A Smart Shopping Cart for Automated Billing and Personalized Recommendations

This study presents a Smart Shopping Cart system integrating QR code technology with a Flutter-based mobile application to enhance the traditional retail experience in Nepal. The system employs QR codes for cart identification and product tracking, synchronized with a Firebase database in real time. A tablet-mounted application provides instant cart updates and personalized product recommendations using an item-based content filtering algorithm. By supporting online payments, it reduces checkout times and manual interventions. Testing over 50 cycles with 100 products and 20 users achieved an 85% recommendation accuracy and a 640.8 ms registration time, confirming efficiency. Tailored for Nepal’s retail challenges, this scalable solution bridges physical and digital shopping, improving customer convenience and operational performance.

Authors

Institutions

Publication Details

Journal
International Journal on Engineering Technology
Published
2025-05-19
DOI
https://doi.org/10.3126/injet.v2i2.78598
Primary Topic
Transportation and Mobility Innovations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Smart Shopping Cart for Automated Billing and Personalized Recommendations

Suman Pokhrel, Ankit Rai, Gagan Pradhan, Manoj Khati et al.
International Journal on Engineering Technology
Transportation and Mobility Innovations
article

A Smart Shopping Cart for Automated Billing and Personalized Recommendations

Suman Pokhrel, Ankit Rai, Gagan Pradhan, Manoj Khati, Shiva Raj Luitel
article en

Abstract

This study presents a Smart Shopping Cart system integrating QR code technology with a Flutter-based mobile application to enhance the traditional retail experience in Nepal. The system employs QR codes for cart identification and product tracking, synchronized with a Firebase database in real time. A tablet-mounted application provides instant cart updates and personalized product recommendations using an item-based content filtering algorithm. By supporting online payments, it reduces checkout times and manual interventions. Testing over 50 cycles with 100 products and 20 users achieved an 85% recommendation accuracy and a 640.8 ms registration time, confirming efficiency. Tailored for Nepal’s retail challenges, this scalable solution bridges physical and digital shopping, improving customer convenience and operational performance.

International Journal on Engineering TechnologyVol. 2(2)
Himalayan Rescue Association (NP)
Openalex Percentile: Top 89%
Transportation and Mobility Innovations
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.