Experimental Procedure to Design a Smart Shopping Trolley for Supermarkets by Using Internet of Things (IoT) Association

This paper presents the design and development of a smart shopping trolley using Internet of Things (IoT) technology to enhance the supermarket shopping experience. The trolley is equipped with RFID sensors, weight sensors, barcode scanners, and GPS to automate item scanning, provide real-time price updates, and track trolley location. The system was tested over 30 days in a supermarket environment, and key performance metrics were recorded, including item detection speed, weight sensor accuracy, and system reliability. The trolley achieved an average item detection accuracy of 98.2%, with a reduction in checkout times by 40% compared to traditional methods. Customer feedback indicated an average satisfaction rate of 90%, with real-time updates being particularly appreciated. Error rates, including failed item detection and price calculation errors, decreased over time, demonstrating the system's capacity to self-optimize. Overall, the smart shopping trolley provides an efficient, user-friendly solution for supermarkets, improving both operational efficiency and customer experience. Future improvements will focus on refining AI-based product recommendations and integrating more advanced inventory management capabilities.

Authors

Institutions

Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icses63760.2024.10910503
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experimental Procedure to Design a Smart Shopping Trolley for Supermarkets by Using Internet of Things (IoT) Association

Nidal Ali Abbas, N.P.G. Bhavani, E. Sakthivel, Ch. Bhanu et al.
IoT and GPS-based Vehicle Safety Systems
article

Experimental Procedure to Design a Smart Shopping Trolley for Supermarkets by Using Internet of Things (IoT) Association

Nidal Ali Abbas, N.P.G. Bhavani, E. Sakthivel, Ch. Bhanu, SK. Chand Khathoon Bujji, R.V. Adkane
article en

Abstract

This paper presents the design and development of a smart shopping trolley using Internet of Things (IoT) technology to enhance the supermarket shopping experience. The trolley is equipped with RFID sensors, weight sensors, barcode scanners, and GPS to automate item scanning, provide real-time price updates, and track trolley location. The system was tested over 30 days in a supermarket environment, and key performance metrics were recorded, including item detection speed, weight sensor accuracy, and system reliability. The trolley achieved an average item detection accuracy of 98.2%, with a reduction in checkout times by 40% compared to traditional methods. Customer feedback indicated an average satisfaction rate of 90%, with real-time updates being particularly appreciated. Error rates, including failed item detection and price calculation errors, decreased over time, demonstrating the system's capacity to self-optimize. Overall, the smart shopping trolley provides an efficient, user-friendly solution for supermarkets, improving both operational efficiency and customer experience. Future improvements will focus on refining AI-based product recommendations and integrating more advanced inventory management capabilities.

Zarqa University (JO), Saveetha University (IN)
Openalex Percentile: Top 72%
IoT and GPS-based Vehicle Safety Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Experimental Procedure to Design a Smart Shopping Trolley for Supermarkets by Using Internet of Things (IoT) Association — Nidal Ali Abbas, N.P.G. Bhavani, et al. · (2024) | TGRS Research Map | TGRS