespread attention as an important part of modern urban development. Taking two typical cases, Shenzhen and Singapore, as objects, this study compares and analyzes the design and practice experiences of the two smart communities from the modernization perspective. By comparing the design and practice of the two smart communities in Shenzhen and Singapore, it explores the common features and differences of smart community construction in different modernization contexts and provides reference and inspiration for smart community construction in future cities. Through literature research and case studies, a comparative analysis is conducted to study the design concepts, practice methods, and effects of two smart communities in Shenzhen and Singapore. The results of the study show that Shenzhen focuses on innovation and cutting-edge technology, which improves the efficiency of community governance and the quality of life of residents;Singapore focuses on community autonomy, and through intelligent management and residents' cooperation, it has improved the level of community facility management and residents' participation.This study provides useful experience and enlightenment for the construction of other urban smart communities, and provides a reference for promoting the smooth progress of urban modernization.

Territorialising the cloud or clouding the territory? Volumetric vulnerabilities and the militarised conjunctures of Singapore’s smart city-state

This article explores how the volumetric characteristics of cloud computing can create new expressions of territoriality, which in turn can reveal new axes of vulnerability and threat. Whilst recent work in political geography has sought to “locate” the cloud through analyses of data centre geographies and data-driven processes of smart urbanism, we look beyond the material plane and consider the amorphous territorialities of voluminous data instead. As much as these data are acted on by the legal-regulatory mechanics of the state in a bid to territorialise them, so too do these data volumes serve to cloud, and thus obscure, territory. Processes of territorialising and clouding exist in a state of dialectical tension with each other, and reveal the volumetric vulnerabilities of cloud computing. We validate these theoretical claims through an analysis of in-depth interviews with senior stakeholders in Singapore's Smart Nation initiative. In Singapore, defending the city is equivalent to defending the nation, which causes the military to play an outsized role in securing the city-state. We consider how the attack surface of the city becomes a more voluminous construct with cloud computing, how strategies of geofencing attempt to secure the cloud, and how these processes reveal the increasingly militarised conjunctures of everyday life. Overall, these insights reveal a need for political geography to continually evolve its theoretical premises in line with the rapid digitalisation of the world.

Evaluating coupling coordination between urban smart performance and low-carbon level in China’s pilot cities with mixed methods

The construction models of smart cities and low-carbon cities are crucial for advancing global urbanization, enhancing urban governance, and addressing major urban challenges. Despite significant advancements in smart and low-carbon city research, a consensus on their coupling coordination remains elusive. This study employs mixed-method research, combining qualitative and quantitative analyses, to investigate the coupling coordination between urban smart performance (SCP) and low-carbon level (LCL) across 52 typical smart and low-carbon pilot cities in China. Independent evaluation models for SCP and LCL qualitatively assess the current state of smart and low-carbon city construction. Additionally, an Entropy–TOPSIS–Pearson correlation–Coupling coordination degree (ETPC) analysis model quantitatively examines their relationship. The results reveal that smart city initiatives in China significantly outperform low-carbon city development, with notable disparities in SCP and LCL between eastern, non-resource-based, and central cities versus western, resource-dependent, and peripheral cities. A strong positive correlation exists between urban SCP and overall LCL, with significant correlations in management, society, and economy, and moderate to weak correlations in environmental quality and culture. As SCP levels improve, the coupling coordination degree between the urban SCP and LCL systems also increases, driven primarily by economic, management, and societal factors. Conversely, the subsystems of low-carbon culture and environmental quality show poorer integration. Based on these findings, this study proposes an evaluation system for smart and low-carbon coupling coordination development, outlining pathways for future development from the perspective of urban complex systems.

Cultivating Change: Empowering Communities Among Elderly Through Social Innovation and Entrepreneurship in Smart Urban Farming

