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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM38535
Volume:
8 |
11 |
Nov 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
This research article introduces Dr. ASTAN, an innovative system that uses multi-camera inputs to follow and evaluate shopper movements in a retail environment. Dr. ASTAN uses deep learning models, especially YOLOv5mu for object recognition and DeepSORT for real-time multi-object tracking in several zones. The objective of the system is to map consumer behavior, generate actionable insights, and visualize trends using Pandas and Power BI. The results offer retailers a comprehensive view of foot traffic, zone engagement, and consumer behavior patterns, enabling data-driven decision-making to enhance sales and customer experience.
KEYWORDS
Publication Date
10/10/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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