Challenges Of Smart Cities Research Articles

Deep learning solutions for smart city challenges in urban development

In the realm of urban planning, the integration of deep learning technologies has emerged as a transformative force, promising to revolutionize the way cities are designed, managed, and optimized. This research embarks on a multifaceted exploration that combines the power of deep learning with Bayesian regularization techniques to enhance the performance and reliability of neural networks tailored for urban planning applications. Deep learning, characterized by its ability to extract complex patterns from vast urban datasets, has the potential to offer unprecedented insights into urban dynamics, transportation networks, and environmental sustainability. However, the complexity of these models often leads to challenges such as overfitting and limited interpretability. To address these issues, Bayesian regularization methods are employed to imbue neural networks with a principled framework that enhances generalization while quantifying predictive uncertainty. This research unfolds with the practical implementation of Bayesian regularization within neural networks, focusing on applications ranging from traffic prediction, urban infrastructure, data privacy, safety and security. By integrating Bayesian regularization, the aim is to, not only improve model performance in terms of accuracy and reliability but also to provide planners and decision-makers with probabilistic insights into the outcomes of various urban interventions. In tandem with quantitative assessments, graphical analysis is wielded as a crucial tool to visualize the inner workings of deep learning models in the context of urban planning. Through graphical representations, network visualizations, and decision boundary analysis, we uncover how Bayesian regularization influences neural network architecture and enhances interpretability.

CYBERSECURITY CHALLENGES IN SMART CITIES: A CASE REVIEW OF AFRICAN METROPOLISES

The rapid urbanization and digital transformation of cities across Africa have given rise to the concept of Smart Cities, where advanced technologies are integrated to enhance efficiency, sustainability, and the overall quality of urban life. However, this paradigm shift towards interconnected and technology-driven urban environments brings forth a host of cybersecurity challenges that demand careful consideration. This paper explores the cybersecurity challenges in Smart Cities, focusing on a case review of African metropolises. African cities, emblematic of the global urbanization trend, are embracing Smart City initiatives to address urban challenges and foster economic development. While these initiatives promise improved services and enhanced connectivity, they concurrently expose cities to a myriad of cybersecurity threats. The interconnectedness of devices and systems in Smart Cities creates a vast attack surface, making them susceptible to cyber-attacks ranging from data breaches to infrastructure disruptions. This case review delves into specific instances of cybersecurity challenges faced by African metropolises in their quest for technological advancement. It analyzes the vulnerabilities in critical infrastructure, such as energy grids, transportation systems, and healthcare networks, highlighting the potential risks associated with inadequate cybersecurity measures. Moreover, the paper sheds light on the socio-economic implications of cyber threats in Smart Cities, emphasizing the importance of resilient cybersecurity frameworks in safeguarding citizen data and urban functionality. In conclusion, the paper underscores the urgent need for comprehensive cybersecurity strategies tailored to the unique challenges faced by Smart Cities in Africa. The findings aim to contribute to a better understanding of the intricate relationship between urbanization, technology, and cybersecurity, offering insights that can inform policy decisions, technological implementations, and collaborative efforts to build secure and resilient Smart Cities in the African context.
 Keywords: Cybersecurity, Smart Cities, Africa, Metropolis, Review.

Towards an IoT based secured framework for smart cities

<p>Cities are evolving into smart urban environments, where various devices, technologies, services, connections, blocks, and storage systems are transforming to embrace smart solutions, departing from traditional counterparts. This intricate network of interconnected devices collectively constitutes the Internet of Things (IoT), promising users a life of enhanced convenience. However, this transformation also introduces challenges, particularly in managing loosely linked devices and transmitting information across networks. This study conducts a comprehensive review of the various components contributing to the formation of a smart city, scrutinizing the challenges and factors that influence them. The overarching objective is to identify specific areas within smart cities grappling with cybersecurity challenges and ascertain the relative significance of each area. Data for this research is gathered through questionnaires, expert opinions, and paired comparisons drawn from previous studies, and employs the Fuzzy Analytic Hierarchy Process approach to determine the weight of each factor and sub-factor, subsequently ranking them. Among the nine identified factors, the "Smart Security" factor is the most critical, with a weight of 0.198, signifying its paramount importance. To overcome the security challenges in smart cities, we introduce an advanced secure framework (ARPL) for detecting security threats, using the Routing Protocol for Low Power and Lossy Networks (RPL) as its foundation. The advanced framework is adept at identifying a variety of attacks. Performance assessments of the proposed framework encompass several key parameters, such as ADA, TPR, FPR, and end-to-end delay. The positive outcomes observed strongly endorse the effectiveness of the proposed framework, positioning it as an optimal solution for RPL-based smart environments.</p>

