Cyber Security within Smart Cities:A Comprehensive Study and a Novel Intrusion Detection-Based Approach

The expansion of smart cities,facilitated by digital communications,has resulted in an enhancement of the quality of life and satisfaction among residents.The Internet of Things(IoT)continually generates vast amounts of data,which is subsequently analyzed to offer services to residents.The growth and development of IoT have given rise to a new paradigm.A smart city possesses the ability to consistently monitor and utilize the physical environment,providing intelligent services such as energy,transportation,healthcare,and entertainment for both residents and visitors.Research on the security and privacy of smart cities is increasingly prevalent.These studies highlight the cybersecurity risks and the challenges faced by smart city infrastructure in handling and managing personal data.To effectively uphold individuals’security and privacy,developers of smart cities must earn the trust of the public.In this article,we delve into the realms of privacy and security within smart city applications.Our comprehensive study commences by introducing architecture and various applications tailored to smart cities.Then,concerns surrounding security and privacy within these applications are thoroughly explored subsequently.Following that,we delve into several research endeavors dedicated to addressing security and privacy issues within smart city applications.Finally,we emphasize our methodology and present a case study illustrating privacy and security in smart city contexts.Our proposal consists of defining an Artificial Intelligence(AI)based framework that allows:Thoroughly documenting penetration attempts and cyberattacks;promptly detecting any deviations from security standards;monitoring malicious behaviors and accurately tracing their sources;and establishing strong controls to effectively repel and prevent such threats.Experimental results using the Edge-IIoTset(Edge Industrial Internet of Things Security Evaluation Test)dataset demonstrated good accuracy.They were compared to related state-of-theart works,which highlight the relevance of our proposal.

An Enhanced Multiview Transformer for Population Density Estimation Using Cellular Mobility Data in Smart City

This paper addresses the problem of predicting population density leveraging cellular station data.As wireless communication devices are commonly used,cellular station data has become integral for estimating population figures and studying their movement,thereby implying significant contributions to urban planning.However,existing research grapples with issues pertinent to preprocessing base station data and the modeling of population prediction.To address this,we propose methodologies for preprocessing cellular station data to eliminate any irregular or redundant data.The preprocessing reveals a distinct cyclical characteristic and high-frequency variation in population shift.Further,we devise a multi-view enhancement model grounded on the Transformer(MVformer),targeting the improvement of the accuracy of extended time-series population predictions.Comparative experiments,conducted on the above-mentioned population dataset using four alternate Transformer-based models,indicate that our proposedMVformer model enhances prediction accuracy by approximately 30%for both univariate and multivariate time-series prediction assignments.The performance of this model in tasks pertaining to population prediction exhibits commendable results.

City Network Evolution Characteristics of Smart Industry: Evidence from Yangtze River Delta, China

The dual-path model of industrial evolution and spatial progression has been widely acknowledged and incorporated into the strategic planning to promote the development of urban industries and regional collaborations.However,current research on inter-enter-prise city networks mainly focuses on the single sector of flows on all enterprise branches,such as product value chains and production factors,but neglects that of particular industry department.Built upon the new economic geography and city networks theory,this paper develops a methodological framework that focuses on the analysis of city network evolution characteristics of smart industry.Particu-larly,a conceptual model of smart industry enterprise-industry-city is proposed and then applied to a case study of smart industry in the Yangtze River Delta Region,China.Using enterprise supplier-customer data,a city network of smart industry is constructed and sub-sequently analyzed with the proposed model.Findings indicate that the smart industry network in Yangtze River Delta Region exhibits a hierarchical structure and the expansion of the network presents a small-world network characteristic.The study not only makes a meth-odological contribution for revealing the industrial and spatial evolution path of the current smart industry,but also provides empirical support for the formulation of new economic development policies focused on smart industries,demonstrating the role of city clusters as carriers of regional synergistic development.

