Though concurrent growth of technologies can sometimes lead to discord, often they lead to the meshing of ideas to form a new frontier of study, collaboration, and innovation. Recently, the inelastic ..
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Though concurrent growth of technologies can sometimes lead to discord, often they lead to the meshing of ideas to form a new frontier of study, collaboration, and innovation. Recently, the inelastic collision of technologies has begotten a new frontier, called Medical Artificial Intelligence of Things (MAIot), edge-inferencing, encompassing the knowledge from Internet of Things (IoT) and Artificial Intelligence (AI), just targeted toward medicine using physiological data. Further, MAIoT is a discipline-focused subcategory of Artificial Intelligence of Things (AIoT) where feature detection from sensor data is done by a Machine Learning (ML) model programmed on a microprocessor unit (MPU); sequentially, inference results are communicated to an IoT network using additional software and an integrated circuit (IC) radio transceiver. In this study, Machine Vision (MV), a computer vision-based form of ML, is used to enhance camera data for a domain-specific purpose. High-power demand, specifically, from the camera, microprocessor, radio transceiver, and other sensors operating simultaneously, generates a load of approximately 7.916 Watts. This is a problem for the battery within the targeted handheld device. Therefore, a power management subsystem featuring battery HotSwap was conceived by combining hardware, software, and mechanical design to retain wireless modality, IoT connectivity, and practitioner dexterity during health monitoring.
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