Smart City Components Research Articles

Cybersecurity and Cyber Forensics for Smart Cities: A Comprehensive Literature Review and Survey.

Smart technologies, such as the Internet of Things (IoT), cloud computing, and artificial intelligence (AI), are being adopted in cities and transforming them into smart cities. In smart cities, various network technologies, such as the Internet and IoT, are combined to exchange real-time information, making the everyday lives of their residents more convenient. However, there is a lack of systematic research on cybersecurity and cyber forensics in smart cities. This paper presents a comprehensive review and survey of cybersecurity and cyber forensics for smart cities. We analysed 154 papers that were published from 2015 to 2022 and proposed a new framework based on a decade of related research papers. We identified four major areas and eleven sub-areas for smart cities. We found that smart homes and the IoT were the most active research areas within the cybersecurity field. Additionally, we found that research on cyber forensics for smart cities was relatively limited compared to that on cybersecurity. Since 2020, there have been many studies on the IoT (which is a technological component of smart cities) that have utilized machine learning and deep learning. Due to the transmission of large-scale data through IoT devices in smart cities, ML and DL are expected to continue playing critical roles in smart city research.

Fog computing-assisted path planning for smart shopping.

A Smart City (SC) is a viable solution for green and sustainable living, especially with the current explosion in global population and rural-urban immigration. One of the fields that is not getting much attention in the Smart Economy (SE) is customer satisfaction. The SE is a component of SC that is concerned with using Information and Communication Technology (ICT) to improve stages of the traditional economy. In this paper, we propose a fog computing-based shopping recommendation system. Our simulations used Al-Madinah city as a case study. It aims to improve the customer shopping experience. Customers in shopping malls can connect to the system via Wi-Fi. Then the system recommends products to the shoppers according to their preferences. It optimizes shoppers' schedules using price, the distance between the shops, and the congestion. It also improves customers' savings by up to 30%. It also increases the shopping speed by up to 6.12% compared to the system proposed in the literature.

Plastic waste management in the smart cities: Poland and Turkey as a case study

Introduction/background: Waste in various forms, such as solid waste, gaseous waste, and liquid waste, increases as a result of population growth, urbanization, and industrialization, and has a global impact. Waste management entails activities such as reuse, recycling, and reducing waste generation, as well as other strategies to combat the effect of waste generation caused by increasing population and industrialization. Monitoring is a critical function of waste management because it is required to address waste management issues such as waste generation, waste collection, waste transportation, waste treatment, and waste disposal. The article presents plastic waste management in the context of smart cities. Purpose: The goal of the article is to present and compare of the production of plastic waste in Poland and Turkey in the context of smart cities. Sustainable and eco-innovation plastic waste management solutions to reduce plastic waste are provided to be implemented in smart cities. In this study, smart cities are explained, how to manage plastic waste by using smart city components, and methods of dealing with plastic waste are explained. Methodology: The article is based on a review of the literature, own observations and own experience. The currently available plastic waste management solutions were analyzed and examples in the implementation of the technology in a smart city are described. Findings: The incorporation of smart city technology into waste management practices provides a smart way to solve waste issues. The main of plastic waste management is to develop methods to transform plastic waste into a circular economy. As estimated by 2030 plastic leakage to ecosystems should be 30% reduced, double the global recovery of plastic (collection and recycling), and shift to sustainable inputs for remaining plastic, including recycled content, sustainably sourced biocontent, advanced products and reducing unnecessary plastic through a business model, innovation, reduction and substitution. Originality: The goal of waste management is to recover as much useful material as possible, including energy. Waste generated in smart cities is a category of municipal waste. Traditional approaches to waste management have failed because they are not reliable or sustainable because they require a lot of input for little or no work output. The incorporation of smart city technology into waste management practices provides a smart way to solve waste issues. The main of plastic waste management is to develop methods to transform plastic waste into a circular economy. Keywords: Plastic wastes, waste management, smart cities, eco-innovation solutions.

