Simulation modeling of the smart city system: The concept, methods, and cases

The rapid advancement of global urbanization demands creative strategies for urban management, establishing smart cities as essential frameworks for sustainable development. This article analyzes the essential connection between smart city systems and internet infrastructure architecture, investigating how this symbiotic relationship propels urban transformation. Smart cities use information and communication technologies across six fundamental pillars: government, environment, transportation, economy, living, and populace. These projects essentially rely on a resilient internet infrastructure that includes high-speed broadband, fiber-optic networks, 5G connectivity, cloud computing, and edge computing systems facilitating real-time data interchange among millions of networked Internet of Things devices. The report examines how internet infrastructure serves as the fundamental framework for intelligent transportation systems, e-governance platforms, smart energy grids, telemedicine services, and environmental monitoring applications. In contrast, the increasing requirements of smart city applications expedite technological advancements in internet infrastructure, especially in ultra-low latency networks, improved cybersecurity protocols, and broader broadband implementation. The research analyzes global case studies, including Barcelona, Singapore, Songdo, Dubai, Amsterdam, New York City, and Masdar City, to illustrate practical applications of internet-enabled smart solutions. Nonetheless, considerable challenges remain, such as cybersecurity vulnerabilities impacting interconnected systems, digital divide issues restricting equitable access to services, substantial deployment costs hindering implementation in developing regions, and interoperability challenges among various technological platforms. The article presents a detailed framework for the development of Internet of Things-enabled smart cities, including evaluations of infrastructure preparedness, strategic application implementation across urban sectors, and unified modeling language diagrams depicting system architecture and operations. The findings underscore that effective smart city development necessitates coordinated governance strategies that harmonize technology progress with goals of accessibility, security, and sustainability. This comprehensive viewpoint offers significant insights for legislators, urban planners, and technology developers maneuvering through the intricate realm of digital urban transformation.

Smart city concept redefines the urban planning and development of the existing and new cities. It drives on economic, social, and environmental sustainability of a city and attracts citizens, professionals, and corporations to build sustainable living. It portrays a city that is operationally optimal and provides a space for innovation. This is achieved through state of the art physical, institutional, and digital infrastructure. This chapter addresses the challenges of the digital aspect of the smart city. Enterprise systems technology is widely used in the organizations and will be utilized in the Smart city systems conceptualization and implementation. Smart city systems definition has been derived by analyzing the smart city requirements. Enterprise systems technology has been explained and the latest ICT trends have been explored to develop the technological foundation of smart city systems. Finally, we introduce partial least square regression, a structural equation modeling method to explore interrelationships between different interdisciplinary constructs and show its application to studying smart city systems. From the digital perspective of smart city, it may be concluded that connectedness leads to integration and integration leads to dynamism and dynamism leads to smartness and cycle continues to realize the best in class smart city.

Wastewater management is a mechanism that is used to extract and refine pollutants from wastewater or drainage that can be recycled to the water supply with minimal environmental effects. New methods and techniques are required to ensure safe and smart wastewater management systems in smart cities because of the present deteriorating environmental state. Wireless sensor networks and the Internet of Things (IoT) represent promising wastewater treatment technologies. The elaborated literature survey formulates a conceptual framework with an Internet of Things (IoT)-based wastewater management system in smart cities (IoT-WMS) using blockchain technology. Blockchain technology is now being used to store information to develop an incentive model for encouraging the reuse of wastewater. Concerning the quality and quantity of recycled wastewater, tokens are issued to households/industries in smart cities. Nevertheless, this often encourages tampering with the information from which these tokens are awarded to include certain rewards. Anomaly detector algorithms are used to identify the possible IoT sensor data which has been tampered with by intruders. The model employs IoT sensors together with quality metrics to measure the amount of wastewater produced and reused. The simulation analysis shows that the proposed method achieves a high wastewater recycling rate of 96.3%, an efficiency ratio of 88.7%, a low moisture content ratio of 32.4%, an increased wastewater reuse of 90.8%, and a prediction ratio of 92.5%.

