Smart Nanomaterials in Medicine: Integrating Ai and Iot for Real-Time Health Monitoring and Therapeutics

Abstract

Background: The integration of smart nanomaterials with artificial intelligence (AI) and the Internet of Things (IoT) represents a transformative opportunity in healthcare, offering the potential to significantly enhance real-time health monitoring and therapeutic interventions. These emerging technologies promise more precise diagnostics, personalized treatment, and improved patient outcomes. Objective: The purpose of this research is to explore the adoption of innovative nanomaterials, artificial intelligence(AI), and the Internet of Things in healthcare — perceptions, challenges, and possibilities. This paper looks at how these technologies help improve the efficiency of real-time health tracking and therapy and the possible hurdles that will prevent these instruments from working effectively. Methods: A cross-sectional quantitative survey involved 250 participants including healthcare professionals, researchers, and technologists. A formalized questionnaire containing both the Likert scale and closed questions was used to gather the data on awareness of the technologies, perceived efficiency, and identified difficulties. Descriptive statistics, correlation analysis, and reliability tests were conducted in data analysis. Results: According to the results obtained, there was a fair level of awareness of AI and IoT in healthcare, highlighting that data privacy was the most significant challenge (35%), followed by cost at 30%. The respondents are aware of the benefits in which the utilization of nanomaterials can be practical, specifically in monitoring health, since the results are not generally distributed according to the Shapiro-Wilk test. In addition, while finding a Cronbach's Alpha value of (0.13), it can be understood that there is poor internal consistency with the survey questions measured using the Likert scale format and poor survey design. Conclusion: Intelligent materials, AI, and IoT have a wide range of applications in healthcare but have not been fully implemented because of privacy and cost issues. The only way to reduce this will be by gaining further awareness of the problems addressed here through education and improved data protection mechanisms. Therefore, there is a need to conduct more research and refine the methodologies that can successfully explain the attributes that characterize the adoption of the technologies into medical practice.

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