Smart City Development Research Articles

Expediting decarbonization in energy, waste, and water sector through digitalization in sustainable smart cities (SSC): Case-studies in Malaysia and China based on Industry 5.0 paradigm

This work explores the application of Industry 5.0 principles in smart cities development in Malaysia and China, focusing on digital transformation for sustainable urban development. The study presents case-studies from both the countries, highlighting the implementation strategies, challenges, and outcomes associated with integrating advanced technologies to enhance efficiency, climate resilience, and sustainability. This study aims to develop a data-driven methodology to address the absence of region-specific frameworks for sustainable smart cities (SSCs) and to evaluate their impacts. In Malaysia, the implementation of smart energy management systems that utilize IoT and AI has shown promise in reducing carbon footprints and maximizing resource efficiency. China's focus on smart water management using sensor networks and real-time data analytics provides insights into effective water conservation. Smart waste management systems have increased recycling rates by 20-30%. Progress is crucial for the region's pursuit of SSCs to reach a global investment of USD 2.5 trillion by 2025. This work concludes by discussing the implications of this work in both countries to achieve sustainable urbanization through Industry 5.0 technologies. This work offers recommendations for policymakers, urban planners, and technologists to navigate the complexities of smart city development, while providing a roadmap to leverage digital transformation to achieve decarbonization goals in energy, waste and water sector by 2060.

Innovative Transitions: Exploring Demand for Smart City Development in Novi Sad as a European Capital of Culture

This study investigates the factors influencing the acceptance and implementation of smart city solutions, with a particular focus on smart mobility and digital services in Novi Sad, one of the leading urban centers in Serbia. Employing a quantitative methodology, the research encompasses citizens’ perceptions of the benefits of smart technologies, their level of awareness regarding smart solutions, the degree of engagement in using digital services, and their interest in smart mobility. The results indicate that these factors are crucial for the successful integration of smart technologies. Notably, awareness of smart city initiatives and the perceived benefits, such as improved mobility, reduced traffic congestion, increased energy efficiency, and enhanced quality of life, are highlighted as key prerequisites for the adoption of these solutions. Novi Sad, as the European Capital of Culture in 2022, presents a unique opportunity for the implementation of these technologies. Our findings point to the need for strategic campaigns aimed at educating and raising public awareness. The practical implications of this study could contribute to shaping policies that encourage the development of smart cities, not only in Novi Sad but also in other urban areas across Serbia and the region. This study confirms the importance of citizen engagement and technological literacy in the transformation of urban environments through smart solutions, underscoring the potential of these technologies to improve everyday life and achieve sustainable urban development.

Measuring the Effectiveness of the ‘Batch Operations’ Energy Design Pattern to Mitigate the Carbon Footprint of Communication Peripherals on Mobile Devices

The Internet of Things (IoT) is set to play a significant role in the future development of smart cities, which are designed to be environmentally friendly. However, the proliferation of these devices, along with their frequent replacements and the energy required to power them, contributes to a significant environmental footprint. In this paper we provide scientific evidences on the advantages of using an energy design pattern named ‘Batch Operations’ (BO) to optimize energy consumption on mobile devices. Big ICT companies like Google already batch multiple API calls instead of putting the device into an active state many times. This is supposed to save tail energy consumption in communication peripherals. To confirm this, we set up an experiment where we compare energy consumption and carbon emission when BO is applied to two communication peripherals on Android mobile device: 4G and GPS. Results show that (1) BO can save up to 40% energy when sending HTTP requests, resulting in an equivalent reduction in CO2 emissions. (2) no advantages for the GPS interface.

Parking Assistant with the Simulation of Application

Smart Parking can be used for any city. It aims to improve the efficiency and sustainability of urban transportation systems by using technology to manage parking systems. This article provides an overview of the different components of smart parking systems. The increasing vehicular population in urban areas has led to significant challenges related to parking management, exacerbating traffic congestion, environmental impact, and user dissatisfaction. The app facilitates real- time information on available parking spaces, reservation capabilities, and payment integration, thereby enhancing user experience and operational efficiency. We summarize the methodologies applied in developing the app, which include sensor integration for dynamic parking space monitoring and mobile application development for user interaction. The article concludes with a consideration of the future of smart parking and its role in the overall development of smart cities. In conclusion, the findings serve as a basis for future advancements in intelligent parking systems, ensuring improved service delivery for urban commuters.

