Real Smart City Research Articles

Developing a Manufacturing Industrial Brain in a Smart City: Analysis of fsQCA Based on Yiwu Knitting Industry Platform

Developing a Manufacturing Industrial Brain in a Smart City: Analysis of fsQCA Based on Yiwu Knitting Industry Platform

Addressing Data Challenges to Drive the Transformation of Smart Cities

Cities serve as vital hubs of economic activity and knowledge generation and dissemination. As such, cities bear a significant responsibility to uphold environmental protection measures while promoting the welfare and living comfort of their residents. There are diverse views on the development of smart cities, from integrating Information and Communication Technologies into urban environments for better operational decisions to supporting sustainability, wealth, and comfort of people. However, for all these cases, data is the key ingredient and enabler for the vision and realization of smart cities. This article explores the challenges associated with smart city data. We start with gaining an understanding of the concept of a smart city, how to measure that the city is a smart one, and what architectures and platforms exist to develop one. Afterwards, we research the challenges associated with the data of the cities, including availability, heterogeneity, management, analysis, privacy, and security. Finally, we discuss ethical issues. This article aims to serve as a “one-stop shop” covering data-related issues of smart cities with references for diving deeper into particular topics of interest.

Functional Optimization of Smart Street Lamp via Hybrid Kano-DEMATEL Model: A Case Study on Hebi Area, China

World's major cities are rapidly advancing towards the development of smart cities. Smart street lamps, due to their integration and systematization, have become among the most promising physical infrastructure for realizing smart city construction. However, current smart street lamps face challenges. The function setting of smart street lamps is a prominent challenge. Research how to optimize function settings to enhance cost-effectiveness and practicality is crucial. However, existing research in this area is limited. This paper proposes a novel approach that leverages the strengths of the Kano model and the DEMATEL method, culminating in the establishment of a hybrid Kano-DEMATEL Model for comprehensively ranking smart street lamp functions. The model comprises four layers: the target layer, the Kano criterion layer, the DEMATEL criterion layer, and the requirements sorting table layer. The ordering strategy involves using the Kano model as the primary criterion and complementing it with the DEMATEL method as the secondary criterion. The model operates with specific rules as follows: The target layer serves as the product requirements iteration strategy. The Kano criteria layer is used to initially prioritize product requirements, following the order of M > O > A > I, and retaining only essential, expected, and attractive attributes. The DEMATEL criteria layer identifies key requirements and their interrelationships using the Centrality-Causality Map method. Further prioritization is conducted based on the DEMATEL quadrant order: Quadrant I > Quadrant II > Quadrant III > Quadrant IV. Within the same DEMATEL quadrant, requirements are ranked by centrality from high to low. After qualitative and quantitative dual sorting of all requirements, a requirement prioritization table is established. This model brings clarity to the importance of optimizing various indicators, provides a clearer understanding of the strengths and weaknesses of product functions, and considers correlations and complementarities between different functions, ultimately enhancing the cost-effectiveness and practicality of smart street lamps. By applying this model, this paper obtained a thorough ranking of the 21 must-be, expected, and attractive functions of smart street lamps. Furthermore, aligning these findings with specific regional research requirement, the functions of new smart street lamps were successfully optimized in the Hebi area, leading to substantial improvements and successful construction outcomes.

Gauging Public Acceptance of Conditionally Automated Vehicles in the United States

Public acceptance of conditionally automated vehicles is a crucial step in the realization of smart cities. Prior research in Europe has shown that the factors of hedonic motivation, social influence, and performance expectancy, in decreasing order of importance, influence acceptance. Moreover, a generally positive acceptance of the technology was reported. However, there is a lack of information regarding the public acceptance of conditionally automated vehicles in the United States. In this study, we carried out a web-based experiment where participants were provided information regarding the technology and then completed a questionnaire on their perceptions. The collected data was analyzed using PLS-SEM to examine the factors that may lead to public acceptance of the technology in the United States. Our findings showed that social influence, performance expectancy, effort expectancy, hedonic motivation, and facilitating conditions determine conditionally automated vehicle acceptance. Additionally, certain factors were found to influence the perception of how useful the technology is, the effort required to use it, and the facilitating conditions for its use. By integrating the insights gained from this study, stakeholders can better facilitate the adoption of autonomous vehicle technology, contributing to safer, more efficient, and user-friendly transportation systems in the future that help realize the vision of the smart city.

