Smart City Paradigm Research Articles

Mobilizing alternative urbanisms in the semiperipheral smart city agenda

ABSTRACT Within critical urban studies, this inquiry examines how mobile policies arriving in a global semiperiphery contribute to developing socially just smart city paradigms. By provincializing smart city research and expanding the North–South dichotomy by analyzing a “South of the West,” the inquiry focuses on Lisbon as a semiperipheral city. It adopts a policy mobility approach and an analytical framework of smart city paradigms, combining thematic document analysis and in-depth interviews to examine the case study. The inquiry engages with local historical transformations and temporally analyzes Lisbon’s smart city agenda representing its development phases and exploring the mobility of ideas and paradigm shifts. Due to historical challenges reflected by the peripheralization of Southern Europe, local arrangements have led to political-economic and social transformations that, as the study argues, are potentialized by policy mobilities and entail smart city paradigm shifts towards social justice. Therefore, hybridizing new and old, emerging and established urban agendas provides alternatives to replicating neoliberal policies.

Smart City Planning To Create Good And Clean Government In Ternate City

Abstract: In the journey towards a Smart City, efforts to make it a bridge that connects people's expectations of appropriate, effective, and efficient government services by utilizing Information and Communication Technology (ICT) is of the essence. The Smart Governance concept is the main key, where the Ternate City Government as executor of government duties is expected to be able to provide quality services following Standard Operating Procedures (SOP) and the principles of law, humanity, justice, democracy, participation, transparency, accountability, and commitment to the welfare of its citizens. To realize the Smart City vision in Ternate, there needs to be a mutual understanding regarding the true Smart City paradigm. "In addition to supporting regulations, good cooperation between various parties who are committed to implementing Smart City as a form of public service to the community is very important.Keywords: Smart City, Planning, Government

A MODEL OF REGIONAL ENERGY SUPPLY SYSTEMS BASED ON SPECIALIZED QUEUEING SYSTEMS

This paper reviews the works of foreign scholars on the topic of regional power supply, based on data from the VINITI abstract journal for the years [2022] - [2024]. The review concludes that management systems for regional power supply are insufficiently explored, and within the context of the smart city paradigm, such studies have not been conducted. This highlights both the relevance and the scientific and practical novelty of the research. A power supply management system based on advanced queueing systems is proposed, which corresponds to the architecture of the modeled object (the power supply system of the city of Petropavlovsk).

An efficient security and privacy approach for internet of vehicles in vehicular networks for smart cities

AbstractIntelligent sensing plays a crucial role in making vehicles safe and trouble‐free. The purpose of this paper is to introduce Vehicular Sensor Networks (VSNs) in a vehicular IoT‐based smart city paradigm, focusing on security. Furthermore, we discuss the robustness and reliability of VSN. In this design, Ad hoc On‐Demand Distance Vector (AODV) routing‐based Internet of Vehicles is integrated with a privacy‐aware secure ant colony optimization for smart cities in which suspicious vehicles are prevented from disseminating messages. IoV real‐time communication emphasizes data security. A comparison of experimental results shows that the proposed approach outperforms existing approaches. Smart city communication networks can be optimized using the proposed model.

Integration of Building Information Modeling (BIM) and Geographic Information System (GIS): a new approach for IFC to CityJSON conversion

Within the contemporary urban development discourse, the paradigm of smart cities has gained prominence over the past two decades. Ensuring sustainability in smart cities requires coherent orchestration of processes that span design, construction, operations, and management. Central to this orchestration are technologies such as Building Information Modeling (BIM), which provides detailed architectural data, and Geographic Information Systems (GIS), which provide comprehensive geographic intelligence. However, a significant challenge remains: data degradation during BIM-GIS integration. This data inconsistency, exacerbated by the different data structures of BIM and GIS, is a barrier to true interoperability. One promising solution to this conundrum is the use of Semantic Web technologies. In this study, we leverage Semantic Linked Data and geometric conversion tools to develop an algorithm that mitigates the loss of semantic information during the BIM-to-GIS conversion process. The effectiveness of this approach is underscored by a 95% accuracy rate of the converted semantic information.

