<![CDATA[Pain in osteoarthritis varies across time, activity, sleep, and environmental context, while conventional clinic-based recall may not capture short-term fluctuations. Internet of Things technology offers a means to combine repeated self-reported pain assessments with mobility and physiological measurements from wearable devices. This conceptual technical review defines design requirements for an IoT-based remote pain monitoring system for older adults with osteoarthritis. The proposed architecture includes wearable and mobile sensing, ecological momentary assessment, secure data transmission, quality control, event detection, visualization, and clinician review. The synthesis emphasizes that pain remains a subjective experience and should not be inferred solely from sensor data. Wearable measures can contextualize patient reports and identify changes that warrant review, but they should not automatically diagnose or alter treatment. Key engineering requirements include low-burden interaction, large and accessible controls, intermittent-connectivity support, timestamp synchronization, missing-data detection, encryption, role-based access, and transparent alert thresholds. Evaluation should include usability, adherence, battery performance, transmission reliability, data completeness, false-alert rate, and agreement between device records and reference measures. The framework provides a responsible pathway for developing remote monitoring systems that support clinical decision-making while preserving patient autonomy and safety.]]>
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