Context-aware energy-efficient wireless sensor architecture for body activity recognition

Abstract

International audienceIn this paper, we present EEWAA, a new Energy-Efficient Wireless sensor Architecture for Activity recognition Applications. Contrary to existing approaches, our solution aims at optimizing the lifetime of every battery-operated devices that may contribute to the activity recognition, including sensors but also smart phones or tablets. Depending on the environment opportunities, our approach balance the load among multiple base stations (mobile phone, tablet, laptop) and when beneficial, enables the energy-limited base stations and/or sensors to offload a part of their tasks to back-end servers. In order to do this, we propose a new decision metric to select the best execution configuration, considering the latency and accuracy requirements, as well as the energy of every device involved in the computation

Human continuous activity recognition based on energy-efficient schemes considering cloud security technology

“…Processing procedure of collected data and computational complexity of the recognition algorithm will affect the system's energy consumption. Therefore, choosing recognition algorithm with low algorithm complexity and increasing the effectiveness of handling the collected data are a challenge in this scenarios There are some researches now devote to reduce energy consumption of recognition system from the aspects of data acquisition, feature extraction, and recognition algorithm.…”

Mobile activity recognition and fall detection system for elderly people using Ameva algorithm

“…This addition allowed the authors to reduce the computational complexity. On the other hand, Rault [13] proposed a new decision metric in order to evaluate these systems. It takes into account latency, accuracy, and energy consumption requirements in order to select the best execution configuration.…”