Limitations in IoT and Machine Learning Enabled Remote Patient Monitoring

DOI

10.2991/978-94-6239-693-7_11How to use a DOI?

Keywords

Internet of Medical Things; Mobile Health; Telehealth Systems; Machine Learning; Artificial Intelligence; Wearable Technology

Abstract

The combined use of the Internet of Things (IoT) with Machine Learning (ML) has grown considerably Remote Patient Monitoring (RPM) because of regular clinical data generation, accelerated measurement, and predictive healthcare decision support. Even so, the extensive use of IoT and ML based RPM systems experiences limitations due to several constraints that demand detailed study. The presented research study carefully analyses the existing literature to determine, organize, and summarize the key technical, operational, ethical and clinical issues associated with IoT and ML based RPM solutions. The study underlines limitations in regulatory compliance, experimental validation, limited scope of disease focus, short-term evaluation of system performance, potential for data overload, cost implications etc. This review paper combines the limitations and correlates them with unresolved research issues, preparing a structure for future research for the purpose of providing useful IoT and ML enabled RPM solutions. The research findings serve to benefit academics, developers and regulators to deal with current limitations and in order to foster patient focused and sustainable RPM solutions.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Sumitra Singar
AU  - Raghuveer Singh Dhaka
PY  - 2026
DA  - 2026/06/16
TI  - Limitations in IoT and Machine Learning Enabled Remote Patient Monitoring
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 91
EP  - 103
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_11
DO  - 10.2991/978-94-6239-693-7_11
ID  - Singar2026
ER  -