Green AI for Telehealth
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Yunyong Guo1, Bryan Guo1, Nathan Guo1
1University of Victoria Institute on Aging & Lifelong Health, Victoria, British Columbia, Canada.
Abstract:
Telehealth is increasingly supported by connected devices, remote monitoring, Artificial Intelligence (AI), and distributed computing. These tools can extend access and support more responsive care, but their computational and environmental demands are rarely considered alongside clinical and organizational needs. We describe the current Canadian telehealth landscape, including remote care management, virtual visits, patient portals, and remote monitoring, and identify opportunities and gaps for AI integration. We then define Green AI in healthcare and explain how an IoT-fog-cloud architecture can support resource-aware telehealth. For health leaders, Green AI is not only an engineering issue. It affects procurement, infrastructure planning, workforce capacity, clinical workflow, environmental responsibility, and equity. Evaluation should consider clinical performance, resource use, organizational fit, and sustainability. Responsible AI-enabled telehealth requires more than technical performance. A Green AI perspective can help health organizations improve computational efficiency while maintaining patient safety, usable workflows, resilience, and equitable access.
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