Actual practices of citizen participation in smart cities

This article attempts to explore the actual citizen participation practices. Scholarly articles on smart cities have investigated different aspects of the smart city paradigm. Despite increased scholarships on smart cities examining the citizen-centric claim, the praxis of citizen participation has not received much attention. Therefore, the aim of this article is to explore and understand the ‘actual practices’ of citizen participation in smart cities and how can an inclusive and equitable citizen participation can be ensured. Based on an in-depth review and analysis of secondary data, this article argues that enabling “active” involvement of citizenry through a rights-based approach can make citizen participation a worthwhile endeavor in the development process, which is equitable, inclusive and sustainable.

Unleashing The Power of Big Data: The Phenomenon Behind Indonesia's Smart City Policy Implementation

The concept of smart cities has emerged as a promising prospect for several major urban centers in Indonesia. Putting smart city projects together requires thinking about many things. Big data has become one of the most important parts for making sure that these projects will last. Employing big data technology makes it easier to improve the ways that data is stored and processed. This makes it possible to gather useful data that could greatly improve a wide range of smart city services. This study uses a library-based qualitative research approach to analyze scholarly journals and relevant literature. The method involves meticulous collection of data from carefully chosen libraries, aiming to provide comprehensive insights into the phenomenon of big data in smart cities implementation within government administration. This study aims to contribute to the identification and analysis of challenges encountered in emergency situations, with the ultimate goal of providing assistance in effectively mapping the problem at hand. The present discourse underscores the indispensability of Indonesia's contemporary human mindset in bolstering the viability of the smart city paradigm.

Community Engagement in Smart Cities: A Social Network Analysis and Community Engagement Test

This study, carried out in the ever-changing context of Smart Cities, reveals the complex interactions of digital social networks, digital community involvement, and the Community involvement Test (CET) framework. The examination of data obtained from certain Smart Cities indicates a thriving milieu of community engagement, characterized by a markedly elevated rate of active participation. The identification of urgent issues, particularly those related to environmental sustainability, safety, traffic management, and educational quality, is consistent with the larger urban difficulties that these creative urban centers are facing. Additionally, the CET framework's integration of SNA data and survey results produces very high ratings, indicating the engagement programs' outstanding performance in promoting resident satisfaction and active involvement. These results highlight how digital technologies can help Smart Cities foster vibrant, engaged communities. They also highlight the continued need for smart urban policies to address urgent issues and maintain residents' quality of life while adhering to the Smart City paradigm.

Enhancing Sustainability in Smart Cities: IoT-Enabled with Fog and Haze Mitigation Using EDN-GTM Technology

the growing reliance on Information and Communication Technologies (ICT) has prompted a shift towards smart city concepts, especially as over 70 per cent of the global population is expected to reside in urban areas by 2050. The smart city paradigm addresses the challenges of managing critical infrastructure by integrating intelligent ICT solutions across various sectors such as the economy, mobility, environment, people, living spaces, and governance. Central to this vision is the Internet of Things (IoT) role, acting as a pivotal network connecting devices and enabling seamless interactions in urban settings. Efficient energy usage is a key aspect of IoT-enabled smart cities, given the increasing demand for power with population growth. Lighting, a fundamental need, consumes a significant portion of energy, and an SLS becomes crucial for effective energy management in a smart city leveraging IoT technologies. The proposed system aims to enhance image quality and address fog-related challenges in Smart City applications by integrating IoT-based technology. In urban environments, foggy conditions can significantly impact visibility, affecting surveillance and monitoring systems. The system employs a comprehensive approach, utilising sensor data, image processing techniques, and deep learning models for efficient fog detection and removal. Key objectives include fog removal and image quality enhancement, focusing on adaptability to varying environmental conditions. The system dynamically adjusts fog removal processes based on real-time fog density information collected from cloud-based sensors. The dataset for training and evaluation is obtained from Kaggle, comprising fully foggy images. Pre-processing involves grey conversion and wavelet transform filters, simplifying image representation and extracting relevant features for subsequent stages. Segmentation with a region of interest (ROI) approach optimises processing efficiency by focusing on information-rich areas. Enhanced Dehazing Network (EDN) and Guided Transmission Map (GTM) models are separately implemented for haze removal and transmission map refinement. A hybrid approach combines the strengths of both models, aiming for superior fog removal and image quality improvement. Performance is assessed using metrics like PSNR, SSIM, TMQI, and FSIMc, providing a comprehensive evaluation. The proposed system, leveraging deep learning, adaptive processing, and IoT integration, offers an effective solution for mitigating the impact of foggy conditions in Smart City scenarios.