Assessing Factors Influencing Citizens’ Behavioral Intention towards Smart City Living

The adoption and results achieved by “smart city” projects heavily rely on citizens’ acceptance and behavioral intention to embrace smart city living. Understanding the factors influencing citizens’ behavioral intention towards smart city living is crucial for the effective development and rollout of smart city initiatives. This research paper aims to assess the factors influencing citizens’ behavioral intention towards smart city living using quantitative research methods. Through a comprehensive literature review, an ideation structure was developed, integrating theoretical perspectives from the Technology Acceptance Model (TAM). The structure encompasses key variables such as perceived utility, convenience of use, engagement, trialability, observability, interoperability, willingness, and propensity to embrace smart city lifestyles. A quantitative methodological stance was employed to gather information from a statistically significant subset of citizens residing in urban areas in developed countries. A structured questionnaire, based on the theoretical framework, was formulated and distributed to the participants. Statistical analysis techniques, including structural equation modeling, were used for investigating connections between identified factors and citizens’ behavioral intention towards smart city living. Preliminary findings indicate that behavioral intention towards smart city living strongly depends on attitude and perceived usefulness. By addressing these factors, smart cities can foster greater citizen engagement, participation, and ultimately, the successful realization of smart city living.

Assessment of Leica CityMapper-2 LiDAR Data within Milan’s Digital Twin Project

The digital twin is one of the most promising technologies for realizing smart cities in terms of planning and management. For this purpose, Milan, Italy, has started a project to acquire aerial nadir and oblique images and LiDAR and terrestrial mobile mapping data. The Leica CityMapper-2 hybrid sensor has been used for aerial surveys as it can capture precise and high-resolution multiple data (imagery and LiDAR). The surveying activities are completed, and quality checks are in progress. This paper concerns assessing aerial LiDAR data of a significant part of the metropolitan area, particularly evaluating the accuracy, precision, and congruency between strips and the point density estimation. The analysis has been conducted by exploiting a ground control network of GNSS and terrestrial LiDAR measurements created explicitly for this purpose. The vertical component has an accuracy root mean square error (RMSE) of around 5 cm, and a horizontal component of around 12 cm. Meanwhile, the precision RMSE ranges from 2 to 8 cm. These values are suitable for generating products such as DSM/DTM.

Statistical Building Energy Model from Data Collection, Place-Based Assessment to Sustainable Scenarios for the City of Milan

Building energy modeling plays an important role in analyzing the energy efficiency of the existing building stock, helping in enhancing it by testing possible retrofit scenarios. This work presents an urban scale and place-based approach that utilizes energy performance certificates to develop a statistical energy model. The objective is to describe the energy modeling methodology for evaluating the energy performance of residential buildings in Milan; in addition, a comprehensive reference dataset for input data from available open databases in Italy is provided—a critical step in assessing energy consumption and production at territorial scale. The study employs open-source software QGIS 3.28.8 to model and calculate various energy-related variables for the prediction of space heating, domestic hot water consumptions, and potential solar production. By analyzing demand/supply profiles, the research aims to increase energy self-consumption and self-sufficiency in the urban context using solar technologies. The presented methodology is validated by comparing simulation results with measured data, achieving a Mean Absolute Percentage Error (MAPE) of 5.2%, which is acceptable, especially considering city-scale modeling. The analysis sheds light on key parameters affecting building energy consumption/production, such as type of user, volume, surface-to-volume ratio, construction period, systems’ efficiency, solar exposition and roof area. Additionally, this assessment attempts to evaluate the spatial distribution of energy-use and production within urban environments, contributing to the planning and realization of smart cities.

Efektivitas Penerapan E-Government Dalam Mewujudkan Smart City Di Kabupaten Tapanuli Selatan

In the current era of globalization and digital, fast, precise and accurate information services are needed. One of the technologies that must be applied in government agencies is the implementation of e-government which refers to the development of national e-government, and is adapted to the conditions that exist in each government agency. The aim of this e-government is to improve the quality of service and especially to realize the smart city which is currently being discussed. One of the districts that has recently implemented a smart city is the South Tapanuli district. So that in this study an analysis of the application of e-government in realizing smart cities will be carried out with the aim of knowing the process of implementing e-government policies, implementing smart cities that focus on the community, and to find out the obstacles or obstacles in the implementation of e-government. The results of the study explain that the implementation of e-government in South Tapanuli district is indeed very effective in realizing smart cities in the midst of increasingly sophisticated technological developments. This is shown by the achievement of smart city aspects, although not optimal. In the implementation of e-government there are still a number of weaknesses, obstacles and challenges because the implementation in South Tapanuli district is still relatively new. These obstacles include the inadequate availability of human resources, the level of public capacity regarding e-government is still very low. Supporting factors for e-government implementation are full government support through regulations and established financial support.

