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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: June 2026
Volume 11 | Issue 6
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 121
Article Submitted : 24726
Article Published : 9361
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| Paper Title: | Deep Fish Net |
| Authors Name: | Jyothika V , Mrs.Athira V , Krishnendhu S Nair , Vighnesh T , Hanan M V |
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IJRTI_212374
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| Published Paper Id: | IJRTI2605043 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | Ensuring the freshness and safety of fish is vital to maintaining high quality seafood standards and consumer trust. Traditional methods of fish freshness evaluation such as manual inspection and chemical testing are often subjective, time consuming and unsuitable for large scale operations. To overcome these limitations, this paper presents Deep Fish Net, an intelligent and non invasive fish quality monitoring system that integrates sensor data acquisition with deep learning based image analysis. The system employs an ESP32 microcontroller as the central control unit, interfacing with multiple sensors including a temperature sensor, ammonia sensor and ultrasonic sensor to monitor environmental conditions affecting fish freshness. A camera module captures real time images of fish samples on a conveyor belt mechanism driven by DC motors controlled through an L293D motor driver IC. Captured images and sensor data are transmitted to a server, where a Convolutional Neural Network (CNN) fine tuned using MobileNetV2 classifies fish into distinct freshness categories. Experimental results demonstrate an impressive classification accuracy of 97.50%, outperforming conventional inspection techniques in both speed and reliability. Real time monitoring and alert generation through LED indicators and buzzer notifications are made possible. The proposed Deep Fish Net framework provides an efficient, accurate and scalable solution for automated fish freshness assessment, significantly enhancing food safety, reducing spoilage and improving quality control in seafood processing industries. |
| Keywords: | Deep Learning, Fish Detection, CNN, Image Classification, Marine Monitoring, Artificial Intelligence |
| Cite Article: | "Deep Fish Net ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a382-a386, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605043.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: IJRTI2605043
Registration ID:212374
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: a382-a386 Country: Kannur , Kerala , India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605043 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605043 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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