1 Department of Computer Science, School of Computing and Informatics, Kaimosi Friends University, Kaimosi, Kenya.
2 Department of Information Technology, School of Computing and Informatics, Kaimosi Friends University, Kaimosi, Kenya.
World Journal of Advanced Research and Reviews, 2026, 31(01), 533–544
Article DOI: 10.30574/wjarr.2026.31.1.1806
Received on 23 May 2026; revised on 05 July 2026; accepted on 09 July 2026
Remote monitoring of patients with chronic diseases can extend care beyond hospitals. However, most Internet of Medical Things (IoMT) frameworks assume that patients have stable electricity and internet connections and have high levels of digital literacy. These assumptions may not hold true in under-resourced communities. In response, we propose CARE-Lite IoMT, a context-specific framework for energy-efficient remote monitoring of chronic patients. The framework integrates low-power sensors, smartphone gateways, contextual sensing, community health worker support, interoperability, and secure communication. A design-science methodology was used to develop the framework through problem identification, literature-derived requirement specification, framework design, and scenario-based evaluation. Through scenario analysis, the system reveals that patient monitoring can be performed locally, and only information that reflects clinically meaningful changes can be sent to clinicians. Results from this developed framework show that energy efficiency should be regarded as a clinical safety requirement for remote monitoring systems rather than a secondary engineering consideration. The findings support IoMT designs based on low-power operation, offline resilience, actionable triage, interoperability, and secure data exchange.
Internet of Medical Things; Remote patient monitoring; Chronic disease; Energy-adaptive monitoring; Edge-fog computing; Resource-limited settings; Community health workers
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Abraham Isiaho, Kelvin Omieno and Ayub Shirandula. A context-specific IoMT framework for energy-efficient remote monitoring of chronic patients in resource-limited settings. World Journal of Advanced Research and Reviews, 2026, 31(01), 533–544. Article DOI: https://doi.org/10.30574/wjarr.2026.31.1.1806