Integrating AI, Machine Learning, and IoT Technologies for Enhanced Communication and Medical Applications

Abstract

The growth of the Internet of Things has ushered in a wealth of information and a variety of uses, bringing the vision of a smarter world into reality. With the integration of cutting-edge technologies like cloud computing, interconnected devices, and intelligent multiple-sensor media systems, the concept of “smart healthcare” has garnered significant attention from various stakeholders, including medical specialists, businesspeople, governmental agencies, and educational establishments. This study aims to examine the Privacy and security issues posed by the AIIoT and provide recommendations for solutions. Qualitative study techniques were employed to gather pertinent information from numerous additional sources. The findings suggest that the fusion of artificial intelligence with the IoT has led to an abundance of new web-connected sensors and gadgets, raising myriad security and privacy concerns for consumers. Therefore, it is imperative for AI-driven IoT systems to adhere to well-defined architectural standards encompassing platforms and information patterns to guarantee consumers' improved safety and confidentiality. In simpler terms, the proliferation of IoT, combined with AI, has introduced numerous new gadgets and sensors connected to the web, raising serious concerns about user security and privacy. To address these issues, AI-driven IoT systems must follow clear architectural standards prioritizing user privacy and security.