Distributed systems (3rd ed.): concepts and design
Distributed systems (3rd ed.): concepts and design
Time-diffusion synchronization protocol for wireless sensor networks
IEEE/ACM Transactions on Networking (TON)
Fidelity and yield in a volcano monitoring sensor network
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Recognition of dietary activity events using on-body sensors
Artificial Intelligence in Medicine
Recovering temporal integrity with Data Driven Time Synchronization
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Using sound source localization in a home environment
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Time synchronization in sensor networks: a survey
IEEE Network: The Magazine of Global Internetworking
Proceedings of the Fifth International Conference on Body Area Networks
Characterising and minimising sources of error in inertial body sensor networks
International Journal of Autonomous and Adaptive Communications Systems
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A major challenge in using multi-modal, distributed sensor systems for activity recognition is to maintain a temporal synchronization between individually recorded data streams. A common approach is to use well defined 'synchronization actions' performed by the user to generate, easily identifiable pattern events in all recorded data streams. The events are then used to manually align data streams. This paper proposes an automatic method for this synchronization. We demonstrate that synchronization actions can be automatically identified and used for stream synchronization across widely different sensors such as acceleration, sound, force, and a motion tracking system. We describe fundamental properties and bounds of our event-based synchronization approach. In particular, we show that the event timing relation is transitive for sensor groups with shared members. We analyzed our synchronization approach in three studies. For a large dataset of 5 users and totally 308 data stream minutes we achieved a synchronization error of 0.3 s for more than 80% of the stream.