Do companies influenced by smart cities pay more attention to green governance?Mechanism and optimal spatial correlation

Smart cities are a way for China to construct an innovative and environmentally conscious nation.The paper examines the impact of smart cities on corporate green governance and provides a theoretical foundation for formulating and executing smart city policy in China.Based on panel data from Chinese A-share listed companies in Shanghai and Shenzhen from 2008 to 2020,this study constructs a multiperiod double-difference model to examine the influence of smart cities on corporate green governance.Additionally,it uses a spatial double-difference model to investigate the spatial spillover effect of smart cities on neighboring areas.The findings indicate that smart cities effectively enhance corporate green governance.Analyzing the influencing mechanisms reveals that resource allocation efficiency,technological innovation,management environmental awareness,and regional environmental enforcement efforts act as mediators.Furthermore,the study reveals that the impact of smart cities on promoting corporate green governance is more pronounced in regions with lower levels of marketization and resource-based cities.Moreover,the research explores the spatial spillover effects of smart cities,with an effective radius of approximately 350 km.The optimal spatial correlation zone for green governance of businesses in neighboring areas in relation to smart cities is within a range of 250-350 km.This is manifested by the significant promotion of green governance in neighboring area businesses facilitated by smart cities.

Ensemble Deep Learning Based Air Pollution Prediction for Sustainable Smart Cities

Big data and information and communication technologies can be important to the effectiveness of smart cities.Based on the maximal attention on smart city sustainability,developing data-driven smart cities is newly obtained attention as a vital technology for addressing sustainability problems.Real-time monitoring of pollution allows local authorities to analyze the present traffic condition of cities and make decisions.Relating to air pollution occurs a main environmental problem in smart city environments.The effect of the deep learning(DL)approach quickly increased and penetrated almost every domain,comprising air pollution forecast.Therefore,this article develops a new Coot Optimization Algorithm with an Ensemble Deep Learning based Air Pollution Prediction(COAEDL-APP)system for Sustainable Smart Cities.The projected COAEDL-APP algorithm accurately forecasts the presence of air quality in the sustainable smart city environment.To achieve this,the COAEDL-APP technique initially performs a linear scaling normalization(LSN)approach to pre-process the input data.For air quality prediction,an ensemble of three DL models has been involved,namely autoencoder(AE),long short-term memory(LSTM),and deep belief network(DBN).Furthermore,the COA-based hyperparameter tuning procedure can be designed to adjust the hyperparameter values of the DL models.The simulation outcome of the COAEDL-APP algorithm was tested on the air quality database,and the outcomes stated the improved performance of the COAEDL-APP algorithm over other existing systems with maximum accuracy of 98.34%.

Geospatial Technology Integration in Smart City Frameworks for Achieving Climate Neutrality by 2050: A Case Study of Limassol Municipality, Cyprus

This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.

The Contribution of AI-Powered Mobile Apps to Smart City Ecosystems

In the groundbreaking study “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems,” authored by Zaki Ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is meticulously examined. This comprehensive research delineates the multifaceted ways in which AI-powered mobile applications can significantly enhance the efficiency, sustainability, and livability of urban environments, marking a pivotal step towards the realization of smart cities globally. Bayashot meticulously outlines the critical areas where AI-powered apps offer unprecedented advantages, including urban mobility, public safety, energy management, and environmental monitoring. By leveraging AI’s capabilities, these applications not only streamline city operations but also foster a more sustainable interaction between city dwellers and their environment. The paper emphasizes the importance of data-driven decision-making in urban planning, showcasing how AI analytics can predict and mitigate traffic congestion, optimize energy consumption, and enhance emergency response strategies. The author also explores the social implications of AI in urban settings, highlighting the potential for these technologies to bridge the gap between government entities and citizens. Through engaging case studies, Bayashot demonstrates how participatory governance models, enabled by AI apps, can promote transparency, accountability, and citizen engagement in urban management. A significant contribution of this research is its focus on the challenges and opportunities presented by the integration of AI into smart city ecosystems. Bayashot discusses the technical, ethical, and privacy concerns associated with AI applications, advocating for a balanced approach that ensures technological advancements do not come at the expense of civil liberties. The study calls for robust regulatory frameworks to govern the use of AI in public spaces, emphasizing the need for ethical AI practices that respect privacy and promote inclusivity. Furthermore, Bayashot’s research underscores the necessity of cross-disciplinary collaboration in the development and implementation of AI technologies in urban contexts. By bringing together experts from information technology, urban planning, environmental science, and social sciences, the author argues for a holistic approach to smart city development. This interdisciplinary strategy ensures that AI applications are not only technologically sound but also socially and environmentally responsible. The paper concludes with a visionary outlook on the future of smart cities, posited on the seamless integration of AI technologies. Bayashot envisions a world where AI-powered mobile apps not only facilitate smoother urban operations but also empower citizens to actively participate in the shaping of their urban environments. This research serves as a critical call to action for policymakers, technologists, and urban planners to embrace AI as a tool for creating more sustainable, efficient, and inclusive cities. By presenting a detailed analysis of the current state of AI in urban development, coupled with practical insights and forward-looking recommendations, “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems” stands as a seminal work that is poised to inspire and guide the evolution of urban landscapes worldwide. Its comprehensive exploration of the subject matter, combined with its impactful conclusions, make it a must-read for anyone involved in the field of smart city development, AI technology, or urban policy-making.

