Department of Business Development and Technology

Indoor Localization for Optimized Ambient Assisted Living Services

Research output: Contribution to conferenceConference abstract for conference

    Miroslav Mitev, School of Engineering, University of Essex, Colchester, United Kingdom
  • Albena Dimitrova Mihovska
  • Vladimir Poulkov, Faculty of Telecommunications, Technical University of Sofia, BulgariaMilica Pejanovic-Djurisic, University of Montenegro, Montenegro
Indoor localization is very critical for the provision of Ambient Assisted Living (AAL) services, such as e-Health, smart home, etc. The success of deploying a real-time localization system depends on selecting the right performance characteristics. Bluetooth Low Energy (BLE) is a technology, which has the properties to be used for such an application. The usage of BLE can ensure long life of usage, low initial and maintenance cost and due to the current widespread use of the technology, the algorithms can be easily commercialized. This paper proposes an optimized fall detection algorithm that is based on the use of 2D trilateration for enhanced accuracy of the fall position. The indoor localization method with BLE, uses pre-defined Mean Absolute Error (MAE) and Kalman filtering of the received signal strength. Further, we show a practical case of using the received signal strength indicator (RSSI) as an only input for a fall detection system and to evaluate the algorithm in terms of accuracy.
Original languageEnglish
Publication year26 Apr 2017
StatePublished - 26 Apr 2017
EventWireless Telecommunications Symposium - Holiday Inn, Chicago, United States
Duration: 26 Apr 201728 Apr 2017


ConferenceWireless Telecommunications Symposium
LocationHoliday Inn
CountryUnited States

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