Synchronization of Separate Sensors’ Data Transferred through a Local Wi-Fi Network: A Use Case of Human-Gait Monitoring

Viktor Masalskyi, Dominykas Čičiurėnas, Andrius Dzedzickis (), Urtė Prentice, Gediminas Braziulis and Vytautas Bučinskas ()
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Viktor Masalskyi: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania
Dominykas Čičiurėnas: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania
Andrius Dzedzickis: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania
Urtė Prentice: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania
Gediminas Braziulis: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania
Vytautas Bučinskas: Department of Mechatronics, Robotics and Digital Manufacturing, Faculty of Mechanics, Vilnius Gediminas Technical University, Plytinės Str. 28, LT-10505 Vilnius, Lithuania

Future Internet, 2024, vol. 16, issue 2, 1-22

Abstract: This paper addresses the challenge of synchronizing data acquisition from independent sensor systems in a local network. The network comprises microcontroller-based systems that collect data from physical sensors used for monitoring human gait. The synchronized data are transmitted to a PC or cloud storage through a central controller. The performed research proposes a solution for effectively synchronizing the data acquisition using two alternative data-synchronization approaches. Additionally, it explores techniques to handle varying amounts of data from different sensor types. The experimental research validates the proposed solution by providing trial results and stability evaluations and comparing them to the human-gait-monitoring system requirements. The alternative data-transmission method was used to compare the data-transmission quality and data-loss rate. The developed algorithm allows data acquisition from six pressure sensors and two accelerometer/gyroscope modules, ensuring a 24.6 Hz sampling rate and 1 ms synchronization accuracy. The obtained results prove the algorithm’s suitability for human-gait monitoring under its regular activity. The paper concludes with discussions and key insights derived from the obtained results.

Keywords: sensor network; remote data transfer; latency; network synchronization; gait analysis (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2024
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