V.I.P. | MassiVe MIMO Radio Channel- and Learning-based Indoor Passive Localization and Posture Identification for Multiple Humans

Summary
The aim of the proposed V.I.P. project is to achieve passive localization and posture identification of multiple humans in indoor environment for assisted-living functionalities. We propose to use the temporal-spatial-delay domain radio channel properties with dedicated design of massive Multiple-Input Multiple-Output (MIMO) topology and configuration for specific physical environment, and use the neural-networks-based learning algorithm recognizing the interactions between the human form-factors (body type/shape, posture, motion) and the aforementioned indoor radio channel. Both simulation and measurement platforms will be built to estimate and measure the radio propagation resulting from the reconfigurable physical environment, multiple-antenna systems, and human form-factors.

The proposed research is multidisciplinary, connecting networked systems, electromagnetism, smart building, human factors, and data science. It proactively combines MIMO radio networked system with smart building, targeting at identifying MULTIPLE humans with the help of neural networks. It is proposed by a female researcher with rich international experience, and is supervised by a female professor with top track record. The proposed research includes gender-dependent modelling and parameterization on the propagation mechanism of human-radio interaction, potentially using the double-layer reflection and the uniform theory of diffraction. The body postures are simplified into geometries with homogeneous dielectric, e.g. a standing/laying human as ellipsoid, sitting on the ground with legs crossed as triangle.

Upon the completion of the research, training and networking of V.I.P., the researcher will profit from the first-hand experience on designing and developing the networked system for specific use case, developing neural-network-based pattern recognition methodology, as well as growing towards professional maturity from proposing, coordinating, finance managing, educating to impacting.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101026885
Start date: 01-11-2021
End date: 30-10-2025
Total budget - Public funding: 166 320,00 Euro - 166 320,00 Euro
Cordis data

Original description

The aim of the proposed V.I.P. project is to achieve passive localization and posture identification of multiple humans in indoor environment for assisted-living functionalities. We propose to use the temporal-spatial-delay domain radio channel properties with dedicated design of massive Multiple-Input Multiple-Output (MIMO) topology and configuration for specific physical environment, and use the neural-networks-based learning algorithm recognizing the interactions between the human form-factors (body type/shape, posture, motion) and the aforementioned indoor radio channel. Both simulation and measurement platforms will be built to estimate and measure the radio propagation resulting from the reconfigurable physical environment, multiple-antenna systems, and human form-factors.

The proposed research is multidisciplinary, connecting networked systems, electromagnetism, smart building, human factors, and data science. It proactively combines MIMO radio networked system with smart building, targeting at identifying MULTIPLE humans with the help of neural networks. It is proposed by a female researcher with rich international experience, and is supervised by a female professor with top track record. The proposed research includes gender-dependent modelling and parameterization on the propagation mechanism of human-radio interaction, potentially using the double-layer reflection and the uniform theory of diffraction. The body postures are simplified into geometries with homogeneous dielectric, e.g. a standing/laying human as ellipsoid, sitting on the ground with legs crossed as triangle.

Upon the completion of the research, training and networking of V.I.P., the researcher will profit from the first-hand experience on designing and developing the networked system for specific use case, developing neural-network-based pattern recognition methodology, as well as growing towards professional maturity from proposing, coordinating, finance managing, educating to impacting.

Status

SIGNED

Call topic

MSCA-IF-2020

Update Date

28-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility
H2020-MSCA-IF-2020
MSCA-IF-2020 Individual Fellowships