Authors : Sai Sharad Gaikar; Dhanish Santosh Ghag; Shubham Santosh Balde; Mrunmayee M. Hatiskar

Volume/Issue : Volume 11 - 2026, Issue 3 - March

---

Google Scholar : https://tinyurl.com/25hmwksa

Scribd : https://tinyurl.com/466czrfw

DOI : https://doi.org/10.38124/ijisrt/26mar1563

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

---

Abstract : The beauty and wellness industry is really taking to solutions to make things better for customers and to make things run more smoothly. Aura Connect is a system for beauty parlors that works on lots of platforms. It was made using MongoDB to make salon services more modern. The system is easy to use and it talks to a MongoDB database to store information in a flexible way. Aura Connect tries to make things better for clients by automating schedules and suggesting products that're relevant to them. This should make it so people do not have to wait long. They are happier with the service. When we first tried it out it seemed to make a difference, in how well appointments were booked and how much customers were engaged compared to the old way of doing things.

Keywords : Beauty Salon, Appointment Scheduling, MongoDB, Product Recommendations, Online Booking, User Interface.

References :

1. T. B. Samudra and A. Anggara, “Implementation of Android-Based Salon Booking Application for Customer Service Optimization,” International Journal of Software Engineering and Computer Science (IJSECS), vol. 4, no. 3, pp. 1056–1065, 2024.
2. A. W. Ningrum and R. H. P. Sejati, “Revolutionizing Salon Services: A Comprehensive Study on the Development of a Salon Reservation Application,” International Journal of Computer Applications, vol. 185, no. 44, pp. 34–39, 2023.
3. S. W. Khin and H. H. Yee, “Beauty Salon Appointment System,” University Journal of Student Projects and Research, vol. 2, pp. 1–4, 2025.
4. L. M. I. T. Hemantha, T. M. E. Gayathri, and N. N. M. De Silva, “Personalized Smart Skincare Product Recommendation System,” International Journal of Computer Applications, vol. 184, no. 41, pp. 1–6, 2022.
5. N. Vedula, M. Collins, E. Agichtein, and O. Rokhlenko, “Generating Explainable Product Comparisons for Online Shopping,” Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2023, pp. 202–210.
6. M. Rathore and S. S. Bagui, “MongoDB: Meeting the Dynamic Needs of Modern Applications,” Encyclopedia, vol. 4, no. 4, pp. 1433–1453, 2024.
7. A. Santhosh et al., “Cross-Platform Innovation: The Rise and Impact of Flutter in Modern App Development,” International Research Journal on Advanced Engineering and Management, vol. 2, no. 12, pp. 3560–3569, 2024.