Artificial Intelligence and IoT to Optimize Remote Patient Monitoring in Telemedicine: A Systematic Review

Fernández Ramírez J.O.; Sanchez Perez J.M.; Ibáñez Estrella J.L.; Rueda Ñopo M.I. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.971

Resumen

This systematic review aimed to identify the advances, limitations, and potential of implementing Artificial Intelligence (AI) and the Internet of Things (IoT) in remote patient monitoring through telemedicine. The PICOC methodology was used to structure the research question and the PRISMA method to ensure a rigorous and transparent process in the selection of studies. The search was conducted in three scientific databases: Scopus, Web of Science, and IEEE Xplore, considering publications between 2020 and 2025. A total of 256 articles were retrieved, of which 80 met the inclusion criteria and were analyzed in depth. The studies showed advances such as monitoring automation, greater diagnostic accuracy, expanded coverage in remote areas, and improved treatment adherence. The most common technologies included biomedical sensors, wearable devices, cloud or edge processing, and machine learning models. However, challenges such as a lack of clinical validation, a lack of standardization, and technological access gaps persist. Together, the integration of AI and IoT offers significant potential to improve remote healthcare in a sustainable and contextualized way. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Tecnológica del Perú