Malaysia is gradually experiencing a demographic shift, evolving into an aging society. The problem arises concerning the economic sustainability of urban farming ventures undertaken by elderly individuals. Limited attention has been given to incorporating social science perspectives to understand its broader social and cultural implications, especially for the intergenerational aspects of urban farming, specifically among the elderly. This research investigates the adoption of smart urban farming (SUF) to enhance senior citizens' social and economic well-being (SEW). The study involved 130 elderly participants from Klang Valley, Malaysia. Data was collected through surveys and subsequently analyzed using the SPSS statistics tool. The study reveals that while Social Entrepreneurship alone may not be enough to encourage elderly adoption of SUF when combined with social innovation, it significantly increases adoption. The study also indicated that the adoption of SUF enhances the elderly SEW. This study represents a valuable addition to the existing body of literature on the adoption of SUF, particularly in its impact on the social and economic aspects of elderly individuals' lives. This study further advances the current understanding of SUF adoption, utilizing established theories such as the Resource-Based View Theory (RBT) and Social Cognitive Theory (SCT) to reinforce its conclusions. The findings offer practical insights for governments and local authorities in developing policies to promote and facilitate SUF. Doi: 10.28991/HEF-2024-05-03-012 Full Text: PDF

GC-YOLOv9: Innovative smart city traffic monitoring solution

In urban smart city environments, traffic hazards can lead to catastrophic outcomes, including significant property losses and severe threats to public safety. Conventional traffic monitoring systems are limited in terms of accuracy and speed, presenting significant challenges for real-time traffic surveillance. To tackle these challenges, this paper introduces the GC-YOLOv9 algorithm. Specifically, we have enhanced the YOLOv9 model by incorporating Ghost Convolution, markedly improving the model’s perceptual abilities and detection accuracy. Furthermore, this study designed an integrated smart city framework that includes layers for service applications, the Internet of Things, edge processing, and data centers. By deploying the enhanced YOLOv9 model within this framework, our method achieved mAP@0.5 scores of 77.15 and 74.95 on the BDD100K and Cityscapes datasets, respectively, surpassing existing technologies. Additionally, the potential applications of this method in public area fire safety management, forest fire monitoring, and intelligent security systems further underscore its significant value in improving the safety and efficiency of smart cities.

An Introduction to the Smart Urban Mobility Laboratory at University of South Florida [ITS Research Lab]

An Introduction to the Smart Urban Mobility Laboratory at University of South Florida [ITS Research Lab]

A novel efficient energy optimization in smart urban buildings based on optimal demand side management

Increasing electrical energy consumption during peak hours leads to increased electrical energy losses and the spread of environmental pollution. For this reason, demand-side management programs have been introduced to reduce consumption during peak hours. This study proposes an efficient energy optimization in Smart Urban Buildings (SUBs) based on Improved Sine Cosine Algorithm (ISCA) that uses the load-shifting technique for demand-side management as a way to improve the energy consumption patterns of a SUBs. The proposed system's goal is to optimize the energy of SUBs appliances in order to effectively regulate load demand, with the end result being a reduction in the peak to average ratio (PAR) and a consequent minimization of electricity costs. This is accomplished while also keeping user comfort as a priority. The proposed system is evaluated by comparing it with the Grasshopper Optimization Algorithm (GOA) and unscheduled cases. Without applying an optimization algorithm, the total electricity cost, carbon emission, PAR and waiting time are equal to 1703.576 ID, 34.16664 (kW), and 413.5864s respectively for RTP. While, after applying GOA, the total electricity cost, carbon emission, PAR and waiting time are improved to 1469.72 ID, 21.17 (kW), and 355.772s respectively for RTP. While, after applying the ISCA Improves the total electricity cost, PAR, and waiting time by 1206.748 ID, 16.5648 (kW), and 268.525384s respectively. Where after applying GOA, the total electricity cost, PAR, and waiting time are improved to 13.72 %, 38.00 %, and 13.97 % respectively. And after applying proposed method, the total electricity cost, PAR, and waiting time are improved to 29.16 %, 51.51 %, and 35.07 % respectively. According to the results, the created ISCA algorithm performed better than the unscheduled case and GOA scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers. Furthermore, this study has presented a novel two-stage stochastic model based on Moth-Flame Optimization Algorithm (MFOA) for the co-optimization of energy scheduling and capacity planning for systems of energy storage that would be incorporated to grid connected smart urban buildings.

