Paper Key : IRJ************916
Author: Kajal Thote,Namrata Khade ,Ayush Zare,Chandan Kohad,Chanchal Lende,Apurva Lohakpure
Date Published: 05 Apr 2025
Abstract
Automated retail trolleys are transforming the shopping experience by integrating advanced technologies like AI, IoT, RFID, and machine learning. This study examines how AI-driven personalization and autonomous billing improve efficiency while tackling challenges in sensor-based navigation and energy consumption. Using a prototype approach, we developed a smart trolley powered by Raspberry Pi and Arduino, incorporating RFID, LiDAR, and computer vision sensors. The system is designed to enhance navigation, provide real-time shopping recommendations, and streamline the checkout process. Experimental results show a 30% increase in customer engagement due to AI recommendations, a 50% reduction in checkout time, and 95% accuracy in obstacle avoidance. However, issues like sensor calibration and cloud connectivity disruptions were noted. Overall, our findings suggest that automated trolleys can significantly enhance retail efficiency and customer satisfaction. Future research should focus on large-scale deployment, improving machine learning algorithms, and developing sustainable power solutions to further optimize performance and adoption.
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