Software Engineering Techniques for Building Sustainable Cities with Electric Vehicles

As the process of urbanization continues to accelerate, the demand for sustainable cities has become more critical than ever before. The incorporation of electric vehicles (EVs) is a key component in creating sustainable cities. However, the development of smart cities for EVs entails more than just the installation of charging stations. Software engineering plays a crucial role in realizing smart cities for electric vehicles. This paper examines the role of software engineering in the creation of smart cities for electric vehicles, the techniques utilized in electric vehicle charging infrastructure, the obstacles faced by software engineers, and the future of software engineering in sustainable cities. Specifically, the paper explores the significance of software engineering in integrating EVs into the transportation system, including the design of smart charging and energy management systems, and the establishment of intelligent transportation systems. Additionally, the paper offers case studies to demonstrate successful software engineering implementations for smart cities. Finally, the paper concludes with a discussion of the challenges that software engineers encounter in implementing intelligent transportation systems for EVs and provides future directions for software engineering in sustainable cities.

Blockchain Applications in Sustainable Smart Cities

Sustainable smart cities aim to optimize projected complexities, costs, and environmental challenges accompanied by growing urbanization. The fundamental objectives of sustainable smart cities are to ingeniously utilize available resources and knowledge systems to provide excellent services and the finest quality of life to its citizens. The intelligent use of Information and Communication Technologies (ICT) plays a vital role in realizing smart cities. The purpose of this work is to investigate the role of blockchain technology (BCT) in sustainable smart city applications by providing a detailed study of blockchain applications in the food supply chain, tourism industry, smart healthcare system, intelligent transportation system, next-generation 5G and 6G communication, and smart energy management. Moreover, a statistical study regarding selected articles shows the significance of the underlying study. Finally, a summary of recent trends, challenges, and future research directions is presented for the BCT role in sustainable smart cities.

Analisis Sistem Sadar Lingkungan (Sidarling) Melalui Perspektif E-Government di Kota Denpasar

Globalization provides changes and challenges in utilizing knowledge and technology. Digitalization is expected to be able to be integrated into solving various public problems, one of which is providing public services and realizing smart cities. The waste problem often becomes a public polemic in its solution; this has become the concern of the Denpasar City government by presenting an innovative waste management system. SIDARLING (Information System Awareness and Concern for the Environment) is a form of waste management effort that invites urban residents to save their household waste through a web-based system and mobile application. The focus of this study is to analyze SIDARLING as a form of public service from an e-government perspective. This study used a qualitative descriptive method with data collection techniques through observation and literature study, as well as conducting qualitative data analysis. The results of the study show that SIDARLING is a form of e-government-based public service that focuses on waste management. Theoretically, it shows that SIDARLING has fulfilled the support, capacity, and value elements of its sustainability. This system is a form of government governance in the form of a new public service in digital-based waste management in Denpasar City.

Understanding Smart City Practice in Urban China: A Governance Perspective

Through an evolution from an emerging marketing narrative to a geographical fact around the globe, smart city is increasingly understood as a city’s effort to make itself smart. There seems no single city in the world to be commonly recognized as a real smart city yet, albeit many cities have already tried hard in this missionary commitment. Yet some common features can still be seen and identified, particularly from the urban governance perspective. This article explores the practice of smart city construction in China through a lens of governance by observing the interactive involvement of key stakeholders in the process. By taking three cities (Hangzhou, Wuhan, and Shanghai) in China as study cases, a conceptual framework is established in which three sets of actors, i.e., ICT-related enterprises, government, and civil society, and, accordingly, three types of approaches, i.e., ICT-led, planning-led, and place-making-and-community-oriented, are identified. It is found that the evolution of smart city construction rather follows a nonlinear trajectory and is very dependent on whether or not the primary actors and related stakeholders can form an affirmative acting power in triggering the city’s implementation. In other words, there is no “one-size-fits-all” approach to smart city construction. Each city may have its specialization in smartness based on awareness of and respecting its unique existing setting. The empirical study also shows that smart city construction tends to be converged in recognition that the core of smart city is not the smartness of technology but the smartness of all institutions and people enabled to utilize smart tools properly and efficiently in pursuit of people’s well-being, institutional capacity building, and better spatial arrangement towards a sustainable, resilient, and inclusive city in and for the future. From a geographical perspective, that is how to build a smart urban space to make the city a better place to not just accommodate but facilitate and meet people’s increasing demand for a better life in their living places.

