Support Smart City Research Articles

A new enterprise architecture-based approach for smart city value co-creation

In an era marked by vertiginous technological advancements and urban complexities, digital transformation has emerged to enable cities to offer smart services. This transformation optimizes interaction and collaboration between smart city actors, instead of working in isolated silos. There is a real need for a federative approach that can be aligned with urban vision and goals to support smart city implementation. In this context, enterprise architecture (EA) is emerging as a pivotal force reshaping smart city and supporting its development and transformation. However, the successful implementation of smart city depends also on the collaborative effort to co-create value among city's stakeholders. The present study develops a new approach based on enterprise architecture within the smart city ecosystem. Through methodical delineation our approach seeks to enhance value co-creation, improve smarter service design, and support community engagement.

Evaluation of Permeability Recovery in Precast Concrete with Hybrid Capsules Using Constant-Head Permeability Test as Smart Construction Material.

This study investigates the quality characteristics and healing performance of precast concrete incorporating self-healing technology, with the aim of supporting smart city implementation. To enhance the self-healing capabilities of concrete, hybrid self-healing capsules, combining solid capsules and liquid capsules, were utilized, and their applicability and practicality were assessed. The findings revealed that incorporating hybrid self-healing capsules into precast concrete resulted in a reduction in slump by up to 14% and air content by up to 9%. Furthermore, the addition of hybrid capsules led to a maximum reduction in compressive strength of 16% and flexural strength of 18% at 28 days, while demonstrating an increase in healing efficiency as the capsule content increased. The results also indicated that the use of hybrid capsules enhanced the healing efficiency by approximately 16%, 25%, and 32% for mixing ratios of 1%, 3%, and 5%, respectively, with the overall healing efficiency ranging between 75% and 90%. Additionally, the interaction between the hybrid capsules and natural healing mechanisms promoted crystal formation around cracks, thereby significantly improving the long-term durability of the concrete.

Analysis of Smart Village Development in Supporting Smart City in Indonesia: A Systematic Review

Along with the enactment of the Law of Village in 2014, village development is a top priority on the national development agenda in Indonesia. Village development through the implementation of smart village is thought to be significant given the current state of technology’s rapid expansion. Smart village refers, generally speaking, to the implementation of the smart city idea inside the village borders. This study analyzes the concepts developed in the relationship between smart village and smart city based on a systematic literature review, compares how smart village are implemented to support smart city in various Indonesian regencies, and offers policy alternatives in the form of smart village dimensions that are more appropriate for Indonesian village conditions. Systematic literature review is used as the method for this research, with data collected from the Scopus journal database. The analysis is enriched with empirical findings based on local government policies governing smart village. The results showed that smart village development in Indonesia tends to be top-down with the initiation coming from the central and local governments. It is important to implement smart village that are in line with smart city in order to foster relationships between the two, promote village independence, and assist the smart city implementation in a complementary manner by integrating digital services and bolstering the local economy. The recommended smart village dimensions to support smart city in Indonesia consist of community, technology, institutional, and potential village resources.

Designing information system for sea transportation website in South Bangka Regency to support smart city

Abstract South Bangka is city that located in Province of Bangka Belitung Islands which using ship for support transportation because have a lot of island. The various ship is using because South Bangka have a lot of islands from small until a big island. South Bangka is experiencing difficulties in managing existing sea transportation due to the large number of ships operating without being recorded by the South Bangka transportation service. Therefore, an information system is needed that is able to manage data and information related to sea transportation in South Bangka. This ship transportation system is using the programming PhP and MySQL for the ship database used. This information system is designed to support smart city features for South Bangka Regency, because the management of sea transportation for the islands of South Bangka is centralized, digital also electronic. This information system also accessed easily by the public using smartphones and the internet to give easiness for information about ship transportation.

