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"IEEE Sensors Alert" is a pilot project of the IEEE Sensors Council. Started as one of its new initiatives, this weekly digest publishes teasers and condensed versions of our journal papers in layperson's language.
It’s impossible to imagine the modern lifestyle without positioning systems and navigation technologies. The widely used Global positioning system (GPS) and navigation technologiesare ineffective in indoor environments. The emergence of indoor positioning technologies came as a boon for the indoor. Indoor positioning using light signals have immensepotential to provide a reliable and more accurate solution to the indoor positioning systems.
MGait is a multi-person identification and intruder detection system that utilizes mm-wave sensing to identify users based on gait micro-Doppler (m-D) signatures. Individuals are continuously tracked in indoor scenarios using low-cost mm-wave radars in range-Doppler (R-D) space frame by frame to extract their distinct gait signatures. Trained in a deep learning-based Gaussian mixture loss model, MGait is a promising solution for biometrics and has wide applications in health and security.
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