Surface Light Barriers

Theo Gabloffsky, Britta Kruse, Ralf Salomon

2022

Abstract

It should be known to almost all readers that light barriers are commonly used for measuring the speed of various objects. These devices are easy to use, quite robust, and of low cost. Despite their advantages, light barriers exhibit certain limitations that occur when the objects of interest move in more than one spatial dimension. This paper discusses a physical setup in which light barriers can also be used in case of two-dimensional trajectories. However, this setup requires rather complicated calculations. Therefore, this paper performs these calculations by means of different neural network models. The results show that backpropagation networks as well as radial basis functions are able to achieve a residual error less than 0.21 %, which is more than sufficient for most sports and everyday applications.

Paper Citation

in Harvard Style

Gabloffsky T., Kruse B. and Salomon R. (2022). Surface Light Barriers. In Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-551-7, pages 97-104. DOI: 10.5220/0010777500003118

in Bibtex Style

@conference{sensornets22,
author={Theo Gabloffsky and Britta Kruse and Ralf Salomon},
title={Surface Light Barriers},
booktitle={Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2022},
pages={97-104},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010777500003118},
isbn={978-989-758-551-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Surface Light Barriers
SN - 978-989-758-551-7
AU - Gabloffsky T.
AU - Kruse B.
AU - Salomon R.
PY - 2022
SP - 97
EP - 104
DO - 10.5220/0010777500003118