Trash Tide Collecting System using GSM and GPS - IOT

The accumulation of unmanaged waste poses significant health and environmental risks, especially in rapidly growing urban areas. This paper presents a smart waste monitoring system that leverages Internet of Things (IoT) technology to track waste levels in real-time and improve the efficiency of waste collection. By using ultrasonic sensors connected to IoTenabled devices, this system detects waste levels in garbage bins and sends notifications when bins require servicing. These alerts help in timely waste management, reducing overflowing bins and enhancing public cleanliness. This model’s practical implementation can contribute to a cleaner environment and support smart city initiatives

Real-time joint recognition of weather and ground surface conditions by a multi-task deep network

Climate change and the occurrence of intense and unexpected weather events highlighted the need for real-time weather warning systems, especially in smart roads and isolated scenarios like rural areas. In this work, we propose to jointly recognize the weather and the ground surface conditions using existing video surveillance systems. Previous works separately tackled these two tasks even if they are correlated to each other. We propose a convolutional neural network with shared weights in the lower layers and two separate classification branches on top to exploit the correlation between the tasks and, at the same time, learn diverse high-level features for each task. Moreover, the network architecture implements attention mechanisms allowing the classification branches to focus on diverse image regions. The method is versatile and allows us to train the network on partially labeled data. The experimental analysis on real data demonstrate the effectiveness of the proposed method on both tasks, confirmed by the accuracy comparison with existing methods for the recognition of weather and ground surface conditions. The multi-task solution improves the inference speed (50 frames per second) and reduces the required memory (less than 1 GB) with respect to a system with two different single-task approaches; these results confirm that the proposed solution is ready for video surveillance applications to support smart cities.

Human sensors in the city of super apps: mobilizing people as infrastructure for smart city development in Jakarta, Indonesia

In this paper, we argue that contextual factors such as the availability of infrastructure, sociocultural characteristics of users, governance style, and the regulatory environment in global south cities create opportunities for public and private sector actors to come up with innovative strategies for smart city development and the platformization of services. Despite different objectives, operationalization strategies, and expected outcomes between the public and private sectors, both sectors learn from one another to come up with innovative solutions for navigating contextual contingencies. Due to limited infrastructure and contextual diversities in global south cities, digital platforms require significant and specific forms of groundwork by humans that leverage their everyday networks and interactions with their surroundings. In the process of platformization, both governments and private entities strategically employ the discourse of smart, responsible citizenship to promote the innovative co-creation of platform services, thereby extending biopolitical control over citizens’ bodies and interactions. In this process, citizens are engaged as sensing nodes to support smart city development in global south cities. This paper examines two distinct cases of public and private sector ‘human sensing’ experiments in Jakarta: Jakarta Smart City’s JakLapor platform and Grab's human mapping initiative. In these experiments, ‘peopled collaborations’ (Simone 2021) between citizens are deployed by the government and the platform company as innovations where urban infrastructure is inadequate, or to fill gaps that cannot be filled by conventional digital infrastructure.

Predicting and analysing air quality in smart cities using virtual sensors

Virtual sensors have become essential in generating synthetic data to support smart city initiatives, mainly when physical sensors are absent or inaccessible. They play a crucial role in monitoring air pollutants, benefiting those with health sensitivities, and aiding city planning in the context of smart cities. This research focuses on creating reliable victual sensors for air pollutant measurement through deep learning and machine learning models, providing a cost-effective solution to address the scarcity of physical sensors and data inaccuracies. The main contribution lies in improving smart cities by providing essential health-related data to mitigate the harmful effects of air pollution on residents. Continuous monitoring empowers officials and residents to reduce pollution exposure, ultimately improving public health. The study found that gradient-boosted trees are effective for daily and hourly predictions, emphasizing the vital role of virtual sensors in advancing data-driven decision-making and improving environmental quality in smart cities. The results showed that our model was better using the boosted trees method with an RMSE of approximately 10%.

Literature Review Application of YOLO Algorithm for Detection and Tracking

A vehicle tracking system is a computer program that utilizes devices to monitor the position, movement and condition of a vehicle or fleet of vehicles. Multi-vehicle tracking on highways has significant research interest and practical value in building intelligent transportation systems. Nevertheless, traffic road video frames consist of various complex backgrounds and objects. Detection and tracking are very challenging because foreground to background switching occurs frequently. One-stage algorithm approaches such as YOLO and its various variants have been proven to be accurate for detecting vehicles. Meanwhile, the SORT, DeepSORT, ByteTrack and other algorithms can be combined in YOLO. The aim of this study is to highlight existing research on the application of YOLO and its variants in detecting and tracking vehicles, especially in traffic management. The journals used are limited to 2019 – 2024 and the journal sources consist of Hindawi, IEEE, MDPI, Research Gate, Science Direct, and Springer. Based on the research that has been reviewed, the YOLO variant algorithm approach has been successfully applied in the field of vehicle monitoring to support smart cities. In addition, many new model combinations and improvements have been proposed, proving that this algorithm has a big influence in the field of computer vision.

