<![CDATA[Remote health monitoring is now a viable computer-engineering approach for overcoming the challenge of maintaining a continuous view of a person’s vital signs when not in a hospital or other medical facility. Here, we present a computer engineering framework for a replicable IoT-enabled remote health monitoring system consisting of biomedical sensors, an embedded acquisition node, secure wireless communication, cloud data storage, and a caregiver review dashboard. This work is not intended as an approved medical device; instead, it presents a technical prototyping and simulation framework that illustrates a computer engineering pathway for system designers and architects, demonstrating how the sensing, communication, networking, data handling, security, and alert functions can come together. Our design features a wearable sensor node acquiring ECG, SpO2, HR, temperature, and motion-based activity indicators. Local filtering, packetization with quality flags, secure over-the-air transmission via MQTT or HTTPS, cloud data storage, and data interpretation as structured observations viewable by authorized individuals are employed. We introduce a transparent performance model to quantify the system load requirements, latency, duty cycle of the acquisition node, probability of dat FHIR a loss, and alert response time. Under assumptions specified herein, this model suggests a typical WiFi usage resulting in approximately 300 milliseconds of end-to-end transmission latency for the normal periodically sampled readings, while a busy cellular transmission may be acceptable for passive monitoring if coupled with buffering. We show that the quality of a remote monitoring platform stems more from the interdependent selection of sampling rates, packet sizes, communication technologies and security parameters, than from individual sensor technology selections alone]]>
