BaaS (Bluetooth-as-a-sensor)
Douglas Lautner, Xiayu Hua, Scott DeBates, Miao Song, Jagat Shah, Shangping Ren · 2017
As network connectivity becomes more capable, mobile devices are evolving into sensory data accumulators. Bluetooth (BT) components, which are widely used for communication purposes, also have the potential to become contextual sensors by constantly listening to information broadcast by nearby Bluetooth Low Energy (BLE) beacons. Compared to traditional Micro-Electro-Mechanical (MEMs) based contextual sensors, Bluetooth-as-a-Sensor (BaaS) provides a wider sensing spectrum and more comprehensive environmental information. However, current implementations of BT are optimized as a data transmitter, therefore deploying BaaS on a traditional mobile platform would cause an unacceptably high current drain and hence a significant reduction in battery life. Our objective is to conquer the current drain problem associated with having continuous wireless BT sensing. We provide a novel BaaS-based architecture which utilizes an energy-efficient sensor fusion core (SFC) to execute heavy-duty and long-standing tasks. We also present an optimized duty cycle algorithm that minimizes the duty cycle while guaranteeing an application's QoS requirements. Both BaaS architecture and algorithm are implemented and deployed on a Moto X platform and then applied to an indoor location service for consumer use validation. The performance of the BaaS-based architecture is evaluated for both average current drain and location accuracy. Data measured on Moto X shows that when using the BaaS architecture, the battery life is 5 times longer than using the traditional BT architecture.