Next Article in Journal
Evaluation of the Effect of Nanoparticle Presence in Furnace Off-Gas on Heat and Mass Transfer in Extraction Ducting
Previous Article in Journal
Use of Biomass Residues in MB Removal from the Aqueous Phase
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Proceedings
Volume 105
Issue 1
10.3390/proceedings2024105088
proceedings-logo
Submit to this Journal
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Abstract

BMLFTS: A Novel Approach to Process and Track of Food Quality Data Using Blockchain and Machine Learning †

by
Ajay B. Gadicha
*,
Vijay B. Gadicha
and
Mayur S. Burange
Department of Artificial Intelligence and Data Science, P R Pote Patil College of Engineering and Management, Amravati 444602, Maharashtra, India
*
Author to whom correspondence should be addressed.
†
Presented at the 3rd International Electronic Conference on Processes—Green and Sustainable Process Engineering and Process Systems Engineering (ECP 2024), 29–31 May 2024; Available online: https://sciforum.net/event/ECP2024.
Proceedings 2024, 105(1), 88; https://doi.org/10.3390/proceedings2024105088
Published: 28 May 2024
(This article belongs to the Proceedings of The 3rd International Electronic Conference on Processes—Green and Sustainable Process Engineering and Process Systems Engineering)
Versions Notes

A relatively new piece of blockchain-based software called a food monitoring system seeks to aid in the fight against fraud. In terms of utility, flexibility, and reliability, a large number of the systems now in use in the food processing industry are insufficient. This supply chain link therefore requires a lot of time because it adds more complexity. Blockchain technology offers a new concept that is crucial to resolving the previously described issues when it comes to the supply chain system that is presently being built and used.
The model presented in this abstract combines state-of-the-art advancements in blockchain machine learning (ML) with a fuzzy logic monitoring system that is layered on top of ashelf-life management system to create a blockchain- and machine learning-based food tracing system for handling perishable food. In this instance, the method would be applied to identify potentially contaminated food products. The suggested solution uses blockchain technology to help solve a number of issues, including bulk condensation loss, storage area requirements, and transit times. AI can manage the intricacy of product monitoring as data will be transferred across a network securely. Finally, the supply chain can make use of a precise and trustworthy data management chain to lengthen the entire flow of the system.

Author Contributions

Conceptualization and methodology, A.B.G., V.B.G. and M.S.B.; software, A.B.G., V.B.G. and M.S.B.; validation, A.B.G., V.B.G. and M.S.B.; formal analysis, A.B.G.; data curation, A.B.G. and V.B.G.; writing—original draft preparation, V.B.G.; writing—review and editing, M.S.B.; supervision, A.B.G., V.B.G. and M.S.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Gadicha, A.B.; Gadicha, V.B.; Burange, M.S. BMLFTS: A Novel Approach to Process and Track of Food Quality Data Using Blockchain and Machine Learning. Proceedings 2024, 105, 88. https://doi.org/10.3390/proceedings2024105088

AMA Style

Gadicha AB, Gadicha VB, Burange MS. BMLFTS: A Novel Approach to Process and Track of Food Quality Data Using Blockchain and Machine Learning. Proceedings. 2024; 105(1):88. https://doi.org/10.3390/proceedings2024105088

Chicago/Turabian Style

Gadicha, Ajay B., Vijay B. Gadicha, and Mayur S. Burange. 2024. "BMLFTS: A Novel Approach to Process and Track of Food Quality Data Using Blockchain and Machine Learning" Proceedings 105, no. 1: 88. https://doi.org/10.3390/proceedings2024105088

APA Style

Gadicha, A. B., Gadicha, V. B., & Burange, M. S. (2024). BMLFTS: A Novel Approach to Process and Track of Food Quality Data Using Blockchain and Machine Learning. Proceedings, 105(1), 88. https://doi.org/10.3390/proceedings2024105088

Article Metrics

Back to TopTop