Do smart city policies improve energy efficiency?Evidence from China

To address air pollution and offer a convenient and comfortable living environment,the Chinese government launched a smart city pilot(SCP)project in 2012,accompanied by a comprehensive set of environmental and energy-related laws and regulations.Although academic interest in smart cities has surged,there remains a notable gap in empirical research exploring the economic,environmental,and energy effects of such initiatives.Taking 232 prefecture-level cities from 2003 to 2017 as research subjects,this study measures energy effi‐ciency by using energy consumption per unit of GDP and adopts a difference-in-differences(DID)analysis to investigate the impact of SCPs on energy efficiency.The empirical results indicate that SCPs improved energy efficiency by promoting urban technological innovation capabilities and green total factor productivity,and this effect was more pronounced in cities that were more dependent on traditional fossil fuel energy sources and had more developed fiscal and financial levels.Studying the impact of smart city construction on energy utilization efficiency in developing countries,such as China,is not only significantly enlightening for China’s green and low-carbon transition but also provides reference opinions for constructing smart cities and the path to enhancing energy efficiency in other developing countries.The findings provide valuable insights into the global development of smart cities,urban sustainability,and high-quality economic growth.

Exploration of Smart City Construction

In recent years,all walks of life have begun to propose the construction of“smart cities”.It is hoped that the construction of“smart cities”can pro-mote the transformation and upgrading of urban development and make our cities prosperous and sustainable.In the future,urban construction is very likely to develop in the direction of intelligence and intelligence,and a scientific and effective understanding and objective evaluation of the devel-opment status of China’s smart cities will be conducive to the planning and design of China’s smart cities in the new era,formulate scientific construc-tion policies,and strengthen the supervision and guidance of construction.At present,as far as China is concerned,the urbanization process is accel-erating,the urbanization rate is increasing year by year,and the level of urbanization has increased significantly,and people are beginning to think about how to better combine technology and services to serve the people.Smart cities,as one of the concerns,may be able to better solve this kind of problem.

IoT-Based Management of Smart City Infrastructure

This thesis explores the integration of the Internet of Things(IoT)in managing smart city infrastructure,highlighting its transformative potential across various urban systems,including traffic management,energy optimization,and public safety.As urbanization accelerates globally,cities face mounting challenges,including traffic congestion,excessive energy consumption,and security concerns.IoT-based solutions offer data-driven approaches that leverage real-time monitoring,advanced analytics,and automated decision-making to enhance operational efficiency,promote sustainable practices,and improve quality of life for urban residents.This study examines key IoT applications,identifies infrastructure management challenges,and demonstrates the value of decision support systems(DSS)and feedback mechanisms for adaptive city management.Findings indicate that while IoT deployment poses challenges related to data interoperability,security,and scalability,the advantages it brings in predictive analytics,efficient resource management,and real-time response to urban needs make it a cornerstone for the future of sustainable cities.

Key networks to create disaster resilient Smart Cities Mission: A case for remodeling India’s Smart Cities Mission to include disaster resilience

Amidst a concerning surge in urban losses attributed to disasters,this research paper explores the intricate relationship between urban development,disaster mitigation,and resilience emphasizing the significance of addressing disaster vulnerability in urban settings,where a substantial portion of the population faces risks stemming from high population density,limited resilience,and inadequate coping capabilities.The study advocates for the integration of disaster resilience principles into the Smart Cities Mission of India,placing particular emphasis on the necessity of developing infrastructure,establishing early warning systems,and fostering community engagement to bolster urban resilience.Furthermore,the paper draws comparisons and parallels between the components of smart cities,mitigation strategies,and disaster resilience,illuminating their interconnectedness and potential synergies.In conclusion,the study recommends the incorporation of essential network elements to establish a Smart Cities Mission that is resilient to disasters,ultimately aiming to safeguard urban communities from the adverse impacts of future calamities.

Smart City Rail Transit Operation and Management Information Construction Strategy

Rail transit is considered one of the safest and most efficient modes of transportation.Ticketing,vehicle dispatching,and passenger flow control during rail transit operations in China have been improving over the years.Smart city construction and intelligent management models has also been increasingly emphasized with the rapid development of information and internet technology.Therefore,it is essential to conduct relevant research and discussions to improve the overall efficiency and quality of urban rail transit operation and management.This article provides an overview of smart city rail transit operation and management informatization,the principles of construction,and the functions of smart city rail transit operation and management informatization.Additionally,it discusses the strategies for the construction of smart city rail transit operation and management information and its development prospects.

On the Influence Factors of Second-hand House Prices in First-tier Cities——Empirical Analysis Based on Panel Data

With the arrival of the ＂housing stock＂ in first - tier cities, the second - handhousing^market will become the dominant property market. This ardcle aim to the first - tiercities of second - hand housing prices and new home price index for the empirical analysis, thedata related to the cointegration analysis found that the result of the first -tier cities real estatemarket in China, the new home price index is the significant factors influencing the second -hand house price indexi For Beijing, Shanghai second - hand housing and new home price in-dex time series johans test, found that there exists cointegration relationship between two varia-bles,the new city real estate market prices out of a line on the secondary market have clearguide. Therefore, the real estate market regulation aiming at the first -tier cities and the＂housing stock＂ should take the second - hand housing market as the main direction, startingwith the sale price and influencing factors of new houses. At the same time, in different cities,we should adhere to the city＇ s policies, reflect the policy differentiation, promote the reformof the real estate supply side, and promote the return of housing properties.

Influence of Social Life on Islamic City＇s Planning and Arabic House＇s Design

The originating point of this study on the social life of the Arab world and its influence on architecture and city planning lays in the simple observation of true facts of daily life which are characteristic to the Arabic Society. So the author analyses

The Application of Old City Planning Based on the Concept of Smart Cities: A Case Study of Wanli District, Nanchang

The impact of a smart city as one of the new urban forms on the city is still in the exploratory stage. Therefore, it is necessary to fully analyze the impact of a smart city in the urban planning field, and actively explore the planning ideas and methods that are compatible with the planning and renovation of the old city. On the basis of applying the concept of smart cities, Wanli District of Nanchang City has paid attention to the optimization of urban spatial structure, focused on the development of tourism industry, built an intelligent transportation system with priority to public transport, and improved infrastructure construction, in order to provide guidance for the wisdom update of the old city.

HoD Detector, a System to Create Indicators about the Happiness of Citizens in a Smart City: Case of Study—GDL Smart City

Happiness is the ultimate goal for every living human being, and this condition motivates people to stay active and want to be alive. Having this feeling also fosters the proactivity of citizens. The opposite is depression, a condition capable of significantly affecting a person’s behavior or perception. HoD Detector is a low-cost, easy to use application that aids in the diagnosis of a depressive disorder and motivates the user to seek professional help. The purpose of this study is to propose a way to measure happiness through the measurement of depression;to develop HoD Detector, evaluate the accuracy and usability of this application (with university students) for future enhancements of the system. The development of this application involved basic algorithms and the use of a database to successfully make a diagnosis and store the results of each user for further reference. The application is capable of giving a proper diagnosis with the time interval of 2 - 5 minutes. HoD Detector has the potential to become an extremely useful tool to diagnose depression and motivate users to seek professional help not only in Mexico, but also on an international scale for improving in people’s happiness condition.

Development of Online Based Smart House Renting Web Application

The house rental issue is one of the elemental parts of society. Nowadays, it is extremely difficult to find suitable accommodation in city areas if people search for it physically. On the other hand, the land owner also needs to rent the house. It can be difficult to find tenants just to hang a lease sign on a building, and as a result, they lose money. An online common platform can play a vital role in this case. The purpose of the study is to develop a common web-based online platform for both tenants and house owners so that both tenants and landowners will mutually benefit from the system. This paper presents the development of web applications for the people of Bangladesh where both house owners and tenants can register and tenants can have houses for rent via sophisticated contact with the house owner. In this paper, a common online-based smart house rental web application has been developed both for tenants and for house owners. This web application is very user-friendly, efficient and it has got many unique features that are not offered by other currently available house rental websites here in Bangladesh. Tenants can register using their phone number, store information about their identity, search for available houses, send messages to house owners, and choose a suitable house using developed web applications. House owners can also register for the system, which will manually verify and authenticate the knowledge provided by the house owner can view a tenant’s information history whenever a tenant makes contact through text and supply house-related information accordingly. The proposed online smart house system has been tested and validated. It works very efficiently with many features. The application provided faster and improved opportunities to get houses, as well as ensuring the availability of houses for rent in the greatest number of areas. The system will help to spread trustworthy services nationwide and supply users with the chance to speak and improve the house rent in Bangladesh. Because it has many smart features, this developed online smart house rental web application will make it very easy for tenants to find a house to rent. House owners, on the other hand, can easily rent out their properties.

Inner-City Neighbourhood Changes Predicted from House Prices in Windsor, Ontario, since the Early- or Mid-1980s

Changes in prices of homes are hypothesized as correlated with the times of their sale and resale and the attributes of their dwelling unit and neighbourhood and those of neighbouring homes. They may also be correlated with the occurrences of events inside the neighbourhoods caused by the activities of individuals and organizations outside the neighbourhoods, such as whether the local economy is in a recession or has a high unemployment rate. Calibrated hybrid housing price models predict precipitous decreases in house prices of approximately 2900 sold and resold homes in two inner-city neighbourhoods in Windsor, Ontario, during those events since 1981 or 1986. Overall modest predicted percentage increases in houses’ prices during more than 30 years therefore subsumed periods of inner-city neighbourhood deterioration in dispersed locations of unimproved and disimproved homes. Compensatory predictions however are of increasing prices for minorities of homes with improvements to several attributes of the dwelling unit and neighbourhood.

Enlightenment of Smart Growth Theories on the Development of Nanjing City,China

The background and connotations of smart growth theories of America were introduced first,spatial expansion features of Nanjing City were summarized as the following 3 points:population growth,expansion of urban spaces and industrial expansion.And then problems emerged in the spatial expansion were pointed out as:A."Sprawl" in the urban development;B.Improper internal spatial structure of the city;C.Destructed historical and cultural context of the city.Smart growth theories were applied in this study to analyze potential problems in the spatial expansion of Nanjing,corresponding countermeasures were given as:defining proper growth boundaries,restricting total growth volume,saving land;strictly controlling growth intensity,fully utilizing resources,intensively using land;scientifically evaluating growth benefits,promoting recycling of resources,and realizing sustainable growth.By learning from overseas smart growth theories,the authors hoped to provide useful references for the overall land use planning and urban planning of Nanjing City.

Blockchain-based sharing services:What blockchain technology can contribute to smart cities

Background:The notion of smart city has grown popular over the past few years.It embraces several dimensions depending on the meaning of the word“smart”and benefits from innovative applications of new kinds of information and communications technology to support communal sharing.Methods:By relying on prior literature,this paper proposes a conceptual framework with three dimensions:(1)human,(2)technology,and(3)organization,and explores a set of fundamental factors that make a city smart from a sharing economy perspective.Results:Using this triangle framework,we discuss what emerging blockchain technology may contribute to these factors and how its elements can help smart cities develop sharing services.Conclusions:This study discusses how blockchain-based sharing services can contribute to smart cities based on a conceptual framework.We hope it can stimulate interest in theory and practice to foster discussions in this area.