Green Vehicles For Sustanability In Support For Smart City Development

Green vehicles are vehicles that produce less harmful impacts to the environment than vehicles that use conventional internal combustion comparable to gasoline or diesel, or that use certain alternative fuels. Green vehicles consist of electric, hydrogen and hybrid. Where this green vehicle will help develop and advance smart cities. This research aims to Support the sustainability of Smart City Development and provide Innovation to research and develop green vehicles that are low emission and Dependent on renewable energy or renewable energy. This research was carried out by qualitative methods. By focusing on the sustainability of green vehicles to support smart cities.

Discovering smart cities' potential in Kazakhstan: A cluster analysis.

The potential for developing smart cities in Kazakhstan is evaluated using cluster analysis. Built on previous research focused on clustering the regions of Kazakhstan, this study applies the same method to the cities of the country. The analysis uses indicators related to human capital, infrastructure, education, information technology, production, and other factors to assess the potential of each city. The clustering is performed using Single Linkage, Complete Linkage, and Ward's methods. The results show that Almaty and Astana are the cities with the highest potential for becoming smart cities. Aktobe is identified as a city with distinctive features that may help or hinder its development as a smart city. The remaining cities are clustered into two groups, with one group having the potential to catch up and maintain the trend of developing smart cities, while the other group is less suitable for starting smart city projects and may require more investment per capita. The study highlights the deep regional inequality affecting the potential to successfully develop and manage smart cities in Kazakhstan. The analysis also reveals some limitations and challenges in the data and variables used, including the lack of data for some variables and the difficulties in "translating" some factors and indicators into quantitative variables for clustering. The study concludes that future research should address these challenges and consider clustering inside certain regions to focus on their unique features. The study recommends launching pilot projects in small cities, with the most successful practices then scaled and implemented in the core smart cities and possibly Aktobe, if it manages to use its advantages to compensate for risks. Overall, this study provides insights into the potential of smart city development in Kazakhstan and can inform policymakers in their efforts to support smart city projects in the country.

Securing Microservices‐Based IoT Networks: Real‐Time Anomaly Detection Using Machine Learning

Increased attention is being given to Internet of things (IoT) network security due to attempts to exploit vulnerabilities. Security techniques protecting availability, confidentiality, and information integrity have intensified as IoT devices are viewed as gateways to larger networks by malicious actors. As an additional factor, the microservices‐based platforms have overtaken the deployment of applications that support smart cities; however, the distributed nature of these architectures heightens susceptibility to malicious network infrastructure use. These risks can result in disruptions to system functioning or data compromise. Proposed strategies to mitigate these risks include developing intrusion detection systems and utilizing machine learning to differentiate between normal and anomalous network traffic, indicating potential attacks. This article outlines the development and implementation of an intrusion detection system (IDS) using machine learning to detect online anomalies in network traffic. Comprising a traffic extractor and anomaly detector, the system employs supervised learning with various datasets to train models. The results demonstrate the effectiveness of the decision tree model in detecting traditional denial of service (DoS) attacks, achieving high scores across multiple metrics: an F1‐score of 98.08%, precision of 99.25%, recall of 96.96%, and accuracy of 99.62%. The random forest model excels in identifying slow‐rate DoS attacks, attaining an F1‐score of 99.85%, precision of 99.91%, recall of 99.80%, and accuracy of 99.88%.

Фінансові чинники ефективної імплементації концепції смарт-економіки на різних рівнях

