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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM40093

AI-Powered Retail Insights and Query System

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM40093

Volume:

8 |

12 |

Dec 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM40093

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SSUS

Siva Sakthii U S

PM

Pradeepa M

JD

Janani D

NM

Neena Murali

NM

Narmatha M

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Abstract

The dynamic retail industry demands efficient and intelligent solutions to address operational challenges and enhance customer experience. This paper presents an AI-powered system equipped with three core functionalities: (1) Retail shelf analysis using YOLOv5 to detect empty shelf spaces or identify products, (2) A text-to-query interface allowing users to upload database files and perform SQL queries using natural language, and (3) Sentiment analysis to extract valuable insights from customer feedback. The system is deployed via Streamlit and leverages CI/CD pipelines on GitHub and AWS EC2 for scalable, reliable performance. This study delves into the methodologies, implementation strategies, and the system’s transformative potential in modern retail operations.

KEYWORDS

Retail AI YOLOv5 Text-to-Query System Sentiment Analysis Machine Learning Automation

Cite This Article

Siva Sakthii U S, Pradeepa M, Janani D, Neena Murali, Narmatha M, "AI-Powered Retail Insights and Query System," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 12, Dec 2024. https://doi.org/10.55041/IJSREM40093

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Publication Date

12/24/2024

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Review Rounds: 2

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