IoT Based Smart Systems using Artificial Intelligence and Machine Learning: Accessible and Intelligent Solutions

The Internet of Things (IoT) has grown in importance in both the technological and social spheres as consumers want smarter homes, more efficient businesses, and more efficient healthcare systems. The social setting is very important for this. Communication networks provide uninterrupted internet connectivity for both fixed and mobile devices like PCs and smartphones. Customers may now keep up their level of engagement while interacting with one or more apps at any time and from any location, thanks to developments in information and communication technologies. Many kinds of smart devices might potentially coordinate their responses to events, sending out alerts or keeping records of the system’s condition in line with a predetermined policy. Constant progress toward intelligent solutions is improving many facets of modern life, including manufacturing, transportation, electronic healthcare, electronic education, and many more. Machine-to-machine (M2M) communication in the IoT is autonomous and dynamic. Diverse approaches are being developed to address the challenges posed by disparate data sources, fluctuating signal quality, and overwhelming quantities of data. From the perspectives of intelligent system technologies, security, vulnerabilities, and the potential role that intelligent solutions based on Machine Learning (ML) and Artificial Intelligence (AI) may play, this article examines the IoT. Concerns about privacy and safety have arisen as a major obstacle to the widespread adoption of the Internet of Things (IoT). We propose that the Standard Security Framework (SSF) be made mandatory for all distributed networks to ensure that hardware and software modules may communicate with one another regardless of their respective platforms. In addition, the effectiveness and security of new innovations in using fog and edge computing in conjunction with cloud applications have been studied.