ABSTRACT
In order to allow smart cities to thrive with a bright future, the Internet of Things (IoT) aspires to link billions of intelligent things to the Internet. These objects will generate a lot of data and send it to the cloud for processing to take the right actions. This processing will focus on knowledge discovery. Modern technology’s development has made it possible to create smart cities with a range of automated services. This results in the extensive installation of sophisticated sensing smart infrastructure that is networked into an automated smart city system. Additionally, the full environment of sensing components is frequently networked via the cloud or a centralized system. The deployment of edge computing technologies could have a significant concussion on the smart environment since IoT devices are notoriously resource-constrained and extremely data-intensive. Edge computing can be an optimized approach in developing a smart infrastructure with fewer bottlenecks. Smart cities deal with varied complexity, including wired, wireless, mobile, sensor, optical, and other associated network technologies. There are many obstacles that must be overcome for the convergence of edge computing approaches for smart cities, including hardware constraints on the device side, minor data losses, security flaws, etc. Edge computing for smart city applications effectively addresses these difficulties. The fog (edge) computing model addresses the issue by moving data analytics-based knowledge discovery processes to the edges. However, the computing power of edge devices is constrained. Due to their strengths and weaknesses, the cloud and fog computing paradigms cannot solve these problems alone. Both paradigms must collaborate to build sustainable smart city IoT infrastructure.
The advantages of transparency, decentralization, security, and immutability of blockchain technology are well known. By implementing blockchain technology, smart cities can execute democratic services and applications in a safe, transparent, dependable way while also significantly improving data integrity and openness in city maintenance. In the context smart environment, humongous data is generated to facilitate the automation. Big data analytics heavily relies on artificial intelligence, which also provides reliable data analysis in real time. This chapter presents an important study on various trending technologies, greatly assists IoT system to implement the technical sustainability in smart city applications.