A Review on Key Innovation Challenges for Smart City Initiatives

Smart city initiatives are being promoted across the world to address major urban challenges, and they all share a common belief in the transformative power of digital technologies. However, the pace of innovation in smart cities seems to be much slower than the rapid and profoundly disruptive transformations brought about by digital innovation in many other domains. To develop new insights about the main causes behind this relatively modest success, this study provides a Systematic Literature Review (SLR) on the connection between major smart city challenges and the essential properties of digital innovation. The review involved the qualitative analysis of 44 research papers reporting on smart city innovation practices and outcomes. The results characterize five major challenge categories for smart city innovation: Strategic vision; Organizational Capabilities and Agility; Technology Domestication; Ecosystem Development; and Transboundary Innovation. This study also explores the connections between these challenges and concrete digital innovation practices in smart city initiatives. The main conclusion is that current innovation practices in smart cities are not properly aligned with what the research literature commonly describes as core properties of digital innovation and that this might be a major cause behind the limited progress in smart city initiatives.

Gaia-X & Fiware: Implementation of a Federated Data Platform in Smart Cities

Using and connecting different technologies to improve the quality of urban life is a significant challenge for smart cities. The interconnection of transport, energy, water, public lighting, and other urban infrastructure systems is critical to providing quality services to citizens and reducing environmental impact. However, data interoperability from these systems is a significant challenge, as data is mainly stored in different formats and locations from various sources. This paper examines the challenges of integrating existing datasets in intelligent cities and proposes solutions to create secure and interoperable data-sharing environments. To this end, an approach called data federation is discussed by implementing a federated platform for integrating such data. However, it is essential to note that there may be challenges in terms of cybersecurity and interoperability. This is where context brokers play a crucial role, regulating access to data by enforcing rules and providing security standards. In this way, these challenges can be managed appropriately, ensuring data protection and the system’s proper functioning. Finally, it is essential to mention that this work is linked to a smart cities project, which aims to promote innovation in smart cities by implementing several innovative solutions. The study presented in this research contributes to understanding the challenges in smart cities. It proposes solutions for creating secure and interoperable data-sharing environments, which are essential both for the project’s success and for the development of smart cities worldwide.

The 5G revolution: Tackling challenges in smart cities and intelligent transportation systems

<div><p>The use of cutting-edge technology and data systems to increase the effectiveness, safety, and environmental responsibility of transport networks is known as intelligent transportation systems (ITS). In order to improve many elements of transportation, ITS incorporates a wide range of technologies, including sensors, communication networks, data analytics, and robots. By addressing the shortcomings of the current 4G network, the next mobile technology, 5G, challenges the electronic communication environment as it stands. By allowing a large number of concurrent connections and networks ubiquitous, even in high mobility scenarios or densely inhabited places, such Smart trains and smart cities (SC) are made possible by cutting-edge technology a new approach of becoming fully integrated. According to this strategy; 5G will enable the true Internet of Things (IoT) and its related automobiles on the World Wide Web (WWW). This conversation attempts to thoroughly explain how 5G wireless networks will impact urban smart transport networks, including semi-autonomous or self-driving cars, and automotive communication over the coming years, as well as any technical, economical, and regulatory issues.</p></div>

Unleashing the IoT Revolution in India: Trends, Advantages, Applications, and Strategic Importance

The Internet of Things (IoT) represents a revolutionary paradigm where everyday objects are interconnected, enabling them to collect, exchange, and act upon data. This interconnectedness extends beyond traditional computing devices, incorporating a diverse range of physical objects embedded with sensors and actuators. The applications of IoT are vast and impactful, permeating various sectors globally. From smart homes and cities to industrial automation, healthcare, and agriculture, the IoT is driving unprecedented efficiency, convenience, and innovation. Worldwide, the growth of IoT is staggering, with billions of devices already connected and projections indicating exponential expansion. According to recent statistics, the global IoT market reached $201 billion in 2022, showcasing a 21.5% increase, and it is anticipated to surge further, underlining the pervasive integration of IoT into the daily lives of individuals and industrial activities. In the Indian context, the strategic importance of the IoT is paramount. With a rapidly expanding economy and a burgeoning population, India stands to gain significantly from IoT applications. The technology's potential to address challenges in agriculture, healthcare, smart cities, and industrial processes aligns with national development goals. The implementation of IoT in India fosters efficiency, sustainability, and economic growth. As the IoT continues to evolve globally, its transformative impact on India's socio-economic landscape solidifies its role as a catalyst for innovation and progress, promising a future where connectivity and intelligence converge for the betterment of individuals and the nation as a whole. With a focus on trends, contributions, advancements, and applications, this article seeks to broaden the knowledge around IoT in India and functions as a kind of reference for scholars interested in the subject.

