Smart Food Quality detection using ML

Smart Food Quality detection using ML

Registration ID: IJNRD_215957

Published ID: IJNRD2403421

DOI: Click Here to Get

Amruta Sadhu , Ayush Patel , Riddhi Mehta , Bhasha Anjaria

quality assurance, product defects, machine vision, image processing, food surface quality, computer vision, segmentation, machine learning, freshness detection, mobile application

One of the most critical aspects of quality assurance is inspecting products for defects before they are sold or shipped. A good product is more vital than having more of the same item for a customer’s enjoyment. the client has a significant role in determining the quality of a product. Another way to think about quality is as the total of all the characteristics that contribute to the creation of items that the client enjoys. Recently, the application of machine vision and image processing technology to improve the surface quality of foods has increased significantly. this is primarily because these technologies make significant advancements in areas where the human eye falls short. this means that, by utilizing computer vision and image processing techniques, time-consuming and subjective industrial quality control processes can be eliminated. Its excess food we waste has a large impact on various environmental factors. This research paper discusses how to check and assess food using picture segmentation and machine learning. then, we propose the development of a user-friendly mobile application that allows customers to conveniently capture and analyse images of their ordered food items in real-time. This application provides instant feedback on the freshness status of the food, enabling customers to take proactive measures if any concerns arise. Segmentation of the image is carried out using the K-means clustering technique. These algorithms determine if a food is fress or not. Finally, freshness detection is carried out using the Machine learning algorithm. An application is proposed to display the results of checking food items by the device.

Published Paper   E-Certificate

"Smart Food Quality detection using ML", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.e151-e154, March-2024, Available :https://ijnrd.org/papers/IJNRD2403421.pdf

Volume 9 Issue 3, March-2024

Pages : e151-e154

Paper Reg. ID: IJNRD_215957

Published Paper Id: IJNRD2403421

Downloads: 000121167

Research Area: Computer Science & Technology 

Country: vadodara, Gujarat, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403421.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403421

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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