In the Smart City, the Integrated Renewable Energy System (IRES) is playing a crucial role. Integrating the available renewable energy sources is useful in solving energy supply and demand-related issues. For a stable state of energy supply and energy demand, their proper size is needed to adapt to integrated renewable energy sources in the future. To address technical, economic and sizing problems, different algorithms needed to implement the integrated renewable energy scheme, as suggested by various authors. This paper provides a comprehensive review of various topics related to power generation for Smart City based on Integrated Renewable Energy System (IRES). It discusses in detail issues related to the integration of different energy sources, use of smart grids for integration, methods of IRES sizing using software followed by methods of sizing using artificial intelligence algorithms. This article reviews different AI algorithms that focus on the sizing of integrated renewable energy systems in smart cities.

The process of extracting and refining contaminants from drainage or wastewater so they can be recycled back into the water supply with the least amount of negative environmental impact is known as wastewater management. The current declining environmental condition necessitates the development of new strategies and tactics to guarantee safe and intelligent wastewater management systems in smart cities. The Internet of Things (IoT) and wireless sensor networks are potential technologies for treating wastewater. The comprehensive literature review develops a conceptual framework utilizing blockchain technology for an Internet of Things (IoT)- based wastewater management system in smart cities (IoT- WMS). Information is now being stored using blockchain technology to create an incentive scheme that promotes the reuse of waste water. In smart cities, tokens related to the quantity and quality of recovered wastewater are distributed to homes and businesses. However, this frequently promotes manipulating the data used to award these tokens in order to incorporate particular benefits. To determine whether there is evidence of altered IoT sensor data, anomaly detector techniques are employed. In order to facilitate the most efficient distribution of water depending on user usage at the plot holding level, this study suggests a water distribution and integrated management system based on the Internet of Things (IoT) and data analytics (DA). In addition to preventing water waste, the suggested approach would assist in gathering consumption statistics for macro-level research and town planning

PurposeThe purpose of this research work is to design and apply LabVIEW in the area of traffic maintenance and flow, by introducing improvements in the smart city. The objective is to introduce the automated human–machine interface (HMI) – a computer-based graphical user interface (GUI) – for measuring the traffic flow and detecting faults in poles.Design/methodology/approachThis research paper is based on the use of LabVIEW for designing the HMI for a traffic system in a smart city. This includes considerable measures that are: smart flow of traffic, violation detection on the signal, fault measurement in the traffic pole, locking down of cars for emergency and measuring parameters inside the cars.FindingsIn this paper, the GUIs and the required circuitry for making improvements in the infrastructure of traffic systems have been designed and proposed, with their respective required hardware. Several measured conditions have been discussed in detail.Research limitations/implicationsPJRC Teensy 3.1 has been used because it contains enough general-purpose input–output (GPIO) pins required for monitoring parameters that are used for maintaining the necessary flow of traffic and monitor the proposed study case. A combination of sensors such as infrared, accelerometer, magnetic compass, temperature sensor, current sensors, ultrasonic sensor, fingerprint readers, etc. are used to create a monitoring environment for the application. Using Teensy and LabVIEW, the system costs less and is effective in terms of performance.Practical implicationsThe microprocessor board shields for placing actuators and sensors and for attaching the input/output (I/O) to the LED indicators and display have been designed. A circuitry for scaling voltage, i.e. making sensor readings to read limits, has been designed. A combination of certain sensors, at different signals, will lead to a secure and more durable control of traffic. The proposed applications with its hardware and software cost less, are effective and can be easily used for making the city’s traffic services smart. For alarm levels, the desired alarm level can be set from the front panel for certain conditions from the monitoring station. For this, virtual channels can be created for allowing the operator to set any random value for limits. If the sensor value crosses the alarm value, then the corresponding alarm displays an alert. The system works by using efficient decision-making techniques and stores the data along with the corresponding time of operation, for future decisions.Originality/valueThis study is an advanced research of its category because it combines the field of electrical engineering, computer science and traffic systems by using LabVIEW.

