Abstract

The combination of Internet of Things (IoT) with artificial intelligence (AI) offers a potential way to solve real-time IoT application problems. AI improves large data processing by providing unmatched speed and accuracy. Yet there are significant obstacles to overcome in order to advance large data analysis with AI, including those related to training data, privacy, data security, and centralised architecture. Smart cities refer to metropolitan regions that use diverse technologies, sensors, and actuators to gather and analyse data, resulting in significant insights and amenities for inhabitants. In order to ensure the best possible use of resources, information technology plays a crucial role in managing the social, commercial, and physical infrastructures of smart cities. Smart homes, smart cars, smart industries, and smart transportation are just a few examples of IoT devices found in smart cities that may interact and use smart solutions to efficiently and successfully optimise several domains. Using AI to improve healthcare services in smart cities while putting sustainability first means using AI to support sustainable healthcare. By integrating healthcare systems, this integration seeks to improve inhabitants’ well-being while reducing its negative effects on the environment. IoT has major obstacles such data security, centralization, data analytics, connectivity, and hardware constraints despite its many benefits.