@inproceedings{f8014fcb3b944d53ae27eee006fc9119,
title = "Results classification in an RGB LED based optical fiber sensor system using python",
abstract = "In this paper, the analysis of sensor results from a light emitting diode (LED) based optical fiber sensor (OFS) system is presented. A tri-color RGB (Red-Green-Blue) LED is used to provide three stimulus colors to stimulate a Surface Plasmon Resonance (SPR) sensor which is optically coupled to the system electronics. Analysis of the sensor results under different light conditions is used to identify a particular chemical under test. In the analysis approach undertaken, a combination of the CURE (Clustering Using REpresentatives) data clustering method (algorithm) and the k-nearest neighbor (kNN) algorithm is used for classifying the chemical under test. The system hardware is based on the field programmable gate array (FPGA) and the classification is undertaken on a personal computer (PC) using the Python open source programming language.",
keywords = "Clustering, Optical fiber sensor, Python, RGB LED",
author = "Ong, {Yong Sheng} and Elfed Lewis and Ian Grout and Waleed Mohammed",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2018 ; Conference date: 18-07-2018 Through 21-07-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ECTICon.2018.08619985",
language = "English",
series = "ECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "33--36",
booktitle = "ECTI-CON 2018 - 15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology",
}