Smart cities are being developed worldwide with the use of technology to improve the quality of life of citizens and enhance their safety. Video surveillance is a key component of smart city infrastructure, as it involves the installation of cameras at strategic locations throughout the city for monitoring public spaces and providing real-time surveillance footage to law enforcement and other city representatives. Video surveillance systems have evolved rapidly in recent years, and are now integrated with advanced technologies like deep learning, blockchain, edge computing, and cloud computing. This study provides a comprehensive overview of video surveillance systems in smart cities, as well as the functions and challenges of those systems. The aim of this paper is to highlight the importance of video surveillance systems in smart cities and to provide insights into how they could be used to enhance safety, security, and the overall quality of life for citizens.

Abstract. Smart City is a new concept that uses Information and Communication Technology (ICT) to promote the smartification of urban construction, planning and services. Currently, a number of countries and cities have conducted studies on Smart City, but they mostly focused on the conceptual connotations analysis and applications in specific domains, lacking a common, shareable and integrated framework understanding, which led to significant barriers among individual Smart City projects. By analyzing the framework connotations and application domains of Smart City, this paper proposed a common, shareable and integrated conceptual framework for smart city. Then based on this framework, a unified portal platform that is suitable for multiple domains, including the government, citizen and business, as well as common, custom and other application modes, is further proposed. Finally, Smart Weifang was implemented based on this platform. The application outcomes indicate that this common and shareable platform can effectively eliminate the data and technological barriers between different smart city systems, while also avoiding redundant financial investments. The investigation of the proposed framework and platform is of key significance to the unified construction of Smart City and the intensification of the hardware environment, thus representing a true achievement in the transition from “information island” to “information sharing and interconnection” for urban informatization.

The article is devoted to the development of forecasting methods for the research on migratory processes. The authors pay attention to specific problems of migration in the Arctic regions of Eurasia. It is proposed to use a combination of analytical and simulation modeling to enhance the quality of prognoses for migration flows. Two parts of the ongoing research are described: technology of entropy-robust identification of the parameters of simulation models and a set of simulation models. The technology of entropy-robust assessment is based on the idea of re-use of formalized knowledge in the analysis of statistical characteristics of the parameters of simulation models. The technology allows to shorten the time and reduce the complexity of development of appropriate simulation models of migration. The complex of simulation models is developed on the basis of a combination of system dynamics, discrete-event and agent-based modeling. The integration of agent-based and analytical modeling to create simulation models of migration processes allows, on the one hand, to ensure the accuracy of the simulation according to the quality of the source data, and on the other, to analyze socioeconomic systems at the required level of abstraction. The results of computational experiments to identify trends in migratory processes in the Arctic regions are presented.

This chapter explores the use of edge accessibility computing and blockchain in smart cities. Edge accessibility computing provides seamless access to digital services and information, reducing latency and improving accessibility. This approach is particularly useful in resource-constrained environments. The chapter demonstrates how edge accessibility computing can optimize traffic management and healthcare delivery in smart city operations. Blockchain technology enhances security and efficiency in smart city systems, fostering trust, accountability, and data integrity. The chapter discusses the synergies between edge accessibility computing and blockchain, highlighting their combined application to address challenges in smart city initiatives. The chapter suggests that policymakers, urban planners, and technologists can use these innovative solutions to create smarter, more equitable, and sustainable cities.

Urbanization and digital transformation are rapidly reshaping cities across Morocco, giving rise to Smart Cities that leverage advanced technologies to enhance efficiency, sustainability, and urban life quality. However, this shift towards interconnected, technology-centric urban environments also presents significant cybersecurity challenges that necessitate careful analysis. This paper explores the cybersecurity issues confronting Smart Cities, with a specific focus on case studies from Moroccan cities. As Morocco embraces Smart City initiatives to address urban challenges and drive economic growth, these developments bring both promise and risk. The increased connectivity and technological integration within Smart Cities offer improved services but also expose cities to a wider range of cyber threats. The interconnectedness of devices and systems in Smart Cities broadens the potential for cyber-attacks, including data breaches and disruptions to critical infrastructure. This review delves into the cybersecurity challenges faced by Moroccan cities as they advance technologically. It identifies vulnerabilities in critical infrastructure such as energy grids, transportation systems, and healthcare networks highlighting the dangers posed by inadequate cybersecurity measures. Moreover, the study underscores the socio-economic impact of cyber threats in Smart Cities, stressing the importance of robust cybersecurity frameworks to safeguard citizen data and maintain urban operations. In conclusion, this research emphasizes the urgent need for comprehensive cybersecurity strategies tailored to the unique challenges of Moroccan Smart Cities. The insights presented aim to deepen understanding of the complex relationship between urbanization, technology, and cybersecurity, and to inform policy decisions, technological deployment, and collaborative efforts towards creating secure and resilient Smart Cities in Morocco.