A Cross-Layer Secure and Energy-Efficient Framework for the Internet of Things: A Comprehensive Survey

This survey delves into cross-layer energy-efficient solutions and cutting-edge security measures for Internet of Things (IoT) networks. The conventional security techniques are considered inadequate, leading to the suggestion of AI-powered intrusion detection systems and novel strategies such as blockchain integration. This research aims to promote the development of smart cities by enhancing sustainability, security, and efficiency in the industrial and agricultural sectors through the use of IoT, blockchain, AI, and new communication technologies like 5G. In this paper, we provide a comprehensive review and analysis of secure and energy-efficient cross-layer IoT frameworks based on survey of more than 100 published research articles. We highlight the significance of developing IoT security for robust and sustainable connected systems. We discuss multi-layered security approaches and ways to enhance the energy efficiency of resource-constrained devices in IoT networks. Finally, we identify open research issues and future research directions in the emerging field of cross-layer design for secure and energy-efficient IoT networks. In order to improve cybersecurity and efficiency in smart cities, the research also focuses on developing a secure, energy-efficient IoT framework integrating blockchain, artificial intelligence, and quantum-safe cryptography.

Integrating computer technology and policy management for sustainable smart city development

Abstract. This paper presents the development and application of a machine learning-based Environmental, Social, and Governance (ESG) performance evaluation model. The model quantifies and assesses the ESG performance of companies, enabling them to identify strengths and weaknesses in their sustainability efforts. By leveraging advanced machine learning techniques, the model offers accurate and comprehensive insights into ESG performance, guiding companies in formulating effective improvement strategies. The study involves detailed data collection and preprocessing, model construction and training, and rigorous evaluation metrics to ensure reliability and effectiveness. Additionally, the paper discusses practical applications of the model in strategic decision-making, resource allocation, and enhancing stakeholder engagement. The findings highlight the importance of integrating technology with ESG considerations to drive sustainable business practices. This research provides a robust framework for ESG performance assessment and sets the stage for future advancements in this critical area.

Urban Transportation Data Research Overview: A Bibliometric Analysis Based on CiteSpace

Urban transportation data are crucial for smart city development, enhancing traffic management’s intelligence, accuracy, and efficiency. This paper conducts a comprehensive investigation encompassing policy analysis, a literature review, concept definition, and quantitative analysis using CiteSpace from both domestic and international perspectives. Urban transportation data comprise multiple dimensions, such as infrastructure status, real-time monitoring, policy planning, and environmental assessment, which originate from various sources and stakeholders. Highly influential authors and active institutions, particularly in the USA, China, Canada, and England, contribute significantly to extensive and collaborative research. Key areas include intelligent transportation, traffic flow prediction, data fusion, and deep learning. Domestic research focuses on practical applications, while international studies delve into interdisciplinary research areas. With advancements in intelligent systems and big data technology, research has evolved from basic data collection to sophisticated methodologies, such as deep learning and spatiotemporal analysis, driving substantial progress. This paper concludes by recommending enhanced data integration, improved privacy and security, fostering big data and AI applications, facilitating policy formulation, and exploring innovative transportation modes, thereby underscoring the importance of urban transportation data in shaping the future of smart cities. The findings provide theoretical and practical guidance for the future intelligence, efficiency, and sustainability of urban transportation systems.

Multi-class Object Detection in Urban Scenes Based on Deep Learning

Abstract. The rapid development of urbanization presents challenges and requirements for multi-class object detection in urban scenes. Accurately identifying buildings, vehicles, and trees in urban scenes can optimize urban planning, traffic management, monitoring environmental conditions, and promote the development of smart cities. Traditional target detection methods perform poorly in complex urban environments, while deep learning technology achieves accurate target recognition and positioning by automatically extracting high-level semantic features. In this study, we chose to use the YOLOv5s algorithm for multi-class target detection in urban scenes. YOLOv5s is a lightweight deep learning model with small storage space and efficient detection speed. In this paper, the Potsdam area data published by ISPRS is used to make the label data of buildings, vehicles and trees. The YOLOv5s algorithm is used to iteratively train the model. The results show that the mAP value detected by the YOLOv5s model can reach 82.83%. The experimental results show that the algorithm shows higher accuracy than SSD and Faster R-CNN in tree detection. Although it has a slight decline in building and vehicle detection, considering the factors such as detection accuracy, speed, and model size, the YOLOv5s algorithm has a better recognition and detection effect for the detection of multi-class targets in urban scenes.

