IJRTI
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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 120

Article Submitted : 24205

Article Published : 9239

Total Authors : 24597

Total Reviewer : 847

Total Countries : 165

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: A MULTI LAYERED IOT BASED BODE RALERT HEALTH MONITORING SYSTEM FOR COMMERCIAL FISHERMEN
Authors Name: R.Agilandeswari, ME , S.Chandrasekaran , P.Dhayaniyhi , P.Goventhan , S.Nandhakumar
Download E-Certificate: Download
Author Reg. ID:
IJRTI_211975
Published Paper Id: IJRTI2604297
Published In: Volume 11 Issue 4, April-2026
DOI:
Abstract: The proposed system presents an intelligent and automated boat-based monitoring solution designed for the detection and identification of microplastics in water bodies. This system integrates advanced image processing techniques, embedded control systems, wireless communication, andIoT-basedmonitoringtoensureaccurate detectionandreal-timedatatransmissionfor environmental protection. In this system, MATLAB is utilized to process boat- captured images from a predefined dataset. The image processing stage plays a crucial role in analyzing water surface images to detect the presence of microplastics. A Convolutional Neural Network (CNN) algorithmisimplementedforefficientfeature extraction and classification. The CNN model automatically learns important visual patterns such as shape, texture, and colour variations, which are essential for distinguishing microplastics from other floatingparticles.Additionally,colour-based segmentation techniques are incorporated to improve detection accuracy by isolating plastic materials based on their spectral characteristics. This combination of deep learning and colour analysis enhances the reliability and precision of microplastic identification. The overall system operation is controlled by an ESP32 microcontroller, whichservesasthecentralprocessingunitof the boat system. The ESP32 manages all connected sensors and coordinates real-time data acquisition and processing. Its high processing speed, built-in Wi-Fi capability, andlowpowerconsumptionmakeitsuitable forembeddedmarineapplications.The controller continuously collects sensor data, processes operational commands, and ensures smooth integration between hardware and software components.For wireless communication within short distances,anRFtransmitterandreceiverpair is implemented. This radio frequency communication system enables the reliable transmission and reception of essential boat information, suchas detectionstatus, system health, and navigation updates. The RF module ensures stable and low-latency communication between the boat and the nearby monitoring station, even in remote water environments where conventional communication networks may be limited. Overall, the proposed smart boat monitoring systemcombinesimageprocessing,artificial intelligence, embedded systems, wireless communication,andIoTtechnologytocreate an efficient and automated solution for microplastic detection. The integration of MATLAB-basedCNNanalysiswithESP32- controlled real-time operations ensures accurate identification, reliable communication,andeffectiveenvironmental monitoring, contributing significantly to sustainable water resource management.
Keywords:
Cite Article: "A MULTI LAYERED IOT BASED BODE RALERT HEALTH MONITORING SYSTEM FOR COMMERCIAL FISHERMEN", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c203-c209, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604297.pdf
Downloads: 000205508
ISSN: 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
Publication Details: Published Paper ID: IJRTI2604297
Registration ID:211975
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: c203-c209
Country: salem, Tamil Nadu, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604297
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604297
Share Article:

Share Facebook Twitter Google+ Pinterest LinkedIn Email Tumblr WhatsApp Google Gmail

Click Here to Download This Article

Article Preview
Click Here to Download This Article
Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300
IJRTI

WhatsApp
Click Here

Indexing Partner
Copyright © 2026 - All Rights Reserved - IJRTI