Automated Wall Painting Robot for Mixing Colors based on Mobile Application

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Ayman Abdullah Ahmed Al Mawali 1 Shaik Mazhar Hussain 1,*

1. Middle East College, Muscat, 121, Oman

* Corresponding author.


Received: 31 Aug. 2022 / Revised: 14 Sep. 2022 / Accepted: 10 Nov. 2022 / Published: 8 Feb. 2023

Index Terms

TCS34725 RGB, STM32, Bluetooth, Wi-Fi, Artificial intelligence


The final stage, which is the building paint or the adopted design, is where most real estate developers and constructors struggle. Where extensive painting is required, which takes a lot of time, effort, and accuracy from the firm doing the work. Additionally, it might be challenging to decide on the precise color grades for the design and calculate the right amount of paint to use for the job. Where these activities are extremely expensive, and the complex implementation is accompanied by worries and skepticism. These are the motivations behind the development of painting machines that blend colors. Artificial intelligence is used in the machine's design to make it efficient and quick at what it does. High accuracy is needed when selecting the proper colors, and this machine is distinguished by its ability to select the proper color tone. The color sensor (TCS34725 RGB) determines the relevance and accuracy of the desired color by comparison with the system database with the assistance of the light sensor (STM32), which measures the degree of illumination of the chosen place. By combining basic colors, this technique saves the customer the hassle of looking at specialized stores for the level of color they require. By giving the system the codes assigned to each color, it may also blend colors. The system also has the feature of controlling the machine remotely via smart phone application by enabling bluetooth and wifi features.

Cite This Paper

Ayman Abdullah Ahmed Al Mawali, Shaik Mazhar Hussain, "Automated Wall Painting Robot for Mixing Colors based on Mobile Application", International Journal of Engineering and Manufacturing (IJEM), Vol.13, No.1, pp. 33-44, 2023. DOI:10.5815/ijem.2023.01.04


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