Technological trends in different domains have en-abled operators to integrate large numbers of sensors within their wireless communication networks. These sensors can provide data for many different fields of applications, e.g. process monitoring, eHealth or position feedback for closed loop control of autonomous vehicles. However, such systems often face the challenge to aggregate and process information from many distinct sources in a homogeneous and coherent manner. We propose a software architecture design that is based on any context management and message handling system. The general objective is to design a common interface for different information sources. We assume that by processing this data in conjunction it can be possible to obtain enhanced quality of information. The presented abstract architecture can enable the user to flexibly integrate different Information Anchors - active sensors or passive tags - within a comprehensive multi-modal, multi-domain data aggregation platform. By applying a system as proposed, it is possible to generate a pool of homogeneous data sets that can be used as a sound foundation for further analysis. We demonstrate the feasibility of the concept by presenting a possible realization of a system as described in form of an inter-operable multi-technology indoor localization system.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Unified Multi-Modal Data Aggregation for Complementary Sensor Networks Applied for Localization


    Contributors:


    Publication date :

    2022-06-01


    Size :

    2258212 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Complementary Multi–Modal Sensor Fusion for Resilient Robot Pose Estimation in Subterranean Environments

    Khattak, Shehryar / Nguyen, Huan / Mascarich, Frank et al. | IEEE | 2020


    LOOP CLOSURE USING MULTI-MODAL SENSOR DATA

    RAMANATHAN NARAYANAN / MEYER TIMON / TOUMIER GLENN et al. | European Patent Office | 2023

    Free access

    Object velocity detection from multi-modal sensor data

    PRADHAN SABEEK MANI / SLOAN COOPER STOKES | European Patent Office | 2023

    Free access

    Annotating images based on multi-modal sensor data

    FERSTL DAVID / KOESTINGER MARTIN / NAVOT AMIR | European Patent Office | 2020

    Free access