Development of an IoT System to Gather, Assess, and Improve Cyber-Physical Interaction Data

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A sensor network consisting of small circuits that can be attached to physical equipment in a classroom environment was designed, manufactured, programmed, and tested. Each sensor measures human interaction with the equipment to which it is attached based on motion and reports the data wirelessly to a central Hub computer. All sensor operation is autonomous and requires no direct user-input. The sensors optionally and automatically pair with users through an associated user-worn sensor. The sensor network operates continuously over a long period of time with zero maintenance or operator intervention. The intention of this system is to collect data in a classroom to identify what equipment students use regularly. With this information, educators can make informed decisions about the impact that various resources have. To prove the functionality of the technology developed, a study was done at a fitness center where the sensors were attached to exercise machines. This was a comparable environment to a classroom as it involves consistent human-equipment interaction and was more readily accessible for this research due to ethics involving young students in research along with access restrictions due to COVID-19. The work carefully details the hardware and firmware development of the sensors as they are intended to be commercial-grade yet low cost for mass production. Thirty-five Equipment Sensors and fifteen User Sensors were fabricated and installed in the fitness facility for a two-week period and produced over 30,000 data points. Using redundant sensors on each equipment enabled comparison of the technical performance without having to directly involve gym participants. This gave the benefit of an authentic testing environment where participants would not change their behavior due to the study. The sensor data was used to assess the sensor’s technical performance. The Equipment Sensors provided reliable indication of equipment usage. The User Sensor portion of the study was limited as participation was voluntary and only passively advertised. Recommendations are provided on how to improve the sensor network and use it for future educational research in the classroom.
Engineering Education, Smart classroom, Personalized education, Sensor, Motion sensing, Student interaction, Activity monitoring
Long, J. (2023). Development of an IoT system to gather, assess, and improve cyber-physical interaction data (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from