Demystifying the Role of Natural Language Processing (NLP) in Smart City Applications: Background, Motivation, Recent Advances, and Future Research Directions.

Smart cities provide an efficient infrastructure for the enhancement of the quality of life of the people by aiding in fast urbanization and resource management through sustainable and scalable innovative solutions. The penetration of Information and Communication Technology (ICT) in smart cities has been a major contributor to keeping up with the agility and pace of their development. In this paper, we have explored Natural Language Processing (NLP) which is one such technical discipline that has great potential in optimizing ICT processes and has so far been kept away from the limelight. Through this study, we have established the various roles that NLP plays in building smart cities after thoroughly analyzing its architecture, background, and scope. Subsequently, we present a detailed description of NLP's recent applications in the domain of smart healthcare, smart business, and industry, smart community, smart media, smart research, and development as well as smart education accompanied by NLP's open challenges at the very end. This work aims to throw light on the potential of NLP as one of the pillars in assisting the technical advancement and realization of smart cities.

ANALISIS PELUANG DAN TANTANGAN PEMERINTAH KOTA MEDAN DALAM MENGIMPLEMENTASIKAN SDG TUJUAN 11 DI TINGKAT LOKAL (STUDI KASUS MEDAN SMART CITY)

SDGs implementation by the local government is an interesting study driven by the fact that since the implementation of decentralization policy in Indonesia, the fate and quality of life of the people, in practice, have been mostly determined by the performance of the local government at the district/city level. Geographically, Medan City is the gateway to the western part of Indonesia and bordering the Strait of Malacca, making Medan an important city of trade, industry, and business in Indonesia. This city profile requires an integrated system that can facilitate government tasks and activities of the wider community, which can be supported by the development of Medan Smart City which is also in line with the National Strategy Policy for e-Government Development in 2003. This research uses qualitative methods based on data obtained through field studies and literature studies. The position of this article seeks to examine the role and capacity of the Medan City Government in implementing SDG-Goal 11 concerning the realization of inclusive and sustainable cities through the concept of smart city which has been widely applied in variouscountries and other big cities in Indonesia. This research shows that the means of implementation including funding, technology transfer, and human resources capacity building, which are the keys to the success of the program, have been becoming challenges for the Medan City Government in realizing smart city as a means to achieve sustainable city.

A Transfer Learning Framework for Predictive Energy-Related Scenarios in Smart Buildings

Human activities and city routines follow patterns. Transfer learning can help achieve scalable solutions toward the realization of smart cities accounting for similarities between regions, domains, and activities. In this study, we propose a transfer learning-based framework for smart buildings to test this hypothesis in energy-related problems. Our framework has two major components: the network creation and the transferable predictive model. In order to create the network that groups buildings sharing characteristics, we evaluated two strategies: a novel clustering algorithm for mixed data, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> -prod, and clustering the image-based representation of time series. Then, a combination of long short term memory and convolutional neural network was trained on the centroids of the clusters for energy consumption prediction. The coefficient of variation of the root mean squared error (CVRMSE) of the predictions in such clusters vary between 3.85% and 58.85%. The obtained parameters were transferred to the rest of the buildings for predictive purposes, finding accurate results in buildings with little data. Our framework deals with insufficient training data since parameters from scenarios with more sensors can be received. It also carries out state-of-the-art performance on three datasets from different sources having in total 533 rooms/buildings and two energy efficiency domains: consumption prediction reducing the CVRMSE in a 21.6%, and air conditioning usage prediction moving from a 4.18% to a 0.28% CVRMSE. Our framework extracts more knowledge from available IoT deployments, so that smartness could be spread between environments at a fewer cost given that less individual effort will be needed.

Smart City Architecture Development Framework (SCADEF)

Smart City is a city that implements the latest technologies, such as big data, IoT, Artificial Intelligence, and other new technologies. Smart City has different system characteristics than other systems. Smart City involves several independent stakeholders, so the development of a smart city needs to be designed with a system analysis system and service-based planning. Smart City Architecture Development Methodology (SCADM) has been defined from the previous research. However, the existing Enterprise Architecture approach has yet to specify the artefact to complete the framework. This study recommends the Smart City Architecture Framework (SCADEF) as a comprehensive Enterprise Architecture Framework to develop Smart City Architecture. The architecture framework produced by SCADEF becomes the proposed architecture framework for realizing Smart City. SCADEF consists of SCADM, Meta-model Smart City Architecture Development Methodology Artefact, and guidelines by the implementation SCADEF. The research uses observation, classification, and construction methodologies in Information System Design Methodology. In addition, this study also tested the framework by implementing it on city objects. This implementation is a practical test tool for the resulting enterprise architecture framework. This study implemented SCADEF in the education and health field at Bandung Smart City. Implementing testing on the implementation of SCADEF is to explain the implementation in Bandung Smart City and ask for an assessment from enterprise architecture experts. The results of the expert assessments were calculated statistically to assess the methodology, artefacts, and uses. The measurement results show that SCADEF can be accepted and used to develop enterprise smart city architecture.