Investigating the Key Aspects of a Smart City through Topic Modeling and Thematic Analysis

In recent years, the emergence of the smart city concept has garnered attention as a promising innovation aimed at addressing the multifactorial challenges arising from the concurrent trends of urban population growth and the climate crisis. In this study, we delve into the multifaceted dimensions of the smart city paradigm to unveil its underlying structure, employing a combination of quantitative and qualitative techniques. To achieve this, we collected textual data from three sources: scientific publication abstracts, news blog posts, and social media entries. For the analysis of this textual data, we introduce an innovative semi-automated methodology that integrates topic modeling and thematic analysis. Our findings highlight the intricate nature of the smart city domain, which necessitates examination from three perspectives: applications, technology, and socio-economic perspective. Through our analysis, we identified ten distinct aspects of the smart city paradigm, encompassing mobility, energy, infrastructure, environment, IoT, data, business, planning and administration, security, and people. When comparing the outcomes across the three diverse datasets, we noted a relative lack of attention within the scientific community towards certain aspects, notably in the realm of business, as well as themes relevant to citizens’ everyday lives, such as food, shopping, and green spaces. This work reveals the underlying thematic structure of the smart city concept to help researchers, practitioners, and public administrators participate effectively in smart city transformation initiatives. Furthermore, it introduces a novel data-driven method for conducting thematic analysis on large text datasets.

Road safety control based on a mobile application

Introduction: The smart city paradigm is made up of a set of actors who must operate jointly to guarantee road flow. However, sometimes there are accidents, and they affect productive apparatus, cause minor or temporary injuries and sometimes death of the individuals involved. Problem: Events occur for multiple reasons and the authorities have difficulties in implementing controls that minimize their occurrence since they do not have the necessary tools to capture and analyze timely information on the claims that have been presented. Objective: The objective is to increase road safety control and safeguard mobility in Bucaramanga. For this, a mobile application is designed to capture accident data by implementing the Flutter framework and the Model- View design pattern methodology. Controller (MVC). Methodology: The development of software to analyze the large amount of information on road events. A da- tabase is developed where said information is stored and processed using programming languages, coding and data hosting. Design and process factors are also considered according to the user’s needs, which will determine the interface and expected performance. Results: A structured system for data capture with the ability to integrate the general community, streamline the availability of information and facilitate decision making that deals with the problem in real time. Conclusion: It is concluded that its implementation in the city fosters self-care for pedestrians and drivers, facilitating the design of effective control measures by territorial entities, bringing the city of Bucaramanga closer to sustainability. Originality: This methodology for integrating events is unique in the country and is developed based on the city’s own characteristics. Limitations: The lack of information provided by the government actors.

Integrating Sustainability: Unveiling the Quadruple Helix - A Study on Pre-development of Smart City Strategy

Urban centers, irrespective of their size, grapple with critical issues concerning urban transport, parking, and environmental preservation. Finding solutions to these challenges requires proactive measures, such as research initiatives yielding practical applications. Sustainable innovation flourishes through collaborative efforts across diverse sectors, encouraging mutual learning and optimal solution generation. Embracing the principles of sustainability, one promising approach lies in the Smart City concept adoption. This study delves into the significance of the Smart City paradigm, emphasizing the integration of the Quadruple Helix model, with a specific focus on the involvement of the fourth helix – society. The paper explores societal engagement in shaping Smart City strategies, as highlighted in a pre-development phase questionnaire survey, emphasizing the pivotal role of societal involvement in formulating sustainable urban strategies.

DECENT: Decentralized and Efficient Key Management to Secure Communication in Dense and Dynamic Environments

Intelligent Transportation Systems (ITS), one aspect of the Smart City paradigm, aim to improve the efficiency, convenience, and safety of travelers. The integration of (vehicular) communication technologies allows communication between the on-board communication units (OBUs) of vehicles, roadside units (RSUs), and vulnerable road users (VRUs), and contribute to the efficacy of ITS applications. However, these additional sources of information must be reliable and accurate. Security primitives such as confidentiality, integrity, and authenticity are required, but only achievable when supported with a suitable cryptographic key management scheme. This paper presents the design of a decentralized and efficient key management scheme, abbreviated as the DECENT scheme. This scheme provides secure multi-hop communication in dense and dynamic network environments while functioning in a self-organized manner. Through threshold secret sharing techniques, network nodes act as a distributed trusted third party (TTP) such that a threshold number of nodes can collaborate to execute key management functions. These functions include decentralized node admission and key updating. Novelties include (i) the unique self-healing characteristic, meaning that DECENT is capable of independently recovering from network compromise, and (ii) guidelines for choosing an appropriate security threshold in any deployment scenario which maximizes the level of security while simultaneously guaranteeing that decentralized key management services can be provided.