Investigation of Smart City Components by AHP-BWM-FUCOM and DEMATEL Methods

The concept of smart city has emerged with the development of technology in the 21st century, based on the ideal city concept introduced in the 19th century. 
 Although over forty smart city components can be counted in the literature, the main six elements which are smart economy, smart people, smart governance, smart mobility, smart environment and smart living are mostly included in the studies.
 In this study, these six main smart city components is weighted by one of the most widely used MCDM techniques AHP, DEMATEL and more recently developed techniques BWM and FUCOM. The results of comparison is given at the end.

Prospects for the Formation of a Smart Destination as a Determining Factor in the Modernization of Urban Infrastructure and a Means of Sustainable Urban Tourism Development in Kazakhstan

New requirements of society for the provision of tourist services are shaped by informatization and the transformation of society into one of modern technology. The value of the innovative component of tourist service provision, modernization of priorities in the consumer market, communicative interaction with consumers using the latest technology, and other components call for new approaches and methods in the formation of the complex of relationships in tourist destinations. In this, of importance is the need for scientific research into the formation of a smart destination of the megapolis as a certain factor in the modernization of urban infrastructure. The purpose of the study is to discover prospects for the formation of a smart tourist destination of the metropolis as a decisive factor in the modernization of urban infrastructure and the means of sustainable development of urban tourism. Analysis of research results points to the key technological developments used in smart tourist destinations, as well as the universal mobile travel applications most relevant in Kazakhstan's megacities. The authors conclude that smart tourist destinations can function as the components (elements) of smart cities, giving opportunities for the formation and promotion of the tourist product and the development of urban infrastructure.

Achieving Sustainability in Smart Cities & Its Impact on Citizen

Life became digitalized and smartly controlled that requiring more energy usage. Smart cities and urbanization focus on the challenge of worldwide urbanization through the recognition of opportunities to integrate social, physical, environmental and technological infrastructure. Urbanization expands the need of all services including water, power, transportation, as well as other facilities. All those infrastructures should be delivered to citizen within a short period of time with very well controlled systems to provide more simple and comfortable life. Furthermore, stakeholders and citizens should be responsible and cooperative with government and organizations in order to achieve better solution for smart sustainable living approach. Although the smart urbanization has the potential to become a positive transformative force for every aspect of sustainable development in cities, there is a lack of knowledge using the smart and sustainable concepts in cities. Therefore, this paper aims to propose a framework which merges the sustainable aspects with the Smart city components. The paper started by an analytical study about smart cities fields and their needs, then a study for sustainability aspects, all this end with a framework tested by a questionnaire to propose guidelines and recommendations to be followed by city planners in order to achieve sustainability goals in smart cities for better impact on citizens.

SMART ENVIRONMENT INDEX PREDICTION OF SMART CITY USING POLYNOMIAL REGRESSION

Smart Environment refers to environment where pollution is detected, predicted, classified and solved using smart tools and technology such as using Internet of Things (IoT) sensors, cloud service, and machine learning algorithms. Episodic environment index prediction allows governments and local city agency to detect pollution in environment at a premature stage to initiate proper steps. Advancements in machine learning, sensor, and camera technology have endorsed us to do that, which can benefit millions of cities and its citizens indeed. This paper describes a new method for smart environment index prediction based on index of five others smart city components using polynomial regression. This research mainly works with the Smart Cities Index dataset. We attempted numerous steps to select feature and to filter its contents to make them more apposite for selected regression algorithm. Our approach unites several feature selection techniques, outlier detection technique, polynomial degree selection technique, and random state selection technique, which outcomes in a reduction of Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) to 0.0000000140, 0.000000000000000322, and 0.0000000179 respectively and rise R2 to 1.0 for prediction. This method can be a valuable tool for smart environment index prediction from smartness of various components of a city, thus drastically reducing survey or other related works.

