Sensors, Vol. 20, Pages 6104: DynDSE: Automated Multi-Objective Design Space Exploration for Context-Adaptive Wearable IoT Edge Devices

We report a case study for the design of electromyographic-monitoring eyeglasses with applications in automatic dietary monitoring. The design space included two spotting algorithms, and two sampling algorithms, intended for real-time execution on three microcontrollers. DynDSE yielded configurations that balance retrieval performance and resource consumption with an F1 score above 80% at an energy consumption that was 70% below the default, non-optimised configuration. We expect that the DynDSE approach can be applied to find suitable wearable IoT system designs in a variety of sensor-based applications.
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research