AI/ML-Based Predictive Maintenance for IoT-Enabled Healthcare Devices in Regulated Environments
DOI:
https://doi.org/10.63397/ISCSITR-IJSRAIML_06_02_004Keywords:
Healthcare, IoT, AI, Predictive Maintenance, MLAbstract
In this paper, we study the application of AI/ML based predictive maintenance in IoT devices in healthcare sector in regulated environments. They discuss the operational advantages, the impact to model effectiveness, and regulatory issues using both literature and data analysis. Results show that AI-based systems can make the substantial reduction of downtime and cost while keeping compliance and safety of patients, and can have its scalability potential in modern healthcare systems.
References
Taimoor, N., & Rehman, S. (2021). Reliable and resilient AI and IoT-based personalised healthcare services: A survey. IEEE Access, 10, 535-563. 10.1109/ACCESS.2021.3137364
Bajpai, A., Tolani, M., & Balodi, A. (2023). Smart Healthcare System Using IoT, Cloud and AI/ML. Journal of Engineering Science & Technology Review, 16(6). http://www.jestr.org/downloads/Volume16Issue6/fulltext141662023.pdf
Tuan, D. A., & Thanh, D. T. (2024). Harnessing AI and IoT for the Future of Healthcare: A Comprehensive Review on Chronic Disease Management and Pandemic Response. https://doi.org/10.20944/preprints202409.2451.v1
Lawal, O. O., Nawari, N. O., & Lawal, O. (2025). AI-Enabled Cognitive Predictive Maintenance of Urban Assets Using City Information Modeling—Systematic Review. Buildings, 15(5), 690. https://doi.org/10.3390/buildings15050690
Rajagopal, D., & Subramanian, P. K. T. (2025). AI augmented edge and fog computing for Internet of Health Things (IoHT). PeerJ Computer Science, 11, e2431. https://doi.org/10.7717/peerj-cs.2431
Kodumuru, R., Sarkar, S., Parepally, V., & Chandarana, J. (2025). Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy. Pharmaceutics, 17(3), 290. 10.3390/pharmaceutics17030290
Diameh, J. T., Oluwatobi, B. T., Daniels, C., Ekaette, O., Sunday, N., Azumah, C., & Mariama, Q. (2025). INTEGRATING AI-DRIVEN PREDICTIVE ANALYTICS IN PROJECT RISK MANAGEMENT TO OPTIMIZE DECISION-MAKING AND PERFORMANCE EFFICIENCY. https://www.researchgate.net/profile/Jacob-Diameh/publication/390597476_INTEGRATING_AI-DRIVEN_PREDICTIVE_ANALYTICS_IN_PROJECT_RISK_MANAGEMENT_TO_OPTIMIZE_DECISION-MAKING_AND_PERFORMANCE_EFFICIENCY/links/67f592b695231d5ba5bce20c/INTEGRATING-AI-DRIVEN-PREDICTIVE-ANALYTICS-IN-PROJECT-RISK-MANAGEMENT-TO-OPTIMIZE-DECISION-MAKING-AND-PERFORMANCE-EFFICIENCY.pdf
Kumar, D., Sood, S. K., & Rawat, K. S. (2023). IoT-enabled technologies for controlling COVID-19 Spread: A scientometric analysis using CiteSpace. Internet of Things, 23, 100863. https://doi.org/10.1016/j.iot.2023.100863
Sharma, A., Sharma, R. K., Nanda, S., & Misra, A. (2022). Emerging real time analytics based health start-ups: opportunities during covid-19. Journal of Medical Pharmaceutical and Allied Sciences, 11(4), 5017-5025. https://jmpas.com/admin/assets/article_issue/1661625883JMPAS_JULY_-_AUGUST_2022.pdf
Parween, G., Al-Anbuky, A., Mawston, G., & Lowe, A. (2025). Internet of Things-Based Human Movement Monitoring System: Prospect for Conceptual Digital Twin. Journal of Engineering and Science in Medical Diagnostics and Therapy, 8(2). https://doi.org/10.1115/1.4067947
