Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{198793,
        author = {Muralidaar S and Sasidharan S and M Nitish Kanna and R. Subhashini},
        title = {Detection of Microplastics in Water Using Electrical Impedance Measurements and Support Vector Machine},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {9638-9643},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198793},
        abstract = {We propose an approach based on electrochemical impedance spectroscopy (EIS) combined with machine learning for detecting and identifying microplastics in water. The method relies on measuring the complex electrical impedance of water samples over a range of frequencies, capturing both the real and imaginary components of the signal. These impedance responses are represented using Nyquist plots, from which relevant features such as resistance values, peak characteristics, and frequency-dependent behaviour are derived. The classification is carried out in two stages. In first stage, model determines the presence of microplastic in the sample. In second stage, the model detects the type of plastic. EIS signals are processed and transformed into different features, which is used to train support vector machine and XGBoost for identification. The proposed achieves a high accuracy, under controlled condition it shows 95% and in dynamics scenarios it shows 85%-89% and also provides a real-time visualization through a dashboard which makes easier for real time monitoring.},
        keywords = {Electrical Impedance Spectroscopy, Support Vector Machine, Fourier Transform Infrared Spectroscopy, Receiver Operating Characteristic Curve},
        month = {April},
        }