Toward explainable electrical load forecasting of buildings: A comparative study of tree-based ensemble methods with Shapley values

Electrical load forecasting of buildings is crucial in designing an energy operation strategy for smart city realization. Although artificial intelligence techniques have demonstrated excellent energy forecasting performance, explaining how outcomes are obtained when they are inaccurate is challenging. Explainable artificial intelligence (XAI) has recently received considerable attention in addressing this issue. This study proposes an explainable electrical load forecasting (XELF) methodology. We first preprocess data for input variable configuration and build the following tree-based ensemble models that produce outstanding results in tabular data: random forest, gradient boosting machine (GBM), extreme gradient boosting, light GBM (LightGBM), and categorical boosting. We evaluate performance in terms of the mean absolute percentage error, coefficient of variation of the root mean square error, and normalized mean absolute error. Finally, we provide the rationale for interpreting the influence of the input variables and decision-making process via Shapley additive explanations (SHAP), an XAI technique, on the best model. The experiments were conducted with an electrical load dataset from educational buildings to validate the practicality and validity of this methodology. We applied the SHAP to the LightGBM model and performed its respective analyses and visualizations for XELF.

THE IMPORTANCE OF SMART URBAN PLANNING FOR THE CONSTRUCTION OF SMARTS CITIES

This article has smart cities as its theme and aims to identify the role and importance of urban planning as an instrument for the realization of smart cities. This research is bibliographical and presents the historical context of urban planning as well as concepts of sustainability, security and egalitarian distribution within this scenario, advancing to the concepts of smart cities, their definitions and how they relate to urban planning. The study presents and reflects on the importance of the smart urban planning tool as a protagonist for the construction of really effective smart cities in the promotion of sustainable, safe cities that provide well-being for their inhabitants.

Design and Implementation of SEMAR IoT Server Platform with Applications.

Nowadays, rapid developments of Internet of Things (IoT) technologies have increased possibilities of realizing smart cities where collaborations and integrations of various IoT application systems are essential. However, IoT application systems have often been designed and deployed independently without considering the standards of devices, logics, and data communications. In this paper, we present the design and implementation of the IoT server platform called Smart Environmental Monitoring and Analytical in Real-Time (SEMAR) for integrating IoT application systems using standards. SEMAR offers Big Data environments with built-in functions for data aggregations, synchronizations, and classifications with machine learning. Moreover, plug-in functions can be easily implemented. Data from devices for different sensors can be accepted directly and through network connections, which will be used in real-time for user interfaces, text files, and access to other systems through Representational State Transfer Application Programming Interface (REST API) services. For evaluations of SEMAR, we implemented the platform and integrated five IoT application systems, namely, the air-conditioning guidance system, the fingerprint-based indoor localization system, the water quality monitoring system, the environment monitoring system, and the air quality monitoring system. When compared with existing research on IoT platforms, the proposed SEMAR IoT application server platform offers higher flexibility and interoperability with the functions for IoT device managements, data communications, decision making, synchronizations, and filters that can be easily integrated with external programs or IoT applications without changing the codes. The results confirm the effectiveness and efficiency of the proposal.

Bandung Cooperation with Braunschweig (Germany) in Realizing Smart City

The Bandung City has carried out various international cooperations to obtain investments in the long or short term, support for infrastructure development, youth exchanges, cooperation in culture, and receipt of fees and grant funds. One of the various cooperations is the efforts of Bandung in paradiplomacy through the sister city concept. This study is necessary because Bandung and Braunschweig have carried out the Sister City Program from 1960 to 2021. This research is a descriptive study with a qualitative approach, examining why Bandung maintains cooperation with Braunschweig (Germany), running for more than 40 years. This article employed data collected from journals, news in the mass media, and information from the official websites of related parties as supporting references. In answering the research question, the author utilized the concepts of smart city and sister city. This study discovered that Bandung maintained its cooperation with Braunschweig due to its interest in building a smart city.