Multi-Sensor Data-Driven Synchronization Using Wearable Sensors
Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari

Citation
Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari. "Multi-Sensor Data-Driven Synchronization Using Wearable Sensors". ISWC 2015, ACM (ed.), 113-116, 9, September, 2015.

Abstract
In this paper, we present a method to synchronize the data streams from multiple sensors, including wearables and sensors in the environment. Our approach exploits common events observed by the sensors as they interact. This allows for synchronization of low-power embedded systems in heterogeneous sensor networks by using the events in the physical world to drive the synchronization in the cyber world. Using the events, a sensor-accuracy delay model, and a graph model, we detect physical and cyber couplings between the sensor data streams and determine which couplings will minimize the overall clock drift and time keeping discrepancies. We present a graph model to represent the event couplings between sensors and the drift in the sensor timing. We propose a solution that employs a shortest path algorithm, selects the best set of physical and cyber couplings to update the local time of the sensors, and minimizes the overall clock drift in the system based on the graph model. Our results for two experiments show an improvement of 21.5% and 43.7% for total drift and 59.4% and 60.7% for average drift.

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Citation formats

• HTML

  Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari. <a
  href="http://www.terraswarm.org/pubs/539.html"
  >Multi-Sensor Data-Driven Synchronization Using Wearable
  Sensors</a>, ISWC 2015, ACM (ed.), 113-116, 9,
  September, 2015.

• Plain text

  Terrell R. Bennett, Nicholas Gans, Roozbeh Jafari.
  "Multi-Sensor Data-Driven Synchronization Using
  Wearable Sensors". ISWC 2015, ACM (ed.), 113-116, 9,
  September, 2015.

• BibTeX

  @inproceedings{BennettGansJafari15_MultiSensorDataDrivenSynchronizationUsingWearableSensors,
      author = {Terrell R. Bennett and Nicholas Gans and Roozbeh
                Jafari},
      title = {Multi-Sensor Data-Driven Synchronization Using
                Wearable Sensors},
      booktitle = {ISWC 2015},
      editor = {ACM},
      pages = {113-116},
      day = {9},
      month = {September},
      year = {2015},
      abstract = {In this paper, we present a method to synchronize
                the data streams from multiple sensors, including
                wearables and sensors in the environment. Our
                approach exploits common events observed by the
                sensors as they interact. This allows for
                synchronization of low-power embedded systems in
                heterogeneous sensor networks by using the events
                in the physical world to drive the synchronization
                in the cyber world. Using the events, a
                sensor-accuracy delay model, and a graph model, we
                detect physical and cyber couplings between the
                sensor data streams and determine which couplings
                will minimize the overall clock drift and time
                keeping discrepancies. We present a graph model to
                represent the event couplings between sensors and
                the drift in the sensor timing. We propose a
                solution that employs a shortest path algorithm,
                selects the best set of physical and cyber
                couplings to update the local time of the sensors,
                and minimizes the overall clock drift in the
                system based on the graph model. Our results for
                two experiments show an improvement of 21.5% and
                43.7% for total drift and 59.4% and 60.7% for
                average drift.},
      URL = {http://terraswarm.org/pubs/539.html}
  }
  

Posted by Barb Hoversten on 21 Apr 2015.
Groups: tools