DR ASTAN: Data Report AI-Powered Shopper Tracking & Analysis Network

DR ASTAN: Data Report AI-Powered Shopper Tracking & Analysis Network

Meera Sawalkar, Gaurav Pandit, Prajwal Nivangune, Aryan Tikle, Anushka Yeole, Hemani Wankhedkar

1Meera Sawalkar, Computer Department, JSPM NTC

2Gaurav Pandit, Computer Department, JSPM NTC

3Prajwal Nivangune, Computer Department, JSPM NTC

4Aryan Tikle, Computer Department, JSPM NTC

5Anushka Yeole, Computer Department, JSPM NTC

6Hemani Wankhedkar, Computer Department, JSPM NTC

Abstract - This research paper introduces Dr. ASTAN, an advanced system for monitoring, analyzing, and visualizing shopper behavior in retail environments using state-of-the-art computer vision and deep learning techniques. The system integrates multi-camera inputs and leverages YOLOv8 for real-time object detection, coupled with DeepSORT and the Kalman Filter for accurate multi-object tracking across predefined store zones. Behavioral data is processed using Pandas and visualized through Power BI, generating actionable insights into foot traffic patterns, zone-wise engagement, and consumer movement trajectories. Dr. ASTAN enables data-driven decision-making to optimize store layouts, improve customer experience, and increase sales, all while adhering to strict privacy standards and ethical data handling practices.

Key Words: DR. ASTAN, deep learning, YOLOv8, DeepSORT, Kalman Filter, consumer behavior, retail analytics, computer vision, zone-based analysis