Enterprise Systems for Networked Smart Cities

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%.

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.

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

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.

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.

This study evaluates the critical success factors for smart mobility systems (SM) and assesses its current application level for smart city development using Nigerian as a case study. This study is based on a mixed-method approach (Delphi and quantitative survey). The study revealed seven critical success factors of smart mobility. Furthermore, the findings of this study revealed that factors like sustainable, innovative and safe transportation system, availability of ICT infrastructure, local accessibility of transportation infrastructure, availability of transportation infrastructure (bike, cycling, pedestrian mobility facilities), are the most significant smart mobility success factors. Also, a good consensus was achieved for all the success factors. The Mann Whitney test from the final Delphi result revealed no significant difference in the responses of the two groups of experts. Assessing the level of application of the smart mobility success factors revealed an abysmal application level according to the expert's opinion. This study contributes to the body of knowledge as it reveals the SM success factors that should be considered to achieve a sustainable smart mobility system in a city. The findings of this study will assist cities worldwide in developing smart mobility systems and further improve their competitive advantage. The study concludes that the evaluated success factors are significant in smart mobility systems development and application, based on expert's opinion. However, its level of adoption and application is still low in Nigeria. Therefore, it is recommended that the government and policy decision-makers in urban transportation infrastructure development should use the results from this study, as a scorecard to know lagging areas and factors that need significant improvement and application to achieve a smart mobility system.

Technologies are constantly evolving and finding applications in both business and government organizations for various purposes such as improving operational efficiency, increasing customer satisfaction, and reducing the cost of transactions. Technology adoption is a well-researched phenomenon in the academic world. Based on the current state of e-governance in Saudi cities and the potential of Artificial Intelligence (AI), Internet of Things and Blockchain in e-governance, this research study aims to study factors influencing the adoption intention of AI and Blockchain technologies in citizen services delivery within a smart city in Saudi. This article explores AI, IoT and Blockchain technologies adoption intention in the context of smart cities within a developing country like Saudi. Finally, the study provides a set of practical recommendations for smart city officials while planning to launch service applications using AI and Blockchain technologies. More specifically, the study emphasizes the importance of ethics, data privacy and security, and transparency in building trust between smart city systems.

Smart Cities, urban environments that integrate digital technologies to enhance sustainability, accessibility, and quality of life, are expanding globally. While these initiatives may support population health, their mental health impacts remain understudied and inconsistently reported. This thematic synthesis review integrates diverse forms of evidence to examine how Smart City features influence mental health outcomes and explores contextual factors and underlying mechanisms shaping these effects. Following PRISMA guidelines for qualitative evidence syntheses, a systematic search of Web of Science identified 36 peer-reviewed studies published between 2009 and 2024 that addressed Smart City components in relation to mental health outcomes in urban populations. Studies were thematically synthesized. Three key domains emerged: (1) Smart City features relate to mental health through access to green infrastructure, digital technologies, and transportation systems; (2) contextual vulnerabilities including digital exclusion, gender, age, and socioeconomic status moderate these relationships; and (3) mechanisms include environmental exposure, surveillance anxiety, sensory design, and cultural or relational dynamics embedded in Smart City systems. Findings suggest that Smart Cities can either promote or undermine mental health depending on how technologies are implemented, accessed, and experienced. To ensure Smart City development supports psychological wellbeing, future research should prioritize interdisciplinary collaboration, equity-informed planning, and integration of mental health expertise from the outset.

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.

Artificial Intelligence (AI) is one of the disruptive technologies that is shaping the future. It has growing applications for data-driven decisions in major smart city solutions, including transportation, education, healthcare, public governance, and power systems. At the same time, it is gaining popularity in protecting critical cyber infrastructure from cyber threats, attacks, damages, or unauthorized access. However, one of the significant issues of those traditional AI technologies (e.g., deep learning) is that the rapid progress in complexity and sophistication propelled and turned out to be uninterpretable black boxes. On many occasions, it is very challenging to understand the decision and bias to control and trust systems’ unexpected or seemingly unpredictable outputs. It is acknowledged that the loss of control over interpretability of decision-making becomes a critical issue for many data-driven automated applications. But how may it affect the system’s security and trustworthiness? This chapter conducts a comprehensive study of machine learning applications in cybersecurity to indicate the need for explainability to address this question. While doing that, this chapter first discusses the black-box problems of AI technologies for Cybersecurity applications in smart city-based solutions. Later, considering the new technological paradigm, Explainable Artificial Intelligence (XAI), this chapter discusses the transition from black-box to white-box. This chapter also discusses the transition requirements concerning the interpretability, transparency, understandability, and Explainability of AI-based technologies in applying different autonomous systems in smart cities. Finally, it has presented some commercial XAI platforms that offer explainability over traditional AI technologies before presenting future challenges and opportunities.KeywordsExplainable AIMachine learningDeep learningCyber securityPrivacyTransparency

Urban air mobility (UAM) and drones can significantly improve traffic movement in saturated cities because the skies above them are not frequently used; furthermore, they do not require large-scale infrastructure, like roads and subways do. Thus, UAM vehicles and drones present themselves as new means of transportation in cities. They can be rapidly deployed if their operational safety is secured. However, to date, no precise numerical study has been conducted on the safety of UAM vehicles and drones. In this study, the accident rates of UAM vehicles and drones are predicted based on the accident rates of conventional aircraft. Additionally, control measures for UAM vehicles and drones are presented at a basic level. The results can be summarized as follows: First, in terms of accident rates, for a projected total UAM vehicle flight distance of 650 km and 177,147 h of flight in Seoul in 2035, 0.000221 crashes, 0.45 takeoff/landing accidents, and 0.0011446 deaths are expected. Second, if drones handle 0.5% of the logistics in Seoul in 2035, 38.35 crashes and 7.51 takeoff/landing accidents are projected per year. However, these numbers are plausible only if the infrastructure required for UAM vehicle and drone flights, such as taxiways and flight paths, is built similarly to that for large aircraft. Additionally, UAM vehicles and drones, as with large aircraft, can cause serious damage to facilities and human lives on the ground in the event of a crash. Therefore, thorough response mechanisms for crashes are required even if the crash probability is extremely low. Finally, integration with smart city systems is suggested to monitor UAM vehicle and drone flights and the safety of urban residents. The transportation services of smart cities include emergency dispatch and disaster notification services, which help in immediately notifying the degree of risk to potentially affected urban residents and facilities in the event of a UAM vehicle/drone crash or an emergency. The transportation services of smart cities are also typically equipped with accident handling processes. Therefore, integrating UAM and drone systems into smart city systems is highly recommended.

Subject. The research investigates key processes of urban life and its maintenance, including food supply, infrastructure, fire security, quality and accessibility of medical services, etc. The article also discusses the creation of a system supporting the Smart City decision-making process. Objectives. The research develops methods and tools to manage the Smart City system through system dynamics and agent-based modeling. Methods. Using simulation modeling, namely system dynamics and agent-based modeling (supported via Powersim and AnyLogic), we evaluate how multiple guiding parameters influence crucial characteristics of the Smart City system. Results. We devised an approach to designing the Smart City system through methods of system dynamics and agent-based modeling (supported via Powersim and AnyLogic) intended to streamline the decision making process for reasonable urban planning. Conclusions and Relevance. We propose the consolidated architecture of the Smart City decision-making system integrating the simulation models, data storage and city monitoring subsystem. The article describes the cases of simulation models implemented via Powersim and AnyLogic to support rational urban planning. The simulation models will significantly improve the quality of urban environment, satisfy the demand for food products, provide access to healthcare services and ensure effective rescue actions in case of emergency.