Internet of Things for Smart Cities

Urbanization has increased drastically over the past few years. Currently, more than half of the world’s population is concentrated in urban areas. Moreover, the urban population is expected to reach approximately 70% of the total by 2050. In this tremendous growth, there will be 27 mega cities with more than 10 million people. This congestion of inhabitants poses challenges for highly populated cities in terms of governance, economic growth, environmental sustainability, quality of life, transportation, power, water usage, etc. Consequently, smart solutions are required to address these challenges. Internet of Things (IoT) offers smart solutions for future cities to address these challenges with minimum human intervention. In this chapter, the objective is to provide an insight of different aspects of smart cities and common IoT solutions for future cities.

The Internet of Things (IoT) has come to be the front-runner in changing how devices communicate with each other and with the physical environment. The seamless interconnection of devices to the Internet, being sensors of all types ranging from in situ measurement devices, sensors on smartphones up to hyper-spectral cameras mounted on drones, offers an enormous potential for expanding the functionalities of these devices as well as providing a better control over the situations. In this chapter, we provide an overview of the broad classification of communication protocols for IoT networks. Next, we present an analysis of the technicalities as well as specific advantages and limitations of each type. We also discuss recent protocols for IoT networks. The chapter ends with the comparative analysis of two very different use cases of IoT and the communication technologies used in each of them.

The number of Internet of Things (IoT) devices continues to grow with the invention of sophisticated applications in smart cities. It is forecasted that there will be 50 billion IoT devices by 2025. These large numbers of IoT devices and sensors are generating a huge amount of data in the various different formats such as plain messages, images, audio, and video. It is important to analyze this large amount of data. However, limited capabilities of IoT devices (such as low-power and computational capability) require efficient and robust methods to deal with the big data analytics. Numerous statistical techniques such as regression analysis, support vector machines, ensembles, decision trees, analysis of variance, correlation and autocorrelation, etc. led to massive amounts of data being processed in novel ways. It is important to reduce the number of variables in data before processing it. Dimension reduction is considered as an effective method to reduce the number of variables in data generated by IoT devices. In this chapter, we first present related work on dimension reduction in IoT systems. Then, we provide a detailed discussion of solutions for dimension reduction with several examples. Finally, we present conclusions and highlight open research areas for data reduction in IoT systems.

Climate change made the detrimental impact on the environment. This climate change has urged people around the globe to adopt technologies that utilize clean and sustainable energy resources. Amid these technologies, electric vehicles (EVs) emerged as a transportation technology that is environmentally friendly, unlike traditional fuel-based vehicles that are prevailing in the automotive industry nowadays. However, the large-scale implementation of EVs can impose extra burdens on electric grids; therefore, smart scheduling is essential to optimize the charging process in a smart city. To this end, information exchange between EVs and the charging stations regarding energy’s availability, demand, and the cost is necessary to achieve efficient charge scheduling. The Internet of Vehicles (IoV) paradigm, which is extended from the Internet of Things (IoT), can play a significant role in this process by providing holistic data exchange between charging infrastructure and EVs. This chapter presents an approach for EV charge scheduling in smart distribution systems by considering the cost and speed of charging (i.e., slow, normal, or fast charging) at the charging stations. The scheduling problem aims to maximize the total profit by minimizing the charging cost.

The Internet of Things (IoT) offers connectivity of billions of low-power devices and sensors through the Internet which generates a large amount of data. Recently, blockchain technology is investigated extensively for security and privacy in IoT. In this chapter, we provide an overview of the use of blockchain technology for IoT. First, we analyzed the recent literature for the better understanding of research direction in blockchain for IoT systems. We also present challenges associated with the deployment of IoT and blockchain for the IoT systems. We then discuss two case studies on smart homes and food supply chain traceability to show the effectiveness of blockchain technology for IoT. Finally, we outline the future research directions in this area.