Evaluating the Smart City Status and Acceptance of ISO Standards: A Case Study of Malaysian Local Authority

While most national smart city frameworks outline the urban challenges, local authorities struggle to translate the top-down plan and align the action plan with ISO 37122 indicators, including the case of Majlis Bandaraya Diraja Klang (MBDK), Malaysia. This study aims to evaluate MBDK’s smart city status and examines the acceptance of ISO standards. The quantitative survey findings indicate a positive perception of smart city status, with unanimous agreement on the importance of ISO standards. This research contributed to one of the pioneer studies evaluating the acceptance of ISO indicators in smart city development in Malaysia and beyond.

사회적 자본을 중심으로 찾아본 스마트도시 리빙랩의 성공 요인 분석

In the era of the Fourth Industrial Revolution, modern society is evolving beyond an information society into a hyperconnected society, with the advancement of technology leading to the development of smart cities. According to Cohen (2015), the direction of smart city evolution is shifting from a technology-driven approach to a citizen co-creation model, and living labs play a crucial role in this transition. The objective of this study is to empirically analyze the success factors of living labs in smart cities using the citizen co-creation approach, focusing on social capital. Social capital is measured by variables such as interest, networks, trust, and norms, while the success factors of living labs are analyzed through variables like communication, democracy (conflict acceptance), and open innovation. The analysis results showed that, among the success factors of living labs, communication was positively influenced by trust, norms, and networks, with trust having the greatest impact. Democracy (conflict acceptance) was positively influenced by norms and interest, while open innovation was positively influenced by norms and interest as well. This study concludes that the formation of social capital is crucial for the success of living labs in smart cities following the citizen co-creation model. In particular, the formation of trust among neighbors, colleagues, national and local governments is vital. Additionally, adherence to laws, regulations, and community agreements, as well as interest in various local events and policies, are essential. Based on these findings, this study suggests that while smart cities may have originated from technology, they must ultimately be pursued based on people-centered participation, interest, and trust for sustainable development.

Public Participation in Rapid Response Services for the Sustainability of Jakarta Smart City

Public participation plays an important role in the development of rapid response services to support the sustainability of Jakarta Smart City. This study aims to explore and analyse the level of public participation in utilising and developing these services, and their impact on urban sustainability. The research method used is a qualitative case study through in-depth interviews and document analysis. The results of the study indicate that the level of public participation in rapid response services in Jakarta Smart City varies greatly. Factors such as accessibility, trust, and awareness are the main determinants of the level of public participation. Citizens who actively participate tend to feel greater benefits from these services, while those who are inactive tend to experience gaps in services. Public participation also has a positive effect on service efficiency and the quality of life of city residents. However, this study also found several obstacles that hinder public participation. Low awareness of the importance of the role of individuals in developing smart cities, limited accessibility, and low digital literacy are the main challenges. To increase sustainable public participation, efforts are needed that involve education, training, and strengthening of information technology infrastructure. In conclusion, public participation has a crucial role in the sustainability of Jakarta Smart City through rapid response services. Effective management of public participation can improve service efficiency, strengthen community engagement, and support sustainable urban development. Therefore, continuous efforts are needed to improve and manage public participation for long-term success. With education, training, and improved technological infrastructure, broader and more equitable participation can be realised, supporting the growth of inclusive and sustainable smart cities in the future.