Challenges of Smart Cities: Methods of Prioritization

Smart city development has gotten considerable recognition in systematic literature and international policies throughout the world. The study aims to identify the key barriers to smart cities from the review of existing literature and the views of experts in this area. This work further made an attempt on the prioritization of barriers to recognize the most important barrier category and ranking of specific barriers within the categories to the development of smart cities in India. Through the existing literature, this work explored 31 barriers to smart cities development and divided them into six categories. This research work employed the fuzzy Analytic Hierarchy Process (AHP) technique to prioritize the selected barriers. Findings reveal that ‘Governance’ is documented as the most significant category of barriers to smart city development followed by ‘Economic; ‘Technology’; ‘Social’; ‘Environmental’ and ‘Legal and Ethical’. In this work, author also performed sensitivity analysis to show how robust is the findings of study. This research is useful to the government and policymakers for eradicating the potential interferences in smart city development initiatives in developing country like India.

Empowering smart city governance through decentralized blockchain solutions for security and privacy in IoT communications

This paper highlights the benefits and challenges of smart cities, which leverage technology to offer a wide range of services to citizens. While these services have the potential to greatly improve the quality of life in metropolitan areas, they also raise significant privacy and security concerns. The study emphasizes the need to employ "privacy by design" principles to ensure that personal data is protected throughout the entire lifecycle of data, and data owners have the self-control to manage their data according to their preferences. Smart contracts, built on blockchain technology, offer a secure and transparent way of conducting transactions, particularly in e-governance, and automating processes. By leveraging these technologies, smart cities can address the privacy and security challenges they face while continuing to offer cutting-edge services to their inhabitants. Ultimately, the study emphasizes the importance of a proactive approach to privacy and security in the development and implementation of smart cities.

An integrated framework for addressing urban challenges in smart cities: transitioning from the V-model to a knowledge-action approach

ABSTRACT Digital technologies and tools have been widely deployed in smart city initiatives to improve operations, resource allocation, and infrastructure management. Due to high complexity and diversity, however, numerous technologies have simultaneously created obstacles for practitioners when choosing appropriate tools for certain urban challenges. This study proposes a knowledge-action guiding framework (K-A framework), based on the classic V-model, useful for guiding practitioners to scan through appropriate digital technologies and tools for addressing urban challenges and societal issues. A toolbox was also developed to support the use of the framework. It outlines a comprehensive landscape of popular and emerging digital tools in digitalizing urban services. Essentially, the K-A framework provides a ‘how-to’ in terms of identifying potential tools, while the digital toolbox shows ‘what-are-the-options’ for the users of the framework. The case study underscores the usefulness of the framework and toolbox as effective practical guides for formulating action solutions. Highlights We propose a knowledge-action framework based on a classic systems engineering model This framework can guide practitioners to identify digital technologies and tools A comprehensive toolbox was provided to support the use of the framework A case study of urban safety issues was applied to validate the framework and toolbox Nonlinear thinking and professional competency are key for city planners and managers

6G Connected Vehicle Framework to Support Intelligent Road Maintenance Using Deep Learning Data Fusion

The growth of IoT, edge and mobile Artificial Intelligence (AI) is supporting urban authorities exploit the wealth of information collected by Connected and Autonomous Vehicles (CAV), to drive the development of transformative intelligent transport applications for addressing smart city challenges. A critical challenge is timely and efficient road infrastructure maintenance. This paper proposes an intelligent hierarchical framework for road infrastructure maintenance that exploits the latest developments in 6G communication technologies, deep learning techniques, and mobile edge AI training approaches. The proposed framework abides with the stringent requirements of training efficient machine learning applications for CAV, and is able to exploit the vast numbers of CAVs forecasted to be present on future road networks. At the core of our framework is a novel Convolution Neural Networks (CNN) model which fuses imagery and sensory data to perform pothole detection. Experiments show the proposed model can achieve state of the art performance in comparison to existing approaches while being simple, cost-effective and computationally efficient to deploy. The proposed system can form part of a federated learning framework for facilitating large scale real-time road surface condition monitoring and support adaptive resource allocation for road infrastructure maintenance.

