This deliverable presents the proposed RadioSense platform for the integration of passive radio sensing and vision technologies into a cloud-IoT framework that performs real-time channel quality information (CQI) time series processing and analytics. Radio sensing and vision technologies allow to passively detect and track objects or persons by using radio waves as probe signals that encode a 2D/3D view of the environment they propagate through. View reconstruction from the received radio signals, or CQI, is based on real-time data processing tools, that combine multiple radio measurements from possibly heterogeneous industrial IoT networks. The proposed platform is designed to efficiently store and analyze CQI time series of different types and provides formal semantics for CQI data manipulation (ontology models). Post-processed data can be then accessible to third parties via JSON-REST calls. Finally, the proposed system supports the reconfiguration of CQI data collection based on the respective application.

Deliverable D3.1: RadioSense system architecture and specification

Sanaz Kianoush;Stefano Savazzi;
2020

Abstract

This deliverable presents the proposed RadioSense platform for the integration of passive radio sensing and vision technologies into a cloud-IoT framework that performs real-time channel quality information (CQI) time series processing and analytics. Radio sensing and vision technologies allow to passively detect and track objects or persons by using radio waves as probe signals that encode a 2D/3D view of the environment they propagate through. View reconstruction from the received radio signals, or CQI, is based on real-time data processing tools, that combine multiple radio measurements from possibly heterogeneous industrial IoT networks. The proposed platform is designed to efficiently store and analyze CQI time series of different types and provides formal semantics for CQI data manipulation (ontology models). Post-processed data can be then accessible to third parties via JSON-REST calls. Finally, the proposed system supports the reconfiguration of CQI data collection based on the respective application.
2020
Istituto di Elettronica e di Ingegneria dell'Informazione e delle Telecomunicazioni - IEIIT
Rapporto intermedio di progetto
Radio Sensing
Passive Localization
edge computing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/400128
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