Abstract:
In this thesis work, smartphone-based colorimeter is designed and practically implemented utilizing the in-built sensors like CMOS camera, flash LED, and high-power processor of the smartphone. The developed totally self-contained colorimeter is low-cost, light-weight, robust, field-portable and easily accessible. It has smart sensing facilities without the requirement of additional optics and external power supply. The device can be applied for real-time and on-site measurements of different types of analytes in the fields of environmental research, biomedical applications, and agriculture, which are completely absent in the currently used conventional bench-top type colorimetric instruments.
In the real-world, for most of the colorimetric detection, attributes of color such as wavelength, intensity, saturation, etc. vary simultaneously according to the variation of analytes. The conventional smartphone-based colorimeters are mainly designed to measure the analytes considering the change in color information in only one domain which limits the colorimetric measurement in some specific analytes with a narrow band of detection. In this research, the developed smartphone-based colorimeter can quantify any analytes through multiple nonlinear regression based colorimetric assessment in a wide range of detection considering the variation of color attributes in all significant domains.
To demonstrate the smartphone-based colorimeter a 3D optical enclosure is designed and fabricated for ensuring the constant illumination and hence to improve the SNR by isolating the measuring platform from the environmental illumination. Self-referencing is a unique characteristic of the instrument to calculate the color ratio with respect to the colorimetric information of the sample. A customized Android-based smartphone app is developed for the complete functioning of the developed colorimeter. The app is developed with the graphical user interfaces of calibration, assessment of the real-time or previously recorded test samples, save, and share the results of colorimetric measurement for multiple analytes of different colorimetric tests. For the first time, a novel wavelength estimation algorithm is developed to estimate the wavelength information of the reflected light of colorimetric measurement.
To justify the performance of the developed colorimeter, three different colorimetric tests are demonstrated in this research named as Rhodamine B concentration quantifier, digital pH meter, and chlorine concentration quantifier using the Xiaomi Redmi Note 4 smartphone. Three different colorimetric characteristics are found for the three samples: only color tone changes significantly with the variation of Rhodamine concentration, the wavelength of color varies significantly with the variation of pH value in water, and color intensity, wavelength, and saturation all vary simultaneously with the variation of chlorine concentration. For all of the three colorimetric tests, the performance of the designed smartphone-based colorimeter is found excellent compared to the conventional colorimeters. The average error of RhB concentration quantifier within the detection range of (0.2-4.0) PPM is 0.95% whereas the chlorine concentration quantifier shows an average error of 1.16% for the detection range of (0.1-8.0) PPM with sensitivity 0.1 PPM. On the other hand, the digital pH meter detects pH value in the range of (4.0-9.0) with an average of 0.0876% detection error.
It is noted that the present smartphone-based colorimeter is designed and demonstrated using three analytes but the developed device can be applied to measure any colorimetric analytes by proper calibration using the developed smartphone app. So, the developed martphonebased colorimeter could be a cost effective common platform for the colorimetric measurement of various analytes in different fields of applications.
Description:
This thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, December 2019.
Cataloged from PDF Version of Thesis.
Includes bibliographical references (pages 82-88).