Print Email Facebook Twitter Light Based Activity Recognition Using Realistic Data Title Light Based Activity Recognition Using Realistic Data Author Vos, Jasper (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Zuniga, Marco (mentor) Zaidman, A.E. (graduation committee) Chavez Tapia, M.A. (graduation committee) Degree granting institution Delft University of Technology Programme Computer Science and Engineering Project CSE3000 Research Project Date 2022-06-27 Abstract In the field of Visible Light Sensing, light sensors are used to extract information from objects which do not actively communicate any information. Previous research within this field proposed the system called SolAR, and proved the possibility of using a solar cell as both a power source and an activity sensor. A wrist mounted solar cell generates more energy than it uses during operation, while achieving a high classification accuracy for different activities. While the wearer performs different activities, the power output of the solar cell fluctuates. In turn, these fluctuations are used to recognise activities. To extend on the concept of SolAR, this paper introduces a prototype to obtain data from different activities while performing day-to-day tasks. During these activities, ordinary actions are performed to emulate natural circumstances. Analysis of this data initially shows no significant drop in accuracy when compared to SolAR. Further examination shows significant differences in mislabelling rates when comparing to the results of SolAR. Subject VLSHuman Activity Recognitionsolar power To reference this document use: http://resolver.tudelft.nl/uuid:56117801-47e6-4c91-9d55-e7db6046a8ba Part of collection Student theses Document type bachelor thesis Rights © 2022 Jasper Vos Files PDF RP_Jasper_Vos.pdf 4.4 MB Close viewer /islandora/object/uuid:56117801-47e6-4c91-9d55-e7db6046a8ba/datastream/OBJ/view