Energy-efficient and Reliable Wearable Internet-of-Things through Fog-Assisted Dynamic Goal Management

Management of energy dissipation and battery life is a challenge in health monitoring wearables. Low-quality data collection, non-reliable monitoring process, and missing important health events are consequences of single-goal fixed-policy solutions. In this research, energy dissipation of IoT-based wearable systems is managed through a dynamic multi-goal approach. Health status of the user of a wearable device, the continuity of monitoring, and the accuracy of collected data are parameters we consider in our goal hierarchy to select a proper system management policy at run-time to achieve the most significant goal at a given time. In our approach, a dynamic observation process assesses the user and system data and a fog-assisted control engine detects the states, enforces the proper policy, and reconfigures the wearable sensor. To demonstrate our solution, we develop a real reconfigurable wireless sensor node with an ability to follow a set of parametrically defined policies and performed a set of experiments to find the most efficient setting. Our evaluation shows that the proposed system is able to reduce the power consumption by 44% and prevent the data loss due to battery shortage in 0.78% of total data collection time compared to a baseline system without a goal manager.