Smart Cities and Human Development: Analysis Using Fuzzy Similarity Measures

Smart Cities and Human Development: Analysis Using Fuzzy Similarity Measures

The Dynamics of the Smart City Development: From the First Wave Model to the Third Wave Model

The Dynamics of the Smart City Development: From the First Wave Model to the Third Wave Model

Exploring best practices in smart public library services: a survey

Purpose This paper aims to the integration of smart cities and technologies has had a profound impact on public library services globally. However, debates continue about how public libraries are incorporating smart technologies and tools, and what this means for their role in smart city development. This paper explores how public libraries are evolving to meet community needs by providing both physical and digital services. Design/methodology/approach The purpose of this study is to assess the role of public libraries in the smart cities and how they are aligning toward development of smart concepts, technologies, services such as contributions to smart city objectives, community impact, the digital divide, unique projects and readiness for future smart city advancements. So, the authors explored 11 public library systems of cities across the world implementing smart city projects. Findings The authors found that all the library systems offer extensive print and digital collections, sustainable buildings and a well-connected network of branches. They provide self-checkout services, makerspaces equipped with 3D printing and coding workshops and advanced recording and video editing technologies. Furthermore, these libraries function as community centers, serving diverse groups including children, women, the elderly and marginalized communities. They function as third spaces that foster lifelong learning and digital literacy. Originality/value Although smart cities face substantial debate regarding their features, tools and feasibility, public libraries have adapted and redefined their roles to become influential public institutions. They now play a crucial part in supporting vibrant and dynamic communities and neighborhoods within smart cities.

High‐Accuracy Liquid Flow Monitoring via Triboelectric Nanogenerator Combined with Bionic Design and Common‐Mode Interference Suppression

AbstractIn the development of smart cities, accurate liquid flow monitoring is essential for the efficient operation of water supply systems. Current flow sensors often face limitations in sensitivity and environmental adaptability, affecting measurement accuracy, and restricting their application in smart city infrastructure. To address these challenges, this study proposes a high‐accuracy flow monitoring method. Specifically, by combining the bionic design with advanced signal processing techniques, the sensitivity and anti‐interference ability are improved, respectively, to enhance the measurement accuracy. Based on this method, a self‐powered flow sensor (SPFS) is developed using noncontact triboelectric nanogenerators (NC‐TENGs) as the sensing unit. The SPFS achieves a sensitivity of 2.07 Hz L−1 min−1 and improves the signal‐to‐noise ratio by more than 13 times over the initial sensing signal. In addition, an intelligent system is developed to accurately measure water resources. The maximum flow rate error rate is less than 0.97% compared to commercial flow sensors. The SPFS demonstrates higher sensitivity and accuracy compared to the existing TENG flow sensors. This study addresses the limitations of existing flow sensors and pioneers a novel solution for enhanced water resource management in smart cities.

How Does the Intelligent Transportation System Promote the Globalization and Digitalization of Cities: Take Tesla Autopilot System as an Example

The globalization and digitization of smart transportation and cities are facilitated by advancements like Teslas autonomous driving technology, which revolutionizes urban mobility. This article explores their interconnection through the example of Teslas system. Teslas Autopilot, based on deep neural networks, utilizes cameras and ultrasonic sensors to perceive the world around vehicles, encouraging data sharing between vehicles and driving global development of smart cities. It employs artificial intelligence to assess terrain and conditions, fostering a transportation revolution in traditional cities and advancing the evolution of smart cities. Moreover, Teslas digital impact is altering transportation solutions, increasing visibility in development, and driving global technological progress. Teslas unique autonomous driving technology, leveraging data from nearly one million Tesla vehicles worldwide, enhances global intelligent transportation systems, promoting global sharing among Tesla users, and facilitating the convenience of autonomous driving and the flow of global traffic information. Teslas autonomous driving mode and intelligent traffic system promote the development of smart cities, although a comprehensive analysis of its global political, economic, and legislative impacts is needed.