The article studies the influence of financial factors on the effective implementation of the conception of smart economy at different levels, reveals the influence of factors on the development of smart economy at different levels, presents a hierarchy of levels of smart economy implementation. It is defined that the key levels of smart economy implementation are national, regional, local and business levels. Accordingly, at each of these levels, the features and key aspects of financing smart economy programs are studied. It is further defined that at the national level, the key sources and areas of funding are the development of innovations, the formation of technology parks and innovation clusters, funds for which can be attracted from national, international sources and individual companies that are interested in the implementation of projects at a high level. The regional level is interested in the implementation of regional programs, funding for which, according to research, is provided from regional development funds, regional budget, bonds, national and international grants, co-financing. The study confirms that the role of finance in the development of regions or localities is quite significant, and programs to support smart cities or localities are developing quite actively. The local level is implemented through projects with an emphasis on digitalization, accordingly, these are attracted investments, grants and subsidies, public-private partnerships, city bonds, grants, and crowdfunding. At the business level, the implementation of smart projects requires attracting finance primarily through corporate investments, especially within the framework of corporate social responsibility programs, green investment development, venture financing, green or social bonds, etc. All these sources of funding are often combined with international grants and loans from organizations. The key levels of financing of the smart economy and the forms of its implementation have been identified, taking into account the limitations and opportunities for the development of national economic systems in the globalized world. This became possible due to the analysis of key prerequisites and examples of practical implementation of the smart economy at different levels, the peculiarities of the possibility of attracting financial resources for development at the national, regional, local and business levels.

Comparative study of high-performance mesophilic and thermophilic anaerobic membrane bioreactors in the co-digestion of sewage sludge and food waste: Methanogenic performance and energy recovery potential

To support smart cities in terms of waste management and bioenergy recovery, the co-digestion of sewage sludge (SeS) and food waste (FW) was conducted by the anaerobic membrane bioreactor (AnMBR) under mesophilic and thermophilic conditions in this study. The biogas production rate of the thermophilic AnMBR (ThAnMBR) at the SeS to FW ratio of 0:100, 75:25, 50:50 and 100:0 was 2.84 ± 0.21, 2.51 ± 0.26, 1.54 ± 0.26 and 1.31 ± 0.08 L-biogas/L/d, inconspicuous compared with that of the mesophilic AnMBR (MeAnMBR) at 3.00 ± 0.25, 2.46 ± 0.30, 1.63 ± 0.23 and 1.30 ± 0.17 L-biogas/L/d, respectively. The higher hydrolysis ratio and the poorer rejection efficiencies of the membrane under thermophilic conditions, resulting that the permeate COD, carbohydrate and protein of the ThAnMBR was higher than that of the MeAnMBR. The lost COD that might be converted into biogas was discharged with the permeate in the ThAnMBR, which was partly responsible for the inconspicuous methanogenic performance. Furthermore, the results of energy recovery potential assessment showed that the energy return on investment (EROI) of the MeAnMBR was 4.54, 3.81, 2.69 and 2.22 at the four SeS ratios, which was higher than that of the ThAnMBR at 3.29, 2.97, 2.02 and 1.80, respectively, indicating the advantage of the MeAnMBR over the ThAnMBR in energy recovery potential. The outcomes of this study will help to choose a more favorable temperature to co-digest SeS and FW to support the construction of smart cities.

Instagram as a Publication and Archiving Media for the General Election Supervisory Agency

An organized documentation process with good archival management is very important for any institution, including the General Election Supervisory Body. In the current era of Industrial Revolution 4.0, archiving media is not only through physical filing but also through digital media, one of which is through the use of Instagram. This research aims to analyze the model for utilizing Instagram accounts as archiving media for the General Election Supervisory Agency using the analysis knife theory, namely politics and archiving. The method in this research is a descriptive method with a qualitative approach. Furthermore, the data that has been collected through the literature study is then interpreted so that a deeper and broader meaning and meaning can be obtained regarding the results of the research carried out. Based on the research results, it is known that the model for utilizing Instagram accounts as archiving media for the General Election Supervisory Agency is implemented based on a good governance perspective with its relevance in the development of the Industrial Revolution 4.0 towards achieving a Smart City. This utilization is carried out with government innovation in archiving to support Smart City via social media Instagram in a tri-s synergistic manner, namely from government actors, non-government actors, and community actors.

