ABSTRACT
According to United Nations predictions by 2050, the world’s population will reach 9.7 billion, with 70% living in urban areas. Resources like energy, water supply, drainage, and traffic management, as well as associated government services like sanitation, sewerage, and traffic management must be provided to all habitats at the same time without causing environmental degradation, which is challenging. AI-based IoT is the solution to getting rid of these problems. The Internet of Things has become increasingly popular in the last couple of decades due to advancements in hardware and software technology. Hardware advancement has seen a huge increase in functionality with a size reduction. The number of Internet of Things (IoT) devices worldwide is expected to triple from 8.74 billion in 2020 to more than 25.4 billion IoT devices by 2030.
With these developments in hardware and wireless technologies, small objects or things are connected to the internet to form IoT networks. Artificial intelligence (AI) empowers IoT networks by making them take calculative decisions without human involvement. With AI-enabled IoT, one can take advantage of the benefits and convenience of advancements in technology to make everyday life more convenient and secure. With smart technology, smart cities can provide quality and performance services like traffic management and police surveillance, smart grid, smart waste management, and smart governance at reduced costs and high speeds. There are many IoT applications for smart cities that utilize both machine learning and deep learning. This chapter describes those applications. Smart city applications today face many challenges, which are addressed as well.