GEOSPATIAL BIG DATA ANALYTICS FOR SUSTAINABLE SMART CITIES

Abstract. Growing urbanization cause environmental problems such as vast amount of carbon emissions and pollution all over the world.Smart Infrastructure and Smart Environment are two significant components of the smart city paradigm that can create opportunities for ensuring energy conservation, preventing ecological degradation, and using renewable energy sources. Since a great portion of the data contains location information, geospatial intelligence is a key technology for sustainable smart cities. We need a holistic framework for the smart governance of cities by utilizing key technological drivers such as big data, Geographic Information Systems (GIS), cloud computing, Internet of Things (IoT). Geospatial Big Data applications offer predictive data science tools such as grid computing and parallel computing for efficient and fast processing to build a sustainable smart city ecosystem. Effective management of big data in storage, visualization, analytics, and analysis stages can foster green building, green energy, and net zero targets of countries. Parallel computing systems have the ability to scale up analysis on geospatial big data platforms which is key for ocean, atmosphere, land, and climate applications. In this study, it is aimed to create the necessary technical infrastructure for smart city applications with a holistic big data management approach. Thus, a smart city model framework is developed for Smart Environment and Smart Governance components and performance comparison of Dask-GeoPandas and Apache Sedona parallel processing systems are carried out. Apache Sedona performed better on the performance test during read, write, join and clustering operations.

Shared mobility companies: A multi-case study comparing different business models and their performances

Shared mobility is one of the smart mobility services that has emerged in the smart city paradigm. It is being adopted by several companies and startups, using distinct business models with different results. So, an important question is: how do mobility companies adopt sharing business models for enhanced performance in this context? This paper aims to propose an empirical model to analyze which components from smart mobility, collaborative consumption, and multisided platforms have been incorporated into companies' business models and their relationship with companies´ results. It was applied to 14 case studies of Brazilian shared mobility companies to investigate the relationship between these components and the business goals proposed by the authors (active company, survival, and mobile application ratings). This study offers a theoretical contribution to deepening the knowledge in this area, considering that the authors found no similar studies. Canvas business model framework, qualitative comparative analysis (QCA), content analysis, and cross-case analysis were applied to analyze these case studies. The results pointed to the necessary components for achieving the business goals and the sufficient conditions for the company's failure. Hence, this research can help entrepreneurs who wish to launch new platforms for shared mobility services – safeguarding the specific characteristics of the cases analyzed. It also allows managers to understand these business models and design operational structures that could benefit from the conclusions that emerged from this study.

Extending the IoT-Stream Model with a Taxonomy for Sensors in Sustainable Smart Cities

Sustainable cities aim to have a lower environmental impact by reducing their carbon footprints as much as possible. The smart city paradigm based on the Internet of Things (IoT) is the natural approach to achieving this goal. Nevertheless, the proliferation of sensors and IoT technologies, along with the need for annotating real-time data, has promoted the need for light weight ontology-based models for IoT environments, such as IoT-Stream. The IoT-Stream model takes advantage of common knowledge sharing of the semantics while keeping queries and inferences simple. However, sensors in the IoT-Stream model are conceptualized as single entities, exluding further analysis concerning their features (energy consumption, cost, etc.) or application areas. In this article, we present a taxonomy of sensors that expands the original IoT-Stream model by facilitating the mapping of sensors/actuators and services in the context of smart cities in such a way that different applications can share information in a transparent way, avoiding unnecessary duplication of sensors and network infrastructure.