Neutrosophic Framework for Assessment Challenges in Smart Sustainable Cities based on IoT to Better Manage Energy Resources and Decrease the Urban Environment's Ecological Impact

Sustainable smart cities based on the Internet of Things (IoT) technology provide promising prospects for improving quality of life. However, in order to facilitate the widespread implementation of IoT-based smart city solutions, there is a need to concern about data privacy and security, standardization, interoperability, scalability, and sustainability. Reducing the environmental effect of urban activities, optimizing the management of energy resources, and designing novel services and solutions for inhabitants are all examples of how the smart city concept is inextricably linked to sustainability. There is a need to assess challenges in smart sustainable cities based on IoT. This paper is intended to introduce a new neutrosophic framework for assessment challenges in smart, sustainable cities based on IoT for better-managing energy resources and decreasing the urban environment's ecological impact. The proposed framework used nine criteria and five alternatives. Also, the proposed framework applied the neutrosophic Weighted Product Method (WPM) to compute the weights of criteria and rank challenges. Moreover, the proposed framework integrated the single-valued neutrosophic set to deal with uncertain data. The results indicated that the proposed framework can handle uncertain data and give more effective results in assessing challenges in smart, sustainable cities based on IoT to better manage energy resources and decrease the urban environment's ecological impact.

Analyzing the Challenges for Future Smart and Sustainable Cities

The fast growth of the urban population increases the demand for energy, water, and transportation, amongst other needs. This study explores the current state and future scenarios of Smart Cities and the environmental, economic, and social challenges that must be overcome. We used the Rapid Review method to understand the challenges of implementing Smart Cities in different urban contexts and the potential impact of research on Smart City planning in future Smart Cities. The study offers insights into the potential for Smart City growth while identifying obstacles that must be addressed to ensure sustainability. Results serve as a foundation for planning and decision-making, highlighting aspects such as the adoption of alternative energies, reduction in car use, preservation of ecosystems, waste reduction, citizen participation, infrastructure, and citizen data privacy, among others. These aspects are essential to overcome obstacles and promoting Smart Cities’ development.

Big data analytics and smart cities: applications, challenges, and opportunities.

Urban environments continuously generate larger and larger volumes of data, whose analysis can provide descriptive and predictive models as valuable support to inspire and develop data-driven Smart City applications. To this aim, Big data analysis and machine learning algorithms can play a fundamental role to bring improvements in city policies and urban issues. This paper introduces how Big Data analysis can be exploited to design and develop data-driven smart city services, and provides an overview on the most important Smart City applications, grouped in several categories. Then, it presents three real-case studies showing how data analysis methodologies can provide innovative solutions to deal with smart city issues. The first one is an approach for spatio-temporal crime forecasting (tested on Chicago crime data), the second one is methodology to discover mobility hotsposts and trajectory patterns from GPS data (tested on Beijing taxi traces), the third one is an approach to discover predictive epidemic patterns from mobility and infection data (tested on real COVID-19 data). The presented real-world cases prove that data analytics models can effectively support city managers in tackling smart city challenges and improving urban applications.

A Review of the Theory and Practice of Smart City Construction in China

The construction of smart cities is an imperative trend for high-quality urban development and represents a crucial solution to various problems that afflict urbanization, such as population growth pressure, resource scarcity, environmental degradation, and economic frailty. To create a smart city, it is essential to gain a profound understanding of the evolution and experiences of urban development and have a clear grasp of the concept, emphasis, and developmental trajectory of smart cities. However, previous research and theoretical frameworks have mainly focused on the digital transformation of cities, the application of new generation information technologies, and the comprehensive intelligence of cities, neglecting the fundamental positioning and value of cities, which is the people’s central position and pursuit of happiness. This has led to many situations where intelligence is pursued for the sake of intelligence, resulting in inefficient use and allocation of resources. This paper puts forth a framework for the three generations of smart city construction and their meanings at the conceptual level, conducts an in-depth analysis of the development process and challenges of smart cities in China, and provides suggestions for improvement.

Smart City Transformation: An Analysis of Dhaka and Its Challenges and Opportunities

Cities worldwide are experiencing rapid urbanization and an increasing population, creating a pressing need for smart infrastructure to enhance citizen services. Dhaka, the capital of Bangladesh, faces similar technological and socio-economic challenges, making it crucial to transform it into a sustainable smart city. This research analyzes the opportunities and challenges of smart cities and Dhaka through SWOT and PESTEL analyses. The study employs a fuzzy rule-based inference system in a MATLAB simulation to calculate the smart city index based on parameters such as governance, transportation, waste management, utility management, healthcare, and industrial automation. The findings reveal that good governance has the highest impact on the smart city index, followed by transportation. The paper proposes a sustainable smart city transportation framework and management technique, outlining future research directions. The proposed framework is expected to impact socio-economic, technological, and environmental aspects positively.