A Q-Learning and Fuzzy Logic-Based Hierarchical Routing Scheme in the Intelligent Transportation System for Smart Cities

A vehicular ad hoc network (VANET) is the major element of the intelligent transportation system (ITS). The purpose of ITS is to increase road safety and manage the movement of vehicles. ITS is known as one of the main components of smart cities. As a result, there are critical challenges such as routing in these networks. Recently, many scholars have worked on this challenge in VANET. They have used machine learning techniques to learn the routing proceeding in the networks adaptively and independently. In this paper, a Q-learning and fuzzy logic-based hierarchical routing protocol (QFHR) is proposed for VANETs. This hierarchical routing technique consists of three main phases: identifying traffic conditions, routing algorithm at the intersection level, and routing algorithm at the road level. In the first phase, each roadside unit (RSU) stores a traffic table, which includes information about the traffic conditions related to four road sections connected to the corresponding intersection. Then, RSUs use a Q-learning-based routing method to discover the best path between different intersections. Finally, vehicles in each road section use a fuzzy logic-based routing technique to choose the foremost relay node. The simulation of QFHR has been executed on the network simulator version 2 (NS2), and its results have been presented in comparison with IRQ, IV2XQ, QGrid, and GPSR in two scenarios. The first scenario analyzes the result based on the packet sending rate (PSR). In this scenario, QFHR gets better the packet delivery rate by 2.74%, 6.67%, 22.35%, and 29.98% and decreases delay by 16.19%, 22.82%, 34.15%, and 59.51%, and lowers the number of hops by 6.74%, 20.09%, 2.68%, and 12.22% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it increases the overhead by approximately 9.36% and 11.34% compared to IRQ and IV2XQ, respectively. Moreover, the second scenario evaluates the results with regard to the signal transmission radius (STR). In this scenario, QFHR increases PDR by 3.45%, 8%, 23.29%, and 26.17% and decreases delay by 19.86%, 34.26%, 44.09%, and 68.39% and reduces the number of hops by 14.13%, 32.58%, 7.71%, and 21.39% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it has higher overhead than IRQ (11.26%) and IV2XQ (25%).

Towards green smart cities using Internet of Things and optimization algorithms: A systematic and bibliometric review

Energy efficiency is an important concern that the scientific community and society will have to deal with in the coming years. Power-efficient structures and effective energy resource management in critical locations, such as tourist spots, have become a crucial problem that must be considered by environmental scientists and governments worldwide. The primary objective is to decrease the ecological effect of energy usage. Also, smart city activities are currently being aided by many innovative technologies such as the Internet of things and cloud computing. Because of the lack of comprehensive study in this field, this study aims to present a systematic and bibliographic overview of the literature on improving the energy efficiency of smart city equipment. This page presents the geographical locations where most publications in this discipline have been released. It provides a wide-ranging, accurate, and novel review of literature on optimizing the energy performance of smart city components. Utilizing computational optimization algorithms in this domain also opens up new perspectives in terms of energy efficiency. The results showed that these algorithms have successfully optimized energy consumption and reduced pollution and emissions of greenhouse gases.

Aplicações de Destino Inteligente de acordo com a Roda da Cidade Inteligente de Cohen:

Since the innovative use of technological systems provides many advantages and convenience to cities, the tendency towards smart applications in cities is increasing. The "smart city" concept, accepted as the new city concept, adopts an innovative and sustainable management style integrated with information and communication technologies in order to find solutions to the problems of cities. By making use of smart city applications, destinations implement smart tourism applications and this provides various conveniences and opportunities to both tourists and tourism stakeholders. In addition, destinations with smart tourism applications provide competitive advantage and increase the quality of tourists' travel experience. İzmir, one of the important destinations of Turkey and visited by many tourists every year, is one of the cities that stand out with its smart city and smart tourism applications. In this context, the aim of the study is to examine the smart city components of İzmir according to Cohen's Smart City Wheel and to determine the studies made to become a smart tourism city based on these applications. In order to achieve this aim, interview technique, one of the qualitative research methods, was used in the research. According to the research findings, the questions directed to the participants regarding smart tourism applications were gathered under 7 themes. These themes were analyzed in the Nvivo 12 package program, including 6 themes (smart mobility, smart living, smart people, smart economy, smart government, smart environment) and smart tourism applications in line with Cohen's smart city dimensions. It is thought that the smart city and smart tourism applications in İzmir will contribute to the residents and tourists visiting the city in terms of easy access, accessibility, sustainability, increasing the quality of life and competitiveness of the destination.