Innovative Business Models for the Future Smart City

This paper examines how to outline and adopt innovative business models for the Smart Cities of the future. Smart Cities are intelligent and efficient communities and ecosystems employing digital technologies to respond a growing waste of resources, unsustainable environmental impact, and inefficiency in traditional processes. Considering the greatest benefits of Smart Cities on economies, societies, and environment, many countries have now introduced national Smart City projects in order to transform life, improve business operations and market competitiveness. However, despite growing interests towards Smart Cities, it remains still difficult to adopt this paradigm due to digital transformation, interaction strategies, social and cultural problems. Therefore, this paper aims to break down the barriers to these problems and support the literature and management to understand how to implement profitable business models for Smart Cities of the future. Specifically, we identify four main areas characterizing Smart Cities (i.e., Smart Mobility, Smart Living, Smart Energy, and Smart Public Ecosystems) where digital technologies have shown greater progress with large savings. For each area, multiple case studies have been discussed and Business Model Canvases have been developed for generalizing effective methodological approaches toward efficient implementation of Smart City paradigm. Results are threefold. As for digital transformation problems, we show how digital technologies (e.g., Cloud, IoT, Big Data and AI) are applied profitably through innovative business models; as for interaction strategies problems we indicate how to organize innovative ecosystems involving public and private actors to promote Smart Cities; as for social and cultural problems we delineate change management and communication practices useful to instill in all stakeholders a culture towards the Smart City. With these findings the paper aims at enriching scientific knowledge about the Smart City Paradigm by means of a business model perspective and to offer public administrations insightful guidelines for the transition toward Smart Cities.

Smart ‘Tourist Cities’ Revisited: Culture-Led Urban Sustainability and the Global Real Estate Market

Smart tourism destinations have received increasing attention during the last few years. Digital technologies have reshaped the smart city paradigm in terms of both resilience and sustainability, capitalizing cities’ cultural and historical components while providing unique potential for growth in the real estate industry. Real estate, in particular, is considered a main asset to the tourist experience, whether it is in the form of hospitality accommodation facilities, urban landscapes, or cultural heritage hotspots. In addition, the effect of cultural sites and overall destination attractiveness on real estate dynamics (land/housing prices and building activity) is well established. Thus, uncovering how enhanced technological throughputs and synergies, culture-led urban sustainability initiatives and the real estate dimension are directly (or indirectly) associated could support cities to better delineate policies for their promotion as international, sustainable, and resilient tourist destinations. With this perspective, the present study focused on four particular cities’ successful smart initiatives, namely Amsterdam, Barcelona, Seoul, and Stockholm, in an attempt to identify how developers and local authorities will need to transform in order to offer better services to residents and visitors. This work reveals that smart projects alone cannot secure the transition of existing (European) cities into smart and sustainable tourism destinations. In addition, this study also contributes to public policy by demonstrating how challenging it is to be smart without the support and involvement of the local community, highlighting the significance of public awareness. The empirical findings suggest that local authorities are of critical importance when shaping a well-structured and practically effective strategy for the integration of sustainable and technologically advanced smart features. Results are promising, and final reflections provide insights for tourism destinations policymakers, city authorities, and real estate professionals.

A Social Internet of Things Smart City Solution for Traffic and Pollution Monitoring in Cagliari

In the last years, the smart city (SC) paradigm has been deeply studied to support sustainable mobility and to improve human living conditions. In this context, a new SC based on the Social Internet of Things paradigm is presented in this article. Starting from the tracking of all vehicles (that is, private and public) and pedestrians, integrated with air quality measurements (that is, in real time by mobile and fixed sensors), the system aims to improve the viability of the city, both for pedestrian and vehicular users. A monitoring network based on sensors and devices hosted on board in local public transport allows real-time monitoring of the most sensitive areas both from traffic congestion and from an environmental point of view. The proposed solution is equipped with an appropriate intelligence that takes into account instantaneous speed, type of traffic, and instantaneous pollution data, allowing to evaluate the congestion and pollution condition in a specific moment. Moreover, specific tools support the decisions of public administration facilitating the identification of the most appropriate actions for the implementation of effective policies relating to mobility. All collected data are elaborated in real time to improve traffic viability suggesting new directions and information to citizens to better organize how to live in the city.

Traffic congestion in Buenos Aires: diagnosis and public policy recommendations for a more sustainable city

In recent decades, traffic congestion has had a central place on the transportation agenda in the City of Buenos Aires. Despite imposing works that benefited -in the short term- the traffic flow, traffic jams are persistent, and the phenomenon has even spread beyond the city center, reaching different points of the suburbs. The mere fact of traveling with a telephone throughout a city generates endless data that can be collected and analyzed to make investment or public policy decisions. In this work, the cost represented by the existence of congestion in Buenos Aires will be estimated and studied through a characterization approach of the variables, thoroughly investigating its causes and its consequences using programming tools and emphasizing the importance of Big Data in building a more sustainable city. Tentative public policies will also be proposed to mitigate the effects of congestion in the city, based on the data observed in the first instance and considering the new paradigm of smart cities, ecological infrastructure, and empowerment of public transport.