"Smart Urban Planning: An Intelligent Framework to Predict Traffic Using Stack Ensembling Approach "

"Smart Urban Planning: An Intelligent Framework to Predict Traffic Using Stack Ensembling Approach "

스마트팜의 공간배치 특성 연구

Globally, decreasing arable land, insufficient food supply, and rapid urbanization have intensified the contradiction between small urban farmlands and inadequate crop production. To address this, the study explores vertical crop cultivation in urban buildings using smart farm models. Employing literature review, inductive reasoning, analytical methods, and case studies, the paper determines smart farm spatial compositions and technical elements, analyzes spatial layouts, and examines Aero Farms in the USA and Spread in Japan. Smart farms include crop production, energy, and auxiliary spaces. Crop production spaces meet growth requirements, energy spaces reprocess waste for irrigation, and auxiliary spaces use smart technology to regulate the environment. Urban smart farms can alleviate food stress, using crop production technology, waste treatment, and renewable energy. This study promotes urban vertical planting and a new agricultural revolution.

Development of Urban Smart Farm Leaf Vegetable Cultivation Vocational Rehabilitation Intervention Program for People With Developmental Disabilities Using Intervention Mapping

Development of Urban Smart Farm Leaf Vegetable Cultivation Vocational Rehabilitation Intervention Program for People With Developmental Disabilities Using Intervention Mapping

Enriching Real-Estate Through Sustainable Public Spaces: The case of Dubai- UAE

In the process of the ongoing urban planning strategies for developing smart cities, the concept of urban public square has not yet been given the attention of urbanists and city planners in the Middle East and North Africa (MENA) region. More focus was given by architects and developers on saturating the market with iconic smart buildings rather than developing more livable communities with public spaces and plazas for people to connect. The overall aim of this paper is to highlight the key role that the real state sector can play to foster developing public spaces and squares as an integral part of smart urbanism. The issue of developing urban public squares in Dubai new communities and formulating policies for including such spaces in new districts and cities should be closely examined. The focus should be on enriching the real estate sector by regulating a concept of injecting urban public squares in the new smart and sustainable urbanism in Dubai to perform as a sociocultural entity within the fabric of new communities for the sake of improving social life and developing vibrant environment. With keywords such as smart city, public squares, social, urban design, livability; and sustainability, this write up makes the case of sustainable urbanization.

Research on data security governance of smart city construction

In the post-epidemic era, the construction of smart cities has become an important link in the economic development of various countries. To improve the degree of urban smart, accelerate the construction of urban digital information infrastructure, and promote the safe sharing of network data is the meaning of smart city construction. At present, China’s smart city construction has made breakthrough progress, but the data flow still faces problems such as leakage, abuse and sharing obstruction. Therefore, we can learn from the mature experience adopted by Europe and the United States in the construction of smart cities, set up third-party institutions to actively promote data sharing, build high-value data sets open to the public, and adhere to the first trial reform. The introduction of regulatory sandbox and common data space mechanism to improve the level of smart city construction and export China’s template for smart city construction.

Harnessing Local Dynamics for Upgrading Informal Settlements: The Ezbit Hegazi Experience with the ALEXU-CoE-SUG

Informal settlements pose multifaceted challenges to urban development, necessitating a reconsideration of traditional upgrading approaches. This study examines the integration of the street-led approach within the Ezbit Hegazi informal settlement, leveraging the Alexandria University Centre of Excellence for Smart Urban Governance’s (ALEXU-CoE-SUG’s) innovative framework. It highlights the centrality of ‘Demand for Good Governance’ (DFGG) practices in bridging the gap between governmental (supply-side) and community (demand-side) objectives, fostering a collaborative urban upgrading process. Through an in-depth case study analysis, this paper reveals the potential of aligning governmental agendas with local aspirations, emphasizing the importance of local dynamics in sustainable urban development. The findings indicate that integrating bottom-up community engagement with top-down institutional support can lead to more effective and sustainable urban regeneration. The study concludes that a combined approach, leveraging both grassroots initiatives and formal governance structures, is crucial for the successful upgrading of informal settlements. The findings contribute to the urban studies literature by providing insights into the synergies between supply and demand perspectives in the context of informal settlement upgrading, offering implications for policy and practice in similar urban settings globally.

