Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2024 Dec 13:7:1442254.
doi: 10.3389/frai.2024.1442254. eCollection 2024.

Assuring assistance to healthcare and medicine: Internet of Things, Artificial Intelligence, and Artificial Intelligence of Things

Affiliations
Review

Assuring assistance to healthcare and medicine: Internet of Things, Artificial Intelligence, and Artificial Intelligence of Things

Poshan Belbase et al. Front Artif Intell. .

Abstract

Introduction: The convergence of healthcare with the Internet of Things (IoT) and Artificial Intelligence (AI) is reshaping medical practice with promising enhanced data-driven insights, automated decision-making, and remote patient monitoring. It has the transformative potential of these technologies to revolutionize diagnosis, treatment, and patient care.

Purpose: This study aims to explore the integration of IoT and AI in healthcare, outlining their applications, benefits, challenges, and potential risks. By synthesizing existing literature, this study aims to provide insights into the current landscape of AI, IoT, and AIoT in healthcare, identify areas for future research and development, and establish a framework for the effective use of AI in health.

Method: A comprehensive literature review included indexed databases such as PubMed/Medline, Scopus, and Google Scholar. Key search terms related to IoT, AI, healthcare, and medicine were employed to identify relevant studies. Papers were screened based on their relevance to the specified themes, and eventually, a selected number of papers were methodically chosen for this review.

Results: The integration of IoT and AI in healthcare offers significant advancements, including remote patient monitoring, personalized medicine, and operational efficiency. Wearable sensors, cloud-based data storage, and AI-driven algorithms enable real-time data collection, disease diagnosis, and treatment planning. However, challenges such as data privacy, algorithmic bias, and regulatory compliance must be addressed to ensure responsible deployment of these technologies.

Conclusion: Integrating IoT and AI in healthcare holds immense promise for improving patient outcomes and optimizing healthcare delivery. Despite challenges such as data privacy concerns and algorithmic biases, the transformative potential of these technologies cannot be overstated. Clear governance frameworks, transparent AI decision-making processes, and ethical considerations are essential to mitigate risks and harness the full benefits of IoT and AI in healthcare.

Keywords: AI; AIoT; IOT in medicine; LLMS; deep learning and NLP; machine learning.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart depicting the selection process of articles for review.
Figure 2
Figure 2
AIoT in health care and medicine.
Figure 3
Figure 3
Use of AIoT in healthcare.

Similar articles

Cited by

References

    1. Abràmoff M. D., Tarver M. E., Loyo-Berrios N., Trujillo S., Char D., Obermeyer Z., et al. . (2023). Considerations for addressing bias in artificial intelligence for health equity. NPJ Digit. Med. 6:170. doi: 10.1038/s41746-023-00913-9, PMID: - DOI - PMC - PubMed
    1. Ahmed Z., Mohamed K., Zeeshan S., Dong X. (2020). Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database 2020:2020. doi: 10.1093/database/baaa010 - DOI - PMC - PubMed
    1. Al-kfairy M., Mustafa D., Kshetri N., Insiew M., Alfandi O. (2024). Ethical challenges and solutions of generative AI: An interdisciplinary perspective. Informatics. 11:58. doi: 10.3390/informatics11030058 - DOI
    1. Anurag Moosavi SR, Rahmani AM, Westerlund T, Yang G, Liljeberg P, et al. . Pervasive health monitoring based on internet of things: two case studies. Proceedings of the 2014 4th International Conference on Wireless Mobile Communication and Healthcare - "Transforming Healthcare through Innovations in Mobile and Wireless Technologies", Mobihealth 2014. (2015). 275–278.
    1. Bajwa J., Munir U., Nori A., Williams B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future Health. J. 8, e188–e194. doi: 10.7861/fhj.2021-0095, PMID: - DOI - PMC - PubMed

LinkOut - more resources