

Arduino-based Colour Detector with TCS 230
Abstract
In today's world, technology has advanced to a level where almost anything is possible. One such example is the usage of color detectors in a variety of applications. Color detectors are devices that can detect and measure the color of an object or surface. Technology has numerous applications in industries such as textiles, automation, automotive, food, printing, pharmaceutical, and many more. The color detector using Arduino and TCS 230 color sensor works by using the principles of light sensing and color measurement. The TCS 230 sensor has an array of photodiodes, each with a specific filter that allows them to sense red, green, blue, and clear light. The TCS230 Color Sensor is a full color detector capable of detecting and measuring practically any visible color. The amount of reflected light is then converted to a frequency signal, which is then processed by the Arduino board. The code is written in C/C++ programming language and can be easily modified and uploaded to the board. This project delves into the domain of color detection utilizing the TCS230 color sensor interfaced with Arduino, creating a symbiotic interaction between technology and the range of hues. The code includes functions to initialize the sensor, read the frequency output, and convert it into a digital value. The digital value is then mapped to a color using predefined values for red, green, and blue. Color detection is vital in industrial automation, particularly in quality control procedures. Color detection is vital in industrial automation, particularly in quality control procedures and in various fields of industries such as Sorting, quality control, and consistency in manufacturing.
Keywords
References
S Banoth, R Aavula, et al (2022), “Multiple Object Detection and Classification based on Pruning Using YOLO”, [Online]
K K S Liyakat (2023). IoT-based healthcare system for home quarantine people, Journal of Instrumentation and Innovation Science, 7, 1-8,
A J Dixit (2015). Iris recognition by Daugman’s algorithm – An efficient approach, Journal of applied Research and Social Sciences, 2(14), 1-4,
A. J. Dixit et al (2014). A review paper on iris recognition, Journal GSD International Society for Green, Sustainable Engineering and Management, 1(14), 71-81,
K.K S Liyakat (2022), “A novel Design of IoT based ‘Love Representation and Remembrance’ System to Loved One’s”, Gradiva Review Journal, 2022, Vol 8, Issue 12, pp. 377 - 383.
V D Gund, et al. (2023). PIR Sensor-Based Arduino Home Security System, Journal of Instrumentation and Innovation Sciences, 8(3), 33-37.
Halli U M, “Nanotechnology in IoT Security”, Journal of Nanoscience, Nanoengineering & Applications, 2022, Vol 12, issue 3, pp. 11 – 16,
Khadake, S. B. Detecting Salient Objects Of Natural Scene In A Video’s Using Spatio-Temporal Saliency & Colour Map. JournalNX, 2(8), 30-35.,
Khadake, S. B., Dolli, S. P., Rathod, M. K., Waghmare, M. O., & Deshpande, M. A. (2016). An Overview of Intelligent Traffic Control System Using Plc and Use of Current Data of Vehicle Travels. JournalNX, 1-4.
Khadake Suhas .B. (2021). Detecting Salient Objects In A Video’s By Usingspatio-Temporal Saliency &Amp; Colour Map. International Journal of Innovations in Engineering Research and Technology, 3(8), 1–9.
Sultanabanu Kazi, et al.(2023). Fruit Grading, Disease Detection, and an Image Processing Strategy, Journal of Image Processing and Artificial Intelligence, 9(2), 17-34.
Karale Aishwarya A, et al, “Smart Billing Cart Using RFID, YOLO and Deep Learning for Mall Administration”, International Journal of Instrumentation and Innovation Sciences, 2023, Vol 8, Issue- 2.
Kazi Sultanabanu Sayyad Liyakat (2023). IoT Based Arduino-Powered Weather Monitoring System, Journal of Telecommunication Study, 8(3), 25-31.
Kazi Sultanabanu Sayyad Liyakat (2023). Arduino Based Weather Monitoring System, Journal of Switching Hub, 8(3), 24-29.
Refbacks
- There are currently no refbacks.
Copyright (c) 2024 Trends in Opto-Electro and Optical Communications