Effectiveness of Go-MT (Gorontalo Integrated Community) Digitalization Services in Supporting Smart City Policy in Dungingi District Gorontalo City

Effectiveness of Go-MT (Gorontalo Integrated Community) Digitalization Services in Supporting Smart City Policy in Dungingi District Gorontalo City

Spatiotemporal flow force model of source/sink human mobilities within city

Human mobility is of importance in supporting smart cities, urban planning and constructions of resilient environments. Previous studies on dominant mobility models (i.e., gravity and radiation models) rarely describe the refined spatiotemporal process of human mobility flow forces especially within city. To address this gap, this paper proposes a spatiotemporal flow force model (FFM) of sink/source human mobilities within city, which is derived from Navier-Stokes equation in the field of fluid mechanics. The FFM model outperforms the gravity and radiation models in modeling the refined spatiotemporal flow force process of source/sink human mobilities, in the aspect of intensity and direction of mobility flow force. Comparison results show that the gravity and radiation models in the source mobility scenario can give a rough force estimation about the total outflow from source mobility areas while without the capability of explaining the specific directions of mobility flow from source mobility areas. Pearson correlation coefficient between the intensity results of the two models and those of FFM range from 0.65 to 0.90 and direction differences between the results of the two models and FFM respectively show no clear regularity. In the sink mobility scenario, the direction of mobility flows can be estimated well by the gravity and radiation models while the intensity of mobility flow between small-scale areas within cities is susceptible to inaccuracies. Pearson correlation coefficient ranges from 0.13 to 0.59 and direction differences follow a stepped distribution from high to low within the range of 0° to 180°. In addition, the potential field of human mobility flow force provides a powerful tool for visually analyzing mobility flows within cities. This proposed model enriches human mobility models and is generalizable in supporting smart cities, urban planning, and constructions of resilient environments in terms of the refined spatiotemporal process of mobility flow force.

M-Tech Profit Program Supports in the Smart City of Madiun

In the digital revolution era, affordable and accessible internet services are crucial for all segments of society, especially with the rise of industrial revolution 4.0. However, limited internet access primarily affects the upper middle class. To bridge this gap, the Madiun City Government initiated the Profit M-Tech program, introducing the Free Wi-Fi Program for Madiun Hand-held Technology. This study aims to (1) clarify the program’s goals, (2) analyze its benefits in education, economy, and socio-culture, and (3) assess its impact on supporting smart city policies. Findings show that the program has significantly increased internet accessibility for all classes, aided sectors like education and economy during the pandemic, and effectively supported smart city initiatives.

Leveraging a novel NFT-enabled blockchain architecture for the authentication of IoT assets in smart cities

The concept of smart city architecture requires a comprehensive solution that can combine real-time response applications for cyber-physical systems. However, the architecture faces challenges that can obstruct the operations in terms of systems, processes, and data flow as far as the breach risk is concerned. Though the field has been researched with the existence of centralized and distributed architectures to support smart cities. Research gaps regarding security concerns, platform assistance, and resource management continue to persist. This research article presents a novel blockchain-based architecture that proposes expansion in the non-fungible tokens (NFTs) to cater to the expansion of IoT-enabled smart assets. It enables NFTs to employ fog computing for all users and smart devices connected to a fog node in a cyber-physical system. The proposed expansion suggested in Non-Fungible Tokens (NFTs) for IoT assets representation in a cyber-physical system, provides devices and user identification and authentication functionality. The proposed NFT architecture has been designed to provide a smart city solution for cyber-physical systems that ensures robust security features (such as CIA) by introducing new attributes and functions for Owner, User, Fog, and IoT device/s authentication. The validation and rigor of the security services, efficiency, and latency have been achieved by deployments on private and public ledgers. The efficiency, and cost-effectiveness of the suggested functions and components have been evaluated in terms of evaluation cost and time complexity which resulted in promising results, obtained and validated on a testnet. The evaluation cost for the devised mint component was approximately 81%, and devised approve() was approximately 23% more efficient than other solutions.

Implementing Digital Literacy Policies and the Challenges of Towards Smart City in Palembang City

This research examines digital literacy's role in supporting smart city development in Palembang City by focusing on four key aspects, including digital skills, digital safety, digital ethics, and digital culture. This study uses a qualitative descriptive approach to use primary and secondary data. The analysis tool used is Nvivo 12 Plus. These findings successfully analyze the challenges faced in integrating digital literacy in smart city development, including digital literacy gaps, privacy concerns, lack of awareness of benefits, technical challenges, and cultural changes. In addition, the role of government and regulation and cross-sector collaboration are also explained as important factors in creating an environment that supports holistic digital literacy. The results of this study provide a comprehensive view of how digital literacy can play a key role in facing challenges and optimizing the benefits of smart technology in the development of inclusive and sustainable smart cities. This research contributes to stakeholders involved in planning and implementing smart cities, as well as providing directions for effective digital literacy efforts in the future.