Smart Urban Mobility: The Role of AI in Alleviating Traffic Congestion

Abstract This article delves into the impact of intelligence (AI), on easing traffic congestion as cities strive to become more intelligent. It highlights advancements in AI technologies like networks (ANNs) and genetic algorithms (GAs), within the context of urban transportation and movement. The incorporation of intelligence, into transportation systems is motivated by the necessity to adapt to evolving circumstances while emphasizing improvements, in the effectiveness and environmental friendliness of transportation networks. Mobility as a Service (MaaS) combines options like transit, ride-sharing and bike rentals. Through the use of networks AI enhances urban traffic management by predicting congestion and optimizing traffic signal control at intersections. Genetic algorithms play a role, in optimizing vehicle routes by taking into account variables such as travel time and associated expenses. The research indicates a rise in the use of AI in the transportation industry signaling a change, in commuting patterns. This study highlights the significance of progressing AI technologies to meet changing infrastructure requirements and fluctuating traffic trends emphasizing the impact of AI on shaping the urban transportation landscape.

The impact of smart city construction on labour distortions from the perspective of labour mobility: evidence from China

ABSTRACT Migration decisions and labour demand are influenced by smart city construction (SCC). However, the impacts of SCC on the labour market remain black-boxed. This paper investigates the impacts of SCC on labour market distortions through an examination of a large-scale smart city pilot policy in China. Utilising urban panel data in China spanning 2008-2019, we employ a multi-period difference-in-difference model to examine the labour factor allocation effects of SCC. Our findings reveal that SCC effectively mitigates labour wage distortion (LWD) but has an adverse effect on labour misallocation (LMA). labour mobility is a critical mechanism through which SCC alleviates labour wage distortion (LWD) but exacerbates labour misallocation (LMA). Furthermore, the results of heterogeneity analysis indicate that strongly connected and high human capital cities not only benefit from SCC in alleviating LWD but also avoid its negative effects on LMA. Conversely, SCC neither improves LWD nor alleviates LMA in weakly connected and low human capital cities. These findings imply that urban smart construction causes multiple impacts on the labour factor market, which is conducive to factor market guidance policies that can coordinate with SCC.

Integrated Underground Analyses as a Key for Seasonal Heat Storage and Smart Urban Areas

The design and performance of a shallow geothermal system is influenced by the geological and hydrogeological context, environmental conditions and thermal demand loads. In order to preserve the natural thermal resource, it is crucial to have a balance between the supply and the demand for the renewable energy. In this context, this article presents a case study where an innovative system is created for the storage of seasonal solar thermal energy underground, exploiting geotechnical micropiles technology. The new geoprobes system (energy micropile; EmP) consists of the installation of coaxial geothermal probes within existing micropiles realized for the seismic requalification of buildings. The underground geothermal system has been realized, starting from the basement of an existing holiday home Condominium, and was installed in dry subsoil, 20 m-deep below the parking floor. The building consists of 140 apartments, with a total area of 5553 m2, and is located at an altitude of about 1490 m above sea level. Within the framework of a circular economy, energy saving and the use of renewable sources, the design of the geothermal system was based on geological, hydrogeological and thermophysical analytical studies, in situ measurements (e.g., Lefranc and Lugeon test during drilling; Rock Quality Designation index; thermal response tests; acquisition of temperature data along the borehole), numerical modelling and long-term simulations. Due to the strong energy imbalance of the demand from the building (heating only), and in order to optimize the underground annual balance, both solar thermal storage and geothermal heat extraction/injection to/from a field of 380 EmPs, with a relative distance varying from 1 to 2 m, were adopted. The integrated solution, resulting from this investigation, allowed us to overcome the standard barriers of similar geological settings, such as the lack of groundwater for shallow geothermal energy exploitation, the lack of space for borehole heat exchanger drilling, the waste of solar heat during the warm season, etc., and it can pave the way for similar renewable and low carbon emission hybrid applications as well as contribute to the creation of smart buildings/urban areas.

Social Aspects of Smart Urban Mobility

There is a growing interest in sustainable urban transport solutions in cities around the world. These changes, known as “smart urban mobility”, aim to reduce the negative effects of transport on the natural environment and enhance the standard of living for urban dwellers. It should be noted that in addition to this transformation’s technological aspects, modifying the city’s structure and architecture also has a social dimension. The transformation of urban mobility has a significant impact on social relations. Introducing new modes of transport, such as city bikes and electric scooters, creates new ways of moving around the city and can impact social interactions. This can increase social integration and a community’s sense of belonging. At the same time, it is necessary to consider the differences between social groups to ensure equal access to the benefits of these changes in addition to deeper social elements, such as changing the habits and expectations of residents and adapting solutions to the specific needs of each city. This paper aims to look at the social aspects of smart urban mobility, including the impact of these changes on the lives and relationships of city residents.

