| Summary: | Performances of athletes, and in this case table-tennis players, are supported by data analytics
technology. This technology then allows the team to strategize their gameplay by analyzing
metrics from the collected data. Sports analysis is important to improve the performance of a
player as well as a team’s quality of play. In this project, surface-mounted piezoelectric shock
sensors are used to convert flat surfaces into low-cost touch interface with algorithm to estimate
the TDOA between the signals by onset detection in the time-frequency domain. The
coordinates of the localization of the table tennis ball will then be computed for the usage of
athletes’ analysis of their accuracy. For real time analysis, the localization computation has to
be quick and hence the main focus of this project is to reduce the computational time for the
localization.
This report will firstly introduce the project by explaining the motivation behind this project
as well as the aims and objectives that was set to be achieved at the end of the whole
duration. This will be followed by the literature review with research findings as well as
existing information required for the project. Next, the whole process of how the optimizing
was implemented as well as the results will be shown and lastly, challenges faced while
working on the project as well as necessary future work will be discussed.
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