Towards a Scalable and Autonomous IoT-Based Healthcare System: Leveraging AI and ML for Predictive Health Analytics

For this paper, a critical issue of developing IoTbased cost-effective auto sustainable healthcare system can be discussed. They also employ artificial intelligence (AI) and (machine learning) ML for health trend forecast. The main findings indicate that the proposed system significantly enhances the productiveness using superior AI techniques with more than 30 % improvement in the anticipation of potential health concerns than previous methods. This research also confirms that employing the range of data sources does not only enhance the algorithm training, but also enhances the potential for health forecasts, underlining the importance of cooperation between different fields of healthcare data analysis. The significance of such findings lies in their capacity to modify patient care by promoting timely actions and reducing health costs by the appropriate application of knowledge and management. Furthermore, the implications of this research show that other research Self-sufficient IoT healthcare systems can provide health care in support of PS Medicine, proper resource management for better health care consequences all over the world resulting into improved and sensitive health care framework system. Thus, positioning modern technology against actual experiences in health care, this body of work creates the condition for subsequent research in the health prognosis analysis putting the ways of healthcare provision in the digital environment.