Vol. 5 No. 2 (2026): April
RESEARCH ARTICLES

EYEFIT: Integrating Virtual Try-On, Online Eye Testing, and Prescription Management for Smart Eyewear Services

DOWNLOAD PDF
  • R Tamil Selvi,
  • Balaganesh G,
  • Mathurin Nesta M,
  • Partha Sarathy R,
  • Sutharshan C
R Tamil Selvi
Department of Computer Science and Design, SNS College of Technology, Coimbatore, Tamil Nadu, India.
Balaganesh G
Department of Computer Science and Design, SNS College of Engineering, Coimbatore, Tamil Nadu, India
Mathurin Nesta M
Department of Computer Science and Design, SNS College of Engineering, Coimbatore, Tamil Nadu, India
Partha Sarathy R
Department of Computer Science and Design, SNS College of Engineering, Coimbatore, Tamil Nadu, India
Sutharshan C
Department of Computer Science and Design, SNS College of Engineering, Coimbatore, Tamil Nadu, India
DOI: https://doi.org/10.5281/zenodo.18497429

Published 2026-02-05

Keywords

  • eyewear Platform,
  • Virtual Try-On,
  • Artificial Intelligence,
  • Augmented Reality,
  • Home Eye Testing

How to Cite

R Tamil Selvi, Balaganesh G, Mathurin Nesta M, Partha Sarathy R, & Sutharshan C. (2026). EYEFIT: Integrating Virtual Try-On, Online Eye Testing, and Prescription Management for Smart Eyewear Services. International Journal of Computational Learning & Intelligence, 5(2), 989–995. https://doi.org/10.5281/zenodo.18497429

Copyright (c) 2026 R Tamil Selvi, Balaganesh G, Mathurin Nesta M, Partha Sarathy R, Sutharshan C

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Abstract

The eyewear industry is essential for eye health and style, but traditional purchasing methods are inefficient. Consumers face issues like limited variety, high costs, inability to try frames easily, and limited access to eye tests, especially in rural areas. This leads to delays and dissatisfaction. To solve this, we propose EYEFIT, an all-in-one digital platform integrating online and offline services. It allows users to browse frames, use virtual try-on (VTO) with AI and AR for personalized recommendations based on face shape, preferences, and budget. Features include home eye tests by professionals, digital prescription management, secure payments, and home delivery. This innovation merges technology, healthcare, and fashion for convenience, affordability, and accessibility, empowering users to make informed decisions from home.
DOWNLOAD PDF

References

  1. Ganitha Aarthi, N. G., Joel Hygin, M., & Max, J. (2025). Enhanced real-time collaborative diagramming platform MELON. European Alliance for Innovation (EAI).
  2. Asharaf, T. (2024). Exploring the potential of big data and machine learning for superior analysis and personalization of customer behavior.
  3. Asharaf, T., Mathew, A. K., Simman, R., Santhosh, S., Sruthi, S., & Dharshini, Y. S. (2025). Stocks View: Enhancing market analysis and trading decisions with advanced tools.
  4. Valivarthi, D. T., Kethu, S. S., Natarajan, D. R., Narla, S., Peddi, S., & Kurunthachalam, A. (2025). Enhanced Medical Anomaly Detection Using Particle Swarm Optimization-based Hybrid MLP-LSTM Model. International Journal of Pattern Recognition and Artificial Intelligence. https://doi.org/10.1142/s0218001425570228.
  5. Optimizing Task Offloading in Vehicular Network (OTO): A Game Theory Approach Integrating Hybrid Edge and Cloud Computing. (2025). Journal of Cybersecurity and Information Management, 15(1). https://doi.org/10.54216/jcim.150110.
  6. Vallu, V. R., Pulakhandam, W., Kurunthachalam, A., & Hugar, S. (2025). PR-MICA and SGELNN: A Unified Framework for Feature Extraction in Graph Learning. 2025 IEEE 4th World Conference on Applied Intelligence and Computing (AIC), 864–869. https://doi.org/10.1109/aic66080.2025.11211928.
  7. Rao, V. V., Jagathpally, A., Pulakhandam, W., Shahwar, T., & Kurunthachalam, A. (2025). A Vision Transformers Approach for Surgical Monitoring with Algorithmic Framework and Experimental Evaluation. 2025 International Conference on Biomedical Engineering and Sustainable Healthcare (ICBMESH), 1–6. https://doi.org/10.1109/icbmesh66209.2025.11182237.
  8. Jadon, R., Budda, R., Gollapalli, V. S. T., Chauhan, G. S., Srinivasan, K., & Kurunthachalam, A. (2025). Grasp Pose Detection and Feature Extraction Using FHK-GPD and Global Average Pooling in Robotic Pick-and-Place Systems. 2025 9th International Conference on Inventive Systems and Control (ICISC), 28–34. https://doi.org/10.1109/icisc65841.2025.11188246.
  9. Vallu, V. R., Pulakhandam, W., & Kurunthachalam, A. (2025). Revolutionizing Mobile Cloud Security: Employing Secure Multi-Party Computation and Blockchain Innovations for E-Commerce Platforms. 2025 International Conference on Artificial Intelligence and Emerging Technologies (ICAIET), 1–6. https://doi.org/10.1109/icaiet65052.2025.11211015.
  10. Vallu, V. R., Pulakhandam, W., Jagathpally, A., Shahwar, T., & Kurunthachalam, A. (2025). Object Recognition and Collision Avoidance in Robotic Systems Using YOLO and HS-CLAHE Techniques. 2025 5th International Conference on Intelligent Technologies (CONIT), 1–6. https://doi.org/10.1109/conit65521.2025.11166833.
  11. Jadon, R., Budda, R., Gollapalli, V. S. T., Singh Chauhan, G., Srinivasan, K., & Kurunthachalam, A. (2025). Innovative Cloud-Based E-Commerce Fraud Prevention Using GAN-FS, Fuzzy-Rough Clustering, Smart Contracts, and Game-Theoretic Models. 2025 International Conference on Computing Technologies &Amp; Data Communication (ICCTDC), 1–6. https://doi.org/10.1109/icctdc64446.2025.11158048.
  12. Gayathri, R., Sheela Sobana Rani, K., & Aravindhan, K. (2024). Classification