Towards energy efficient sensor nodes for online activity recognition

Abstract

In sensor-based activity recognition often huge amounts of data have to be acquired from multiple sensors, which need to be communicated for further processing. When using wireless sensor nodes, energy efficiency is of outstanding importance, since it directly influences the time until the battery needs to be recharged. However, communicating a huge amount of sensor data over wireless interfaces causes high energy consumption as well. Furthermore, the host controller receiving the sensor data is hindered of using its low power modes, as it needs to be woken up more frequently as well. In the paper at hand, we introduce our approach of reducing energy consumption of sensor nodes in online activity recognition scenarios by calculating the feature extraction on the sensor subsystem itself. By doing so, we can reduce the output rate of the sensor which enables the host controller to stay in its low power modes for longer periods. Additionally, this approach drastically reduces the amount of data to be transmitted over wireless interfaces, which further improves energy consumption. In our experiments, the proposed approach reduces the energy consumption of a sensor node by up to 33 %.