Published December 19, 2023 | Version v1
Journal article Open

STORIO - Automated Store Solutions

Description

Shopping is a ubiquitous activity that plays a vital role in our daily lives. It provides a means for consumers to acquire the products and services they need or desire, and it is a key component of the global economy. However, the traditional method of shopping can be time-consuming and stressful, with long queues and limited assistance for customers.

To address these challenges, we propose a novel system that aims to enhance the shopping experience for both customers and retailers. Our system offers a range of features that assist customers in shopping for products, making payments, and receiving personalized recommendations. Additionally, it provides store owners with advanced capabilities for inventory management, sales projection, and supplier notification.

Our system is designed to be user-friendly and intuitive, with a simple and intuitive interface that can be easily accessed through mobile devices or in-store kiosks. It leverages the latest technologies, including machine learning and data analytics, to provide customers with personalized recommendations based on their shopping history and preferences. It also enables retailers to optimize their inventory management and sales strategies, leading to increased profitability and customer satisfaction.

In summary, our proposed system offers a comprehensive solution to the challenges of traditional shopping, providing a more efficient, convenient, and personalized shopping experience for customers while enabling retailers to improve their operations and profitability.

 

Files

STORIO - Automated Store Solutions -Formatted Paper.pdf

Files (569.3 kB)

Additional details

References

  • 1. Sarala, T., Sudha, Y. A., Sindhu, K. V., Suryakiran, C. H., & Nithin, B. N. (2018, May). Smart electronic trolley for shopping mall. In 2018 3rd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT) (pp. 2422-2427). IEEE..
  • 2. Xu, J., Hu, Z., Zou, Z., Zou, J., Hu, X., Liu, L., & Zheng, L. (2020). Design of smart unstaffed retail shop based on IoT and artificial intelligence. IEEE Access, 8, 147728-147737..
  • 3. Polacco, A., & Backes, K. (2018). The amazon go concept: Implications, applications, and sustainability. Journal of Business and Management, 24(1), 79-92..
  • 4. AiFi, AiFi - Autonomous Retail Solutions," https://aifi.com/, 2019.
  • 5. Das, T. K., Tripathy, A. K., & Srinivasan, K. (2020, July). A Smart Trolley for Smart Shopping. In 2020 International Conference on System, Computation, Automation and Networking (ICSCAN) (pp. 1-5)IEEE..
  • 6. Nath, B., Reynolds, F., & Want, R. (2006). RFID technology and applications. IEEE Pervasive computing, 5(1), 22-24..
  • 7. Leong, K. S., Ng, M. L., Grasso, A. R., & Cole, P. H. (2006, January). Synchronization of RFID readers for dense RFID reader environments. In International Symposium on Applications and the Internet Workshops (SAINTW'06) (pp. 4-pp). IEEE.
  • 8. Rao, K. S., Nikitin, P. V., & Lam, S. F. (2005). Antenna design for UHF RFID tags: A review and a practical application. IEEE Transactions on antennas and propagation, 53(12), 3870-3876.
  • 9. Vogt, H. (2002, August). Efficient object identification with passive RFID tags. In International Conference on Pervasive Computing (pp. 98-113). Berlin, Heidelberg: Springer Berlin Heidelberg..
  • 10. Fatonah, S., Yulandari, A., & Wibowo, F. W. (2018, December). A review of e-payment system in e-commerce. In Journal of Physics: Conference Series (Vol. 1140, No. 1, p. 012033). IOP Publishing..