Revitalizing Ukrainian Cities: The Role of Public-Private Partnerships in Smart Urban Development

Purpose: The article examines the role of public-private partnership (PPP) as a key tool for urban infrastructure restoration and the development of Ukrainian cities within the framework of the Smart City concept. It underscoresthe urgent need for effective mechanisms to restore urban infrastructure, especially in light of the challenges associated with the Russian military aggression and the resulting destruction in Ukrainian cities. The study explores key aspects of smart cities development, including the integration of digital technologies, the use of data, and innovative business models aimed at optimizing city functions.Design/Methodology/Approach: The research employs a multi-stage methodological approach, encompassing elements such as gauging urban population satisfaction with municipal services, graphical analysis using CIMI, assessing the relevance of revitalizing Ukrainian cities and the need for mobilizing business resources, sociological surveys, developing a Smart City model based on PPP project outcomes, and formulating key elements of the national Smart City development strategy.Findings: Emphasizing the importance of strategic planning and cooperation between public and private sectors, the study demonstrates the advantages offered by PPP-based projects. The obtained results highlight the pivotal role of PPPs in promoting urban development initiatives basedon the Smart City concept. The study emphasises the potential of PPPs in shaping stable and prosperous smart cities in Ukraine. Through effective PPP utilisation, local governments can restore urban infrastructure,improve service quality, and enhance the quality of life for their citizens.Practical Implications: The research results can serve as the basis for strategic planning and investment in infrastructure projects necessary for the creation of a smart city. The envisioned strategy will allow for the improvement of legislative acts covering a wide range of aspects of smart cities development while promoting collaboration between public and private entities. This includes bolstering the transportation system, deploying digital technologies, modernizing social institutions, and enhancing the efficiency of urban resource management.Originality/Value: The originality and value of the study lie in its multifaceted approach to assessing and promoting the Smart City concept in Ukrainian urban development. It combines various research methods, including satisfaction assessments, CIMI-based graphical analyses, sociological surveys, and the development of a Smart City model based on PPP project results. This approach not only provides a comprehensive understanding of the state of urban infrastructure and citizen satisfaction but also offers a strategic framework for smart cities development.

Artificial intelligence of things for synergizing smarter eco-city brain, metabolism, and platform: Pioneering data-driven environmental governance

Emerging smarter eco-cities, inherently intertwined with environmental governance, function as experimental sites for testing novel technological solutions and implementing environmental reforms aimed at addressing complex challenges. However, despite significant progress in understanding the distinct roles of emerging data-driven governance systems—namely City Brain, Smart Urban Metabolism (SUM), and platform urbanism—enabled by Artificial Intelligence of Things (AIoT), a critical gap persists in systematically exploring the untapped potential stemming from their synergistic and collaborative integration in the context of environmental governance. To fill this gap, this study aims to explore the linchpin potential of AIoT in seamlessly integrating these data-driven governance systems to advance environmental governance in smarter eco-cities. Specifically, it introduces a pioneering framework that effectively leverages the synergies among these AIoT-powered governance systems to enhance environmental sustainability practices in smarter eco-cities. In developing the framework, this study employs configurative and aggregative synthesis approaches through an extensive literature review and in-depth case study analysis of publications spanning from 2018 to 2023. The study identifies key factors driving the co-evolution of AI and IoT into AIoT and specifies technical components constituting the architecture of AIoT in smarter eco-cities. A comparative analysis reveals commonalities and differences among City Brain, SUM, and platform urbanism within the frameworks of AIoT and environmental governance. These data-driven systems collectively contribute to environmental governance in smarter eco-cities by leveraging real-time data analytics, predictive modeling, and stakeholder engagement. The proposed framework underscores the importance of data-driven decision-making, optimization of resource management, reduction of environmental impact, collaboration among stakeholders, engagement of citizens, and formulation of evidence-based policies. The findings unveils that the synergistic and collaborative integration of City Brain, SUM, and platform urbanism through AIoT presents promising opportunities and prospects for advancing environmental governance in smarter eco-cities. The framework not only charts a strategic trajectory for stimulating research endeavors but also holds significant potential for practical application and informed policymaking in the realm of environmental urban governance. However, ongoing critical discussions and refinements remain imperative to address the identified challenges, ensuring the framework's robustness, ethical soundness, and applicability across diverse urban contexts.