SmartCart Project: Adding Intelligence to Shopping Carts
Resumo
The retail sector has been experiencing a transformation in which the incorporation of technologies into the shopping process is becoming increasingly common, aiming to provide a better experience for consumers. In this context, this paper seeks to propose a solution that uses embedded hardware in shopping carts to enhance the shopping experience, primarily speeding up the payment process by allowing customers to scan the barcodes of desired products without having to face long queues. It also aims to provide a supermarket map, indicating the current position of the cart. To achieve these objectives, computer vision was used to recognize QR codes attached to the ceiling. Following this methodology, satisfactory results were obtained, with paths for improvement and possible changes to be made in the project to achieve greater accuracy in estimating the cart’s location.
Palavras-chave:
Indoor localization, embedded computer vision, artificial intelligence of things
Referências
B. Chaure and P. Jain, “Development of e-shopping cart with theft control mechanism: No queue,” in 2016 International Conference on Emerging Technological Trends (ICETT). IEEE, 2016, pp. 1–5.
B. of Labor Statistics, “American time use survey news release,” 2017.
S. Gupta, A. Kaur, A. Garg, A. Verma, A. Bansal, and A. Singh, “Arduino based smart cart,” International Journal of Advanced Research in Computer Engineering & Technology, vol. 2, no. 12, 2013.
Y. Berdaliyev and A. P. James, “Rfid-cloud smart cart system,” in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2016, pp. 2346–2352.
C. M. Ramya, M. Shanmugaraj, and R. Prabakaran, “Study on zigbee technology,” in 2011 3rd international conference on electronics computer technology, vol. 6. IEEE, 2011, pp. 297–301.
A. Yewatkar, F. Inamdar, R. Singh, A. Bandal et al., “Smart cart with automatic billing, product information, product recommendation using rfid & zigbee with anti-theft,” Procedia Computer Science, vol. 79, pp. 793–800, 2016.
B. of Labor Statistics, “American time use survey news release,” 2017.
S. Gupta, A. Kaur, A. Garg, A. Verma, A. Bansal, and A. Singh, “Arduino based smart cart,” International Journal of Advanced Research in Computer Engineering & Technology, vol. 2, no. 12, 2013.
Y. Berdaliyev and A. P. James, “Rfid-cloud smart cart system,” in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2016, pp. 2346–2352.
C. M. Ramya, M. Shanmugaraj, and R. Prabakaran, “Study on zigbee technology,” in 2011 3rd international conference on electronics computer technology, vol. 6. IEEE, 2011, pp. 297–301.
A. Yewatkar, F. Inamdar, R. Singh, A. Bandal et al., “Smart cart with automatic billing, product information, product recommendation using rfid & zigbee with anti-theft,” Procedia Computer Science, vol. 79, pp. 793–800, 2016.
Publicado
18/10/2023
Como Citar
SILVA, Carlos Eduardo Bezerra Mendes; LIMA, Marcos Eduardo Araújo de; SOUZA, Thiago José Alves de; PAULA, João Pedro Mafaldo de; SILVA JÚNIOR, Marcondes Ricarte da; TEIXEIRA, João Marcelo Xavier Natário.
SmartCart Project: Adding Intelligence to Shopping Carts. In: CONGRESSO LATINO-AMERICANO DE SOFTWARE LIVRE E TECNOLOGIAS ABERTAS (LATINOWARE), 20. , 2023, Foz do Iguaçu/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 83-87.
DOI: https://doi.org/10.5753/latinoware.2023.236510.