IoT applications and challenges in smart cities and services

AbstractInternet of Things (IoT) is a revolutionary and novel platform where a smart network connects to the large number of electronic devices via internet through available communication systems for reliable and real time connectivity, sensing thus acquiring data from sensors, computing and actuating devices. A review of the current status of IoT features, architecture, communication infrastructure and applications is presented here. Number of IoT applications and challenges in the development of smart cities are covered about this innovative technological platform in this review along with communication protocols characteristics and applications. IoT aided smart city services, health applications, transport applications and smart grid improvements are also discussed. Many challenges and issues related to security, communication, applications and system architecture along with future directions of IoT technology are elaborated in detail.

Toward the Smart City Ecosystem Model

This study aims to present the processes and mechanisms of creating smart city ecosystems by examining the complex strategic choices and interactions among stakeholders operating at different levels of governance and engagement. Based on the literature review and in-depth analyses of a case study (Lublin, Eastern Poland), we demonstrate that the implementation of tailored strategic thinking using adaptation to global trends, exploitation of development potentials and niches, and stakeholders’ involvement allows for coordination and mobilization of development processes leading to the creation of effective smart city ecosystems. In line with the defined smart city challenges, with the application of a three-stage research program, we create an implementable Smart City Ecosystem Model (SCEM). The contributions of the study are as follows: (1) it provides new insights into smart governance, leadership in creating a sustainable and human smart city; (2) it analyzes strategic choices in the creation of a stakeholder ecosystem and competitive business ecosystems based on smart specializations, providing new opportunities for the design and implementation of smart city strategies. Therefore, this study provides a new multidimensional policy framework for smart cities at both strategic and operational levels that can improve the holistic management of smart and sustainable cities and communities.

Urban Computing for Sustainable Smart Cities: Recent Advances, Taxonomy, and Open Research Challenges

The recent proliferation of ubiquitous computing technologies has led to the emergence of urban computing that aims to provide intelligent services to inhabitants of smart cities. Urban computing deals with enormous amounts of data collected from sensors and other sources in a smart city. In this article, we investigated and highlighted the role of urban computing in sustainable smart cities. In addition, a taxonomy was conceived that categorized the existing studies based on urban data, approaches, applications, enabling technologies, and implications. In this context, recent developments were elucidated. To cope with the engendered challenges of smart cities, we outlined some crucial use cases of urban computing. Furthermore, prominent use cases of urban computing in sustainable smart cities (e.g., planning in smart cities, the environment in smart cities, energy consumption in smart cities, transportation in smart cities, government policy in smart cities, and business processes in smart cities) for smart urbanization were also elaborated. Finally, several research challenges (such as cognitive cybersecurity, air quality, the data sparsity problem, data movement, 5G technologies, scaling via the analysis and harvesting of energy, and knowledge versus privacy) and their possible solutions in a new perspective were discussed explicitly.

Enabling LPWANs for Coexistence and Diverse IoT Applications in Smart Cities Using Lightweight Heterogenous Multihomed Network Model

Smart cities have been envisioned to provide smartness in managing internet of things (IoT) application domains, such as transport and mobility, health care, natural resources, electricity and energy, homes and buildings, commerce and retail, society and workplace, industry, agriculture, and the environment. The growth trajectory in usage of these IoT domains has led to a heterogeneous dense network in a smart city environment. The heterogeneous dense network in smart cities has led to challenges, such as difficulties in the management of LPWAN coexistence, interference, spectrum insufficiency, QoS, and scalability issues. The existing LPWAN technologies cannot support the heterogeneous dense network challenges in smart cities. Further, it cannot support diverse IoT, including medium- to high-bandwidth applications, due to the power, complexity, and resource constraints of the LPWAN devices. Hence, this paper addresses high data rate IoT applications and heterogeneous dense networks. This paper proposes a lightweight heterogenous multihomed network (LHM-N) model for diverse smart city applications that will address dense heterogeneity network challenges in a smart city. The work aims to advocate and integrate a manageable license-free LPWAN that will coexist with 5G private and public cellular networks in the LHM-N model. This will help to provide a cost-effective solution model in a heterogeneous dense smart city environment. Further, a secured lightweight energy-efficient packet-size forwarding engine (PSFE) algorithm is presented using the discrete event simulation (DES) methodological approach in MATLAB for complexity evaluation. In addition, a 5G reduced capability (RedCap) IoT device is integrated into the (LHM-N) model to support smart city. Finally, the results show that the LHM-N model outperforms the conventional quadrature amplitude modulation (QAM) protocol scheme in terms of error rate, latency, and data throughput with reduced energy costs for medium- to high-bandwidth industrial IoT applications. This validates the suitability of the LHM-N model for high data rate IoT applications.