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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
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| Paper Title: | DEVELOPMENTANDCALIBRATIONOFAPORTABLESENSORFORMICRO PLASTIC DETECTION USING MACHINE LEARNING ALGORITHM |
| Authors Name: | Dr.R.Thillaikkarasi ME, PhD , B.Dharanipriya , V.Kowsalya , S.Mehalakarthi , S.Sathyapriya |
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IJRTI_212192
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| Published Paper Id: | IJRTI2604327 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | ABSTARCT Water pollution caused by micro plasticsand floating debris has become a serious environmental concern, requiring intelligent monitoring and detection systems for effective management. This project presents a smart water monitoring and micro plastic detection system using convolutional neural network, ESP32, sensors, and Internet of things technology. The system is designed withtwoseparatetankstosimulatereal-time water conditions and analysis. In Tank-1, convolutional neural network is utilized for image processing to detect micro plasticsand micro wood particles present on the water surface. Images captured using an ESP32-CAM module are processed to identify and analyze floating pollutants with improved accuracy. The project aims to utilize fine filtration methods for the effectiveremovalofmicroplastics.Tank-2 is dedicated to water quality monitoring, where an ultrasonic sensor continuously measures the water level distance to ensure safe and controlled operation. A pH sensoris employed to monitor the acidity or alkalinity of the water, providing crucial information about water quality variations.A water motor facilitates the controlled transfer and spraying of water from Tank-1 to Tank-2, enabling integrated analysis between pollutant detection and water quality assessment. The ESP32 microcontroller acts as the central processing unit, managing sensor data acquisition, processing convolutional neural network generated detection outputs, and coordinating system operations. To enhance system responsiveness and accessibility, Internetofthingstechnologyis implementedtotransmitreal-timedataand alert notifications wirelessly to authorized personnel. This enables timely decision- making and rapid response to pollution detection events. Overall, the proposed system offers a cost-effective, automated, and scalable solution for micro plastic detection and water quality monitoring, contributing to improved environmental safety and sustainable water resource management. |
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| Cite Article: | "DEVELOPMENTANDCALIBRATIONOFAPORTABLESENSORFORMICRO PLASTIC DETECTION USING MACHINE LEARNING ALGORITHM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c441-c449, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604327.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604327
Registration ID:212192
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: c441-c449 Country: Salem, Tamilnadu, india Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604327 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604327 |
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ISSN: 2456-3315
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Journal Starting Year (ESTD) : 2016
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