Incorporation of Artificial Intelligence in Enhancing Quality of Life in Smart Cities

Rapid urbanization and low residential resources in cities are serious issues that are making city life difficult day by day. The development of smart cities is becoming a need of the present era due to the swift increase in population and environmental issues globally. Smart cities are being introduced in different regions of the world with the incorporation of latest technologies. The incorporation of Artificial Intelligence (AI) is one of the tools that can be used in smart building and cities. AI technologies are transforming public safety, trash management, healthcare, traffic control, and resource management, making cities more sustainable, effective, and responsive to their citizens' demands. There are still lack of awareness in some areas of the world on the efficacy of smart building and construction that is impacting negatively on the economy and growth of those countries.; such as Pakistan is one of those countries that is facing serious challenges due to increased population, urban migration, and poor management of natural resources. The need of planning smart strategies for smart building is very crucial to manage population and housing issues. Smart buildings and cities provide unique and convenient facilities to its residents so that they can contribute positively towards the economy of country. This paper focuses at important areas where AI has the most effects in order to investigate how integrating AI improves quality of life in smart cities. The aim is to highlight artificial intelligence's contribution to improving urban operations, streamlining resource management, and advancing sustainability. Additionally, potential concerns about privacy, data security, and fair access will be discussed. In order to show how AI-driven innovations like predictive analytics, machine learning, and IoT-enabled systems are changing the urban environment, the study synthesizes existing research and real-world examples. The evaluation also covers how AI promotes smart government, tailored urban services, and citizen involvement. The conclusion emphasizes that although AI has great potential to improve the quality of life in smart cities, implementation of the technology must be done in a balanced way to prioritize inclusive policies and ethical concerns for the general welfare of residents.

Research status and development direction of smart heritage: a bibliometric review (1994-2024)

ABSTRACT Smart heritage, an emerging and sustainable paradigm, utilises technology to conserve and enhance cultural heritage. Despite integration into smart city development, full implementation remains unrealised. Consequently, this study aims to investigate the status and trends of smart heritage research, explore the development direction of smart heritage, bridge existing knowledge gaps, and guide its integration into smart city development. This study employs a bibliometric analysis method, supported by machine algorithms, to obtain scientific and quantifiable results. The study utilises the bibliometric analysis software CiteSpace 6.2R6 to analyze 981 articles from the Web of Science Core Collection, covering 1994 to 2024. We observe a notable increase in scholarly output over time, especially in smart cities and digital cultural strategies, where smart heritage has emerged as a research hotspot across various disciplines and domains. Smart heritage crosses three stages: digital technology application, technology integration, and multidisciplinary integration, showcasing diverse technological applications, service scenarios, and application domains. Moving forward, we must prioritize a comprehensive research agenda, including theoretical constructs, smart cultural infrastructure, robust policy, public engagement, and expanded application realms. Additionally, fostering interdisciplinary collaboration between international entities and driving technological innovation is vital for promoting the sustainable development of cultural heritage.

Literature Mapping on IoT Integration and Smart City: Bibliometric Analysis and Socio-Economic Impact

The integration of the Internet of Things (IoT) in smart cities has become a transformative force, revolutionizing urban development and management. This study provides an in-depth analysis of the socio-economic impacts of IoT integration in smart cities, examining its influence on economic growth, job creation, public service optimization, social inequality, privacy, security, and environmental sustainability. Through a comprehensive literature review and bibliometric analysis, we highlight the opportunities and challenges that IoT technologies present in the urban context. While IoT fosters economic growth and improves service efficiency, concerns related to data privacy, security, and the digital divide pose significant challenges. Additionally, IoT's role in promoting environmental sustainability is emphasized, as smart cities increasingly adopt technology to monitor resources and reduce carbon emissions. This study underscores the importance of addressing these socio-economic factors to ensure the equitable and sustainable development of smart cities, thereby maximizing the benefits of IoT technologies while mitigating potential risks.

Research on the Practical Path of Green Finance in the Low-carbon Transformation of Smart Cities: A Case Study of the Transformation and Development of European Smart Cities

This study aims to explore the practical path of green finance in promoting low-carbon transformation of smart cities by taking the transformation of smart cities in Europe as a case study. The successful experience of smart city transformation in Europe is deeply studied through case analysis, and the application of green finance and its impact mechanism on urban transformation are discussed. The study found that green finance plays an important role in the transformation of smart cities in Europe, which promotes the transformation of cities to lowcarbon and smart direction through the practice path of policy formulation, technological innovation and sustainable development planning. This study provides a reference for the low-carbon transformation of smart cities in other regions, and has certain theoretical and practical significance for promoting sustainable urban development.