Internet of Things Application for Intelligent Cities

The rapid growth of the world's population is placing a huge strain on the existing infrastructures. As a quest for accommodating this growth, interest is turned to the internet of things (IoT). In fact, the IoT is significantly improving today's quality of life by innovating the provided services and enhancing communication and interaction. Furthermore, it has also empowered real-time decision making by introducing dynamic services for innovative traffic handling, energy-efficient infrastructure saving, and public safety ensuring. However, IoT applications for smart cities is still a major issue as it lacks assuring privacy and security within provided services. In this chapter, the authors pinpoint IoT's security risk assessment challenges and examine its critical influence on smart cities. Additionally, they highlight the key aspects characterizing a smart city which also represent the critical assets requiring security risk assessment. Moreover, they discuss the resulting issues and their related countermeasures.

Intelligent Cities

This chapter focuses on a systematic and integrated approach to managing cities using multidisciplinary and technology-based approach and drawing on integrated knowledge from different fields. The chapter aims to discuss and analyse issues in an organic and holistic approach. It explores theory and combines praxis, applications, and futuristic conjectures. Emphasis is placed on issues of ethics, human rights, environmental friendliness, sustainability, and compliance with the 17 UN Sustainable Development Goals (SDGs). While the chapter has considerable input from existing scholarship, it adopts a narrative that is innovative and creative and engages with novel ideas and propositions for future progress. It also charts the breakthrough in transportation, commerce, medicine, education, the world of work, and contemporary health, with particular emphasis on issues relating to safety, confidentiality, privacy, facial recognition, city policing, crime detection, monitoring and evaluation, forecasting, and future of AI.

Transforming Urban Slums

Cities in developing countries are increasingly under stress through urbanization, which leads to the expansion of slum areas or informal settlements due to demand for low-cost housing. This chapter presents the social, environmental, and economic realities facing slum dwellers and discusses their redevelopment into intelligent cities. The concept of ‘function accompanying intelligent' is introduced for the transformation of slums to functional intelligent cities. In this context, a city is intelligent if it serves both the functional and social needs of its entire population. The chapter overviews an approach to integrated data collection, data analytics, and user access to information. Geospatial analysis of demographic, economic, social, and environmental data is introduced to help delineate slums, and to monitor the outcomes of urban planning initiatives and the progress of social wellbeing. The city of Accra in Ghana is discussed as a potential slum city to functional intelligent city transformation.

A Smart City for the Blind

In this chapter, the authors present the German city of Marburg as an alternative model for the conception of a smart city. Marburg's historical relation with its visually impaired citizens has shaped not only its infrastructure but also its human framework. Generally, smart cities are equated with world-class major metropolitan areas, with international airports, use of high band internet, internet of things, and other IT infrastructures. However, Marburg might be considered a smart city according to other criteria. This case study articulates the uniqueness of what Marburg has been able to achieve using a diverse approach of cultural acceptance of the blind, becoming a world reference for other small cities. The authors suggest that Marburg can serve as a model for other cities. This hypothesis was reached through critical investigations into concepts of smartness and disability, intersected with the insights obtained in a focus group interview.

Developing Trends in Power and Networking Technologies for Intelligent Cities

The introduction of Industry 4.0 has increased the focus on a number of technologies. These technologies also help realize the vision for intelligent cities. Furthermore, there are already discussions of Industry 5.0. One emerging aspect of Industry 5.0 is human-robot co-working. With the help of artificial intelligence, the internet of things paradigm, Industry 4.0, and Industry 5.0 visions, there will be two predominant types of systems interfacing with people in intelligent cities. These are robotic and ambient intelligence systems. The increasing deployment of these will help make cities even smarter. However, we need to see advancements in a number of relevant key technologies, including power and networking technologies. In this chapter, first, the authors briefly discuss Industry 4.0, Industry 5.0, and intelligent cities paradigm, as well as robotic and ambient intelligence systems. Then, they focus on developing trends in power and networking technologies.