Symmetrical Simulation Scheme for Anomaly Detection in Autonomous Vehicles Based on LSTM Model

Technological advancement has transformed traditional vehicles into autonomous vehicles. Autonomous vehicles play an important role since they are considered an essential component of smart cities. The autonomous vehicle is an intelligent vehicle capable of maintaining safe driving by avoiding crashes caused by drivers. Unlike traditional vehicles, which are fully controlled and operated by humans, autonomous vehicles collect information about the outside environment using sensors to ensure safe navigation. Autonomous vehicles reduce environmental impact because they usually use electricity to operate instead of fossil fuel, thus decreasing the greenhouse gasses. However, autonomous vehicles could be threatened by cyberattacks, posing risks to human life. For example, researchers reported that Wi-Fi technology could be vulnerable to cyberattacks through Tesla and BMW autonomous vehicles. Therefore, further research is needed to detect cyberattacks targeting the control components of autonomous vehicles to mitigate their negative consequences. This research will contribute to the security of autonomous vehicles by detecting cyberattacks in the early stages. First, we inject False Data Injection (FDI) attacks into an autonomous vehicle simulation-based system developed by MathWorks. Inc. Second, we collect the dataset generated from the simulation model after integrating the cyberattack. Third, we implement an intelligent symmetrical anomaly detection method to identify false data cyber-attacks targeting the control system of autonomous vehicles through a compromised sensor. We utilize long short-term memory (LSTM) deep networks to detect False Data Injection (FDI) attacks in the early stage to ensure the stability of the operation of autonomous vehicles. Our method classifies the collected dataset into two classifications: normal and anomaly data. The experimental result shows that our proposed model’s accuracy is 99.95%. To this end, the proposed model outperforms other state-of-the-art models in the same study area.

Transitioning from Wired City to Super City: a review of selected 'Smart City' case studies.

The contemporary technological advancements of the twenty-first century are introducing paradigm shifts in every aspect of life. The “Smart City” concept has also brought the latest emerging technologies and their applications to the urban areas. The integration of Nano-technological devices collecting and transmitting data coupled with the availability and penetration of high-speed internet will only raise this potential by providing an easy way to receive and send real-time data more swiftly. The devices could also be connected with each other via the internet under the Internet of Things (IoT), making it possible to establish the machine to machine (M2M) communication between them. This large amount of urban Big Data can also deploy machine learning assisted techniques to ensure robust and precise urban analysis for getting significant insights and desired simulations ensuring the proper deployment as well as utilization of the phenomenon of Urban Intelligence. As the cities are entitled to become “Smart” in due course of time, these Information and Communication Technologies (ICTs) will play a major role in improving the efficiency and effectiveness of urban services and management. Due to their highly versatile and adaptable nature, these technologies can be linked with different components of Smart City thereby enhancing the efficiency and capability of the existing urban systems. This paper discusses the emerging concept of the Internet of Things (IoT) and other associated technologies within the context of contemporary urban scenarios through relevant case studies. It further presents crucial insights based on the influence of these technologies as well as their associated challenges while also exploring the implications of the concepts like ‘Super City’ on the cities of tomorrow.

A Hybrid Model for Intrusion Detection in IoT Applications

Internet of Things (IoT) networks has recently become an important component of smart cities, smart buildings, health care, and other applications. It finds it beneficial due to the inherent characteristics of low cost, compact, and low-powered IoT devices. At the same time, security remains a challenging issue in the design of IoT networks. Intrusion detection systems (IDS) can be used to identify the occurrence of intrusions in the network, i.e., abnormal activities in the network. The latest advances in machine learning (ML) and metaheuristics can be employed to design effective IDS models for IoT networks. This article develops a novel political optimizer with cascade forward neural network (PO-CFNN-)-based IDS in the IoT environment. The major intention of the PO-CFNN technique is to determine the occurrence of intrusions from the IoT environment. The PO-CFNN technique follows three major processes, namely, preprocessing, classification, and parameter optimization. Initially, the networking data is preprocessed to transform it into a useful format. Following that, the CFNN technique is employed for the identification and classification of intrusions in the IoT environment. In the final stage, the PO algorithm is applied for the optimal adjustment of the parameters involved in the CFNN model. The experimental validation of the PO-CFNN technique on a benchmark dataset stated the better outcomes of the PO-CFNN technique over recent approaches.