A smart city is an urban agglomeration which capitalises on information technologies (IT) and artificial intelligence (AI) facilities to offer special services to its community and visitors. These range from more complex services such as energy production, road traffic management, civil security and territorial administration, to simpler services such as household waste management or free Internet in parks, libraries, shopping centres and other public places. To achieve this integration of management, an important step is to install sensors that are essential for collecting data. The collection of information to manage sensitive infrastructure via IT services comes with security risks, however. The impact of cyber security breach risks linked to these data collection activities and storage can be dramatic, depending on the type of service: power plants, water management systems, automated or driverless trains, vehicle traffic management systems, etc. These types of service, due to IT and AI evolution, are increasingly the victim of attacks by cyber criminals, especially the industrial control system (ICS)/supervisory control and data acquisition (SCADA) and smart grid networks. These networks are nowadays prime targets for professional hackers, cybercriminal organisations, or even competitors who want access to inside privileged information. To support interest in this type of attack for these networks, we can cite malicious programs such as Stuxnet, Dragonfly and BlackEnergy3, which damaged the Ukraine SCADA network with major consequences for energy production and distribution. Ukrainian energy private companies were victims of the attack, which resulted in total blackouts in at least eight regions of the country. Stuxnet has also been used to destroy a large part of the centrifuges fleet used by Iran for its uranium enrichment programme, etc. The rise of electric vehicle (EV) smart cities is based on smart grid infrastructure and IT — a combination that can lead to increased cyber security risks to the electricity network as well as for fast-charging stations. The purpose of this paper is to identify the most sensitive systems in smart cities, describe potential risks associated with these systems, and propose mitigation mechanisms to reduce associated cyber security risks.

Multiscale modeling in smart cities: A survey on applications, current trends, and challenges

Approximately 42% of the world's cocoa is produced in Côte d'Ivoire, although only 30% of it is processed there. A significant portion of the nation is dependent on the cocoa industry's economic advantages and supply network. In this study, the authors study a simulation model to evaluate the efficiency of the cocoa supply chain's logistics in Côte d'Ivoire. By highlighting inefficiencies, bottlenecks, and barriers that impede the efficiency and performance of the cocoa supply chain, the simulation model sheds light on the possibility of logistical improvements in the supply chain. According to simulation results, removing checkpoints off the roadways would enhance production by 30%. Investments in secondary and tertiary road improvements will boost productivity by 9% and value by 1%. In this study, further significant findings are provided together with recommendations for improvement in order to improve the logistics of the cocoa supply chain, boost the industry's profitability, and ultimately enhance the quality of life and welfare of the nation's farmers.

This paper explores the applicability of the agent-based (AB) and system dynamics (SD) methods to model a case study of the management of water field services. Water borehole sites are distributed over an area and serve the water needs of a population. The equipment at all borehole sites is managed by a single water utility that has adopted specific repair, replacement, and maintenance rules and policies. The water utility employs several service crews initially stationed at a single central location. The crews respond to specific operation and maintenance requests. Two software modeling tools (AnyLogic and STELLA) are used to explore the benefits and limitations of the AB and SD methods to simulate the dynamic being considered. The strength of the AB method resides in its ability to capture in a disaggregated way the mobility of the individual service crews and the performance of the equipment (working, repaired, replaced, or maintained) at each borehole site. The SD method cannot capture the service crew dynamics explicitly and can only model the average state of the equipment at the borehole sites. Their differences aside, both methods offer policymakers the opportunity to make strategic, tactical, and logistical decisions supported by integrated computational models.