IoT Based Water Turbinity Classification Using Color Sensor TCS3200

DOI

10.2991/978-94-6463-084-8_14How to use a DOI?

Keywords

Internet of Things; Smart Electrical Vehicle; Genetic Programming First Section

Abstract

The use of water in households must pay attention to the cleanliness factor of the condition of the water itself. Based on the Regulation of the Minister of Health of the Republic of Indonesia Number 416/Menkes/PER/IX/1990, water quality requirements include physical, chemical, biological, and radiological qualities so that if consumed or used, it will not cause side effects. This study created a water turbidity classification system based on the TCS3200 IoT color sensor using the MQTT data communication protocol. This research was conducted by testing three times, namely, black box testing, then hardware testing, namely testing the TCS3200 color sensor, and testing with different containers. This study’s classification system belongs to the excellent system category and is feasible to use. The classification system website page can display data from current water conditions and detection history obtained using the MQTT protocol. Based on black box testing, it can be concluded that all functions have been running properly, and the system can perform classification well. Experiments using different containers show that the system can perform the classification as expected if it is calibrated first on each container. Based on the graph of RGB values, mud, moss, and soil have relative RGB values. Tests carried out with closed containers can produce a better classification than containers with open conditions because light intensity influences the surroundings.

Copyright

© 2022 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ida Ayu Vigi Meidhyana Putri
AU  - Wirarama Wedashwara
AU  - Ariyan Zubaidi
AU  - I Wayan Agus Arimbawa
PY  - 2022
DA  - 2022/12/26
TI  - IoT Based Water Turbinity Classification Using Color Sensor TCS3200
BT  - Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Informatics and Computer Science) (MIMSE-I-C-2022)
PB  - Atlantis Press
SP  - 142
EP  - 155
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-084-8_14
DO  - 10.2991/978-94-6463-084-8_14
ID  - Putri2022
ER  -