SOURCE-LINKED INTELLIGENCE

An Energy-Efficient AI Powered Portable Radar System for Human Activity Recognition

CORDIS · observation · Publication date unknown

ered Portable Radar System for Human Activity Recognition Radar systems have been used in ambient sensing to track various subjects using electromagnetic waves. Thanks to the increasing capability of artificial intelligence algorithms in solving classification tasks, human activity detection (HAR) using radar systems have become possible. However, most previous solutions use bulky fixed radar systems with tens to hundreds of watts of power consumption, requiring rigid wall plug connection, making them environmentally unfriendly and difficult to use in applications like indoor security, healthcare, and mobile robots. In this project, we aim to develop a portable radar system for HAR by following a hardware-software co-design approach to significantly reduce the signal processing energy consumption compared to conventional radar-based HAR systems. On the software side, we will explore novel time-domain feature extraction methods to reduce the energy consumption of radar data analysis by at least 2 times. We will also apply brain-inspired neuromorphic principles to reduce 50 times the

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recordType

award

status

SIGNED

region

EU

value

203464.32

unit

EUR