A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device

Year : 2025 | Volume : 03 | Issue : 02 | Page : 32 41
    By

    Heena T Shaikh,

  • Kazi Kutubuddin Sayyad Liyakat,

  1. Assistant Professor, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
  2. Professor and Head, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

Precise and rapid mixing of chemical and biological reagents is a critical yet challenging aspect of microfluidic systems, often limited by laminar flow conditions and the need for manual or pre- programmed interventions. Existing mixing strategies frequently lack real-time adaptability and closed-loop control, hindering reproducibility and the execution of complex reaction protocols. This work presents an innovative automatic feedback control system utilizing the study on real- time image processing to dynamically optimize the mixing of solutions within a microfluidic device. The design and implementation of a novel automatic feedback control system that uses real-time image processing to dynamically improve solution mixing within a microfluidic device is presented in this study in order to overcome these constraints. The device combines a microfluidic chip with programmable reagent inlets with a high-speed imaging setup and specially designed image processing software. Through the use of fluorescent markers to continuously monitor local concentration gradients, the image processing system may provide real-time feedback to dynamically modify the flow rates of individual inlets. The precise manipulation of reagent concentrations and flow patterns is made possible by this closed-loop feedback mechanism, which guarantees that mixing is actively regulated rather than passively induced. The system integrates a high-speed camera, custom image analysis software, and a microfluidic chip with controllable reagent inlets. By continuously monitoring the local concentration gradient via fluorescent markers, the image processing algorithm provides instantaneous feedback to modulate flow rates of individual inlets. The system’s experimental evaluation shows a significant improvement in homogeneity and mixing efficiency under a variety of operating situations. The system maintains performance even when input flow rates or reagent concentrations fluctuate dynamically, reliably achieves the correct mixing ratios, and shortens the time needed to accomplish uniform reagent distribution. In addition to increasing efficiency, the method improves reproducibility, which lowers variability brought on by manual operation and permits consistent results across multiple experiments. This closed-loop approach demonstrated significantly enhanced mixing efficiency and homogeneity, robustly achieving desired mixing ratios and reducing the time to reach uniform distribution even under varying input conditions. The developed system offers a robust, autonomous, and highly reproducible platform for precise microfluidic mixing, paving the way for advanced chemical synthesis, biological assays, and diagnostic applications requiring dynamic control over reaction environments.

Keywords: Automatic feedback control, Image processing, Microfluidic Device, Closed loop approach,

[This article belongs to International Journal of Advanced Control and System Engineering ]

How to cite this article:
Heena T Shaikh, Kazi Kutubuddin Sayyad Liyakat. A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device. International Journal of Advanced Control and System Engineering. 2025; 03(02):32-41.
How to cite this URL:
Heena T Shaikh, Kazi Kutubuddin Sayyad Liyakat. A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device. International Journal of Advanced Control and System Engineering. 2025; 03(02):32-41. Available from: https://journals.stmjournals.com/ijacse/article=2025/view=235559


References

  1.  Kazi KSL. Significance of Projection and Rotation of Image in Color Matching for High-Quality Panoramic Images used for Aquatic Study. Int J Aquat Sci. 2018;9(2):130–45.
  2. Salunke N, et al. Announcement System in Bus. J Image Process Intell Remote Sens. 2022;2(6).
  3. Kamuni MS, et al. Fruit Quality Detection using Thermometer. J Image Process Intell Remote Sens. 2022;2(5).
  4. Kumtole S, et al. Automatic Wall Painting Robot. J Image Process Intell Remote Sens. 2022;2(6).
  5. Kadam A, et al. Email Security. J Image Process Intell Remote Sens. 2022;2(6).
  6. Kazi KSL. An Approach on Yarn Quality Detection for Textile Industries using Image Processing. In: Proceedings of the International Conference on Advances in Engineering, Science and Technology. 2016. p. 325–30.
  7. Swami D, et al. Sending Notification to Someone Missing You through Smart Watch. Int J Inf Technol Comput Eng (IJITC). 2022;2(8):19–24.
  8. K K. Multiple Object Detection and Classification using Sparsity Regularized Pruning on Low Quality Image/Video with Kalman Filter Methodology (Literature Review). 2022.
  9. Warhade NS, Pol RS, Jadhav HM, Mulani AO. Yarn Quality Detection for Textile Industries using Image Processing. J Algebraic Stat. 2022;13(3):3465–72.
  10. Kazi S, et al. Fruit Grading, Disease Detection, and an Image Processing Strategy. J Image Process Artif Intell. 2023;9(2):17–34.
  11. Sayyad L. Impact of Nanotechnology on Battlefield Welfare: A Study. Int J Nanobiotechnol. 2024;10(2):19–32.
  12. Sayyad L. Internet of Battlefield Things: An IoBT-inspired Battlefield of Tomorrow. J Telecommun Switch Syst Netw. 2024;11(3):11–19.
Regular Issue Subscription Original Research
Volume 03
Issue 02
Received 16/09/2025
Accepted 19/09/2025
Published 31/12/2025
Publication Time 106 Days
105

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