An Arrangement to Locate and Identify People with Dual-Frequency Tags Providing Context-Related Information

Antti Ropponen

    Research output: ThesisDoctoral ThesisCollection of Articles


    The demographic dependency ratio is changing in the industrialized countries, because the proportion of senior citizens is growing. An electric sensor with intelligence (ELSI) system was developed to monitor and locate patients, which helps the caring personnel and upgrades the service. The system has been used in many care homes for the elderly in Finland and has proved its benefits for the patients and staff. The problem with the ELSI system was that it could not identify the people it located. Additionally, the alarm devices that were used were impractical. Hence a dual-band localization system was introduced to address these deficiencies. The dual-band system uses active tags that are located with an antenna matrix embedded into the ELSI floor. The tag communicates with the ELSI system using a ZigBee network. The tag also has a display, and thus it can be used to show short alarms. Furthermore, an outline of a more versatile alarm and information system is introduced, with a multifunctional name tag concept. The system introduced here was demonstrated with a pilot installation which consisted of the ELSI and the dual-band system. It was shown that the system can locate and identify people with an accuracy of 0.64 m ± 0.31 m (S.D.). The accuracy can even be improved if the data are combined with the ELSI localization information. It was also shown with measurements that the localization method can be considered to be robust, because the LF signal penetrates nearly all normal objects.
    Translated title of the contributionKontekstipohjaiseen dataan perustuva järjestely ihmisten tunnistamiseen ja paikantamiseen kaksitaajuustunnisteella
    Original languageEnglish
    QualificationDoctor's degree
    Awarding Institution
    • Aalto University
    • Sepponen, Raimo, Supervising Professor
    • Sepponen, Raimo, Thesis Advisor
    Print ISBNs978-952-60-4870-3
    Electronic ISBNs978-952-60-4871-0
    Publication statusPublished - 2012
    MoE publication typeG5 Doctoral dissertation (article)


    • indoor tracking
    • radio frequency identification
    • near field imaging
    • low-frequency
    • ZigBee
    • elder care
    • electric sensor with intelligence (ELSI)


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