Air Pollution Monitoring in Intelligent Cities Using Weighted Association Rule Mining

Through the use of internet of things-based sensors in air quality monitoring stations, concentration of different pollutants and meteorological parameters can be regularly measured. In case of unusual conditions (e.g., increased levels of dangerous pollutants), a smart assessment system can produce warning so that appropriate air quality management process can be initiated. In this context, the objective of this study is to discover relationships and patterns among air pollution features and characteristics. In this case, determination of frequently observed association rules can trigger an appropriate background smart environment system when a critical situation is detected. In the experimental studies in the current project, traditional association rule mining and weighted association rule mining methods have been employed using real-world datasets collected from 21 monitoring stations in Turkey. In consequence, useful and outstanding association rules exceeding the user-defined support and confidence levels were obtained that can form basis for further research.

Building Intelligent Cities

A city may be regarded as an intelligent city when its services to citizens are connected and it is able to obtain data from every aspect of its technology infrastructure to leverage it in real time for resource allocation, monitoring, management, and decision making. Cities around the globe are ambitiously leveraging the latest technologies to transform their infrastructures to better provision and manage the e-services. Although they are setting goals for focusing on the appropriate financing, long-term planning, developing technology stack, and advancing data management, governments need to further encompass all relevant guidelines towards right technology frameworks before commencing their intelligent city projects. This chapter provides a comprehensive introduction to intelligent cities, also known as smart cities, and the associated requirements. It also articulates the evolution of a typical city to a truly integrated, responsive, open, and connected intelligent city and the required underlying technologies.

Connected Vehicles

An intelligent city, also known as smart city or cognitive city, is a new vision for urban development to integrate the various sectors and functions of the society through the use of internet of things and sensor-based technologies. The main objective is to seamlessly integrate and efficiently manage a city's resources such as transportation, healthcare, commerce, manufacturing, education, utilities, law enforcement, as well as city's various e-government information systems. The aim is to improve the quality of life of citizens and efficiency of city's services and processes, through the use of latest distributed technologies. In this chapter, the authors discuss the connected vehicles vision, as a core element of the internet of vehicles paradigm, as part of the intelligent transportation system (ITS). In doing so, they discuss the underlying concepts, technologies, types of vehicular connectivity, and mobile and vehicular ad hoc networks (i.e., MANET and VANET).

Next Generation of Intelligent Cities

Over the past decade, intelligent cities have undergone rapid transformation. The definition of an intelligent city may vary based on the context and the purpose served. However, the next generation of intelligent cities will have unique characteristics that will set them apart from the existing intelligent cities. They will be more people-centered, and they will be formed through the fusion of technology, government, organizations, and people. This chapter explores four intelligent cities in Europe that are setting examples for innovation, ingenuity, technology, public policy making, and sustainable development: London, Amsterdam, Vienna, and Stockholm. With growing emphasis on people involvement in decision making, the intelligent city ecosystem is continuously evolving. However, technology continues to play a prominent role in shaping the intelligent city paradigm. In this contribution, the authors also examine different emerging technologies such as quantum computing, autonomous vehicles, AI, ML, etc. that could potentially impact the next generation of such cities.

Hybrid Intrusion Detection System for Smart Home Applications

Smart homes, which incorporate IoT technologies to provide home security, efficient environmental services, conveniences, and improved living standards, are becoming the centre of smart urban developments. With the increased inter-connectivity of smart objects and sensors, there is now, also, an increased level of cyber threats, which can compromise privacy and security. These threats either modify packets of information or inject modified packets into the networks. This chapter examines current intrusion detection systems (IDSs) and presents a unique solution to overcome intrusion detection challenges. It discusses the implementation of smart home IDS (SHIDS), using a machine learning based signature and anomaly intrusion detection scheme to detect network intrusions in the smart home. Suggested mechanism is based on naïve Bayes technique to improve the detection performance. The performance of SHIDS has been tested with network intrusions resulting from DoS, probe, remote-to-local (R2L), and user-to-root (U2R) attacks.