Sustainability-oriented innovations in smart cities: A systematic review and emerging themes

The purpose of the paper is to clarify the relationship between sustainability-oriented innovations (SOI) and smart city development based on the systematic review of existing literature in the field. As an outcome of the review process, 159 articles were carefully selected for the in-depth analysis of the inter-linked concepts of smart city and sustainability-oriented innovations. The results show a growing trend of research papers in this field, especially in the last five years. The findings show the significance of a systemic multi-dimensional view of innovations for the smart sustainable development of cities. We have identified four main perspectives through which the scholars discourse the SOI dimensions in the smart city context: technology perspective, organizational perspective, social innovation perspective with citizen engagement, as well as system-level changes with innovation ecosystems. Second, we have recognized various focused themes under each main perspective. The various types of innovations also have impacts on different components of smart cities. Although the technological innovation perspectives dominate, and governance aspects are also paid attention to in recent studies, the increasing amount of research outputs also report on the developments of other components and perspectives, such as new human-centric approaches like citizen engagement.

Smart Bus Terminus: Sustainable Urban Public Transport Solution Through BIM and GIS Integrated Approach

Smart city / digital city is engaging in Big Data which will be utilized in monitoring and optimizing the urban systems to minimize resource consumption and maximize the quality of life. To implement the concept of “smart cities”, smart city components, design innovation and prototypes must be studied in detail which will be beneficial in understanding the features. India is moving towards becoming one of the developed nations, the source of revenue is highly dependent on public contributions, especially through the transportation sector. The population of India is majorly comprised of the middle-class income category. Their livelihood mainly depends on the regional level jobs and for commute, they prefer public transportation especially Buses. For lodging these buses that are huge in number, Bus Terminus become an integral infrastructure component. In Indian cities, the existing bus terminus appears to be poorly designed and highly congested irrespective of their sizes. Interventions of modern methodologies to improve the conditions in the existing bus terminus in various Indian cities and reconstructing them is of utmost priority for urban planners and policymakers to reach sustainable cities. The objective of adopting smart innovative solutions in Bus Terminus is to reduce pollution, congestion of traffic, improve safety, time optimization and cost reduction. Modern bus terminus must accommodate some key features such as green buildings and utilization of eco-friendly materials for construction, incorporating real-time response, installing solar panels for energy efficiency and power generation, waste segregation and recycling, the hybrid modal form of transport i.e., both traditional and electric vehicles, etc. In the present study, the attempt has been made to develop an artistic view of a “Smart Bus Terminus” prototype that can be adopted at regional and global levels. Autodesk REVIT Architecture and AutoCAD have been used to design and create 3D models; Geographical Information System tools have been adopted for the recommendation of site selection.

Smart buildings for smart cities: Analysis of the Smart Readiness Indicator

Subject of this study is the analysis of the Smart Readiness Indicator (SRI), as well as its application for a residential building in Greece. The indicator, which was firstly introduced in the revised EPBD in 2018, assesses the buildings’ smart readiness through the examination of the presence and the evaluation of the functionality level of smart services. Its goal is the promotion of buildings that are energy efficient, adaptive to their users’ needs, and flexible in respect of their electricity demand, according to the three key - functionalities, as stated by the Directive. A smart building is not only characterized by its sustainability but also by its adaptiveness to the environmental conditions and its users’ preferences. Smart buildings are a basic component of smart cities, which utilize a great range of smart technologies aiming at the improvement of their citizens’ lives. The Smart Readiness Indicator as well as the sub indicators evaluate the smart buildings using a multicriteria assessment method, which is thoroughly described in this paper. Finally, the indicators’ calculation is executed for a residential building in Greece leading to results, which are discussed along with identified methodology shortcomings and difficulties.

(Re)Considering Smart City Approach in Smart Economy Perspective: Evaluation of Konya Case

It is aimed with this paper to put smart city into smart economy perspective by conceptual framework and analysis. The relation of smart economy components with local economic development have been discussed. Therefore, this study has three key parts. The first part highlights the smart city and smart economy literature. Smart city approach has been discussing in terms of institutional based, environment based and economic based. Smart economy is a new economic approach reflection of smart city approach. Smart economy as one of the component of smart city enables to increase attractiveness of current economic sectors like finance, Information and Communication Technologies (ICT), service and cultural. It enables to occur new economic sectors (sharing economy and clean/green economy). Therefore, the second part investigates the effectiveness of smart economic approach in Turkey with case specific method. Konya in Turkey was selected for testing of smart city inquiry by using municipality’ website & TURKSTAT data with LQ analysis. According to these findings, Konya may not be seen as a real smart city in smart economy perspective due to two reasons. The first reason is current economic sectors under the entrepreneurship have not developed sufficiently according to LQ analysis results. The second reason why Konya may not be a smart city that sharing and cluster based economy have not become popular adequately and production of data about these issues is underestimated. Therefore, third part includes opportunities and limits determined to be smart city especially in economic perspective in the future.

Privacy-Preserving Active Learning on the Internet of 5G Connected Artificial Intelligence of Things

With the advancement in 5G/6G networks, secure communication can help to develop data security applications. A layered network in the Artificial Intelligence of Things helps to assist data monitoring for the operation of critical components of smart cities. Unmanned aerial vehicles (UAVs) are often connected to the mobile network and are vulnerable to identify thefts and attacks. Safe UAV communication can help a number of data-driven applications to perform critical tasks. We introduce a deep reinforcement learning technique for sensitizing private information for a specific vehicle link across vehicular ad hoc networks. We use entropy-based active learning to classify the sensitive sensors data. The entropy-based active-learning-based method significantly increases training instances for the deep attention-based model. The proposed method helps introduce the new features based on the 5G/6G network while balancing safety, privacy, security, and confidentiality through a sanitization procedure.

Hierarchy table of indicators and measures for the current status assessment of urban roads in smart cities

• A hierarchy table of indicators and measures for service areas is required for a smart city. • Keyword network analysis is used to develop a hierarchy table for urban roads in a smart city. • City officials can utilize the developed hierarchy table to understand the basic need for their road facilities to innovate towards a smart city. • The procedures presented to develop our hierarchy table can be utilized to develop other smart city service areas. Urban roads integrated with modern, innovative technologies (called advanced systems) serve as one of the primary service areas to support the function of a smart city. The extensive experience with the benefits that these advanced urban roads provide informs decision-makers toward efficient investments in advanced systems for urban roads. However, there is no tool designed to evaluate the developmental status of urban roads in a smart city. Therefore, this study has developed a hierarchy table of indicators and measures specific to assessing the current status of urban road innovation for smart cities. A keyword network analysis was used to develop the hierarchy table. The procedures take three phases: data preparation, data analysis, and hierarchy table development. As a result, the hierarchy table includes 53 measures in 14 indicators connected to the five smart city components (e.g., environment, mobility, governance, economy, and living). The hierarchy table can be used for city officials to assess the current status of urban roads in the transition of a smart city, which leads to an explicit investment decision on urban road innovation. The procedures presented in this study can be adapted to develop indicators and measures for other service areas necessary for a smart city.

Study on the Case of Songdo Smart City based on the Citizen Participation Approach

The purpose of this paper is to explore the level of citizen participation in Songdo smart city project, once called U-city project, in order to provide citizens with U-service anywhere by using new IT technology in the Incheon Free Economic Zone, a landfill site. To this end, it reviews the literature on smart city, and derives project’s problems, evaluates according to the framework, and proposes implications. This paper uses the “Citizen Participation Evaluation Framework” formalized by Simonofsky and his colleagues and analyzes civic participation method by dividing it into democratic participants, co-creators, and ICT users. The level of citizen participation in the Songdo project is evaluated according to the criteria presented by this framework and the results are presented. The analysis period is from 2003 to 2016, when the government office was opened and the initial foundation was completed. As a result of analysis, Songdo had built open data and infrastructure for citizens, but citizens were participated as ICT users only. Although citizens living in smart cities should be the co-creators and participants in democratic decision-making for solving urban problems, Songdo was missing these factors. In conclusion, this paper argues that Songdo remains in the U-city paradigm as the 'smart people', a key element among the smart city components, has been neglected and ultimately reveals a fundamental limit to its growth into a sustainable smart city. In addition, suggestions for improvement are presented. This paper is meaningful in that it presented lessons and implications that the human factors should be emphasized as the subject of technology and services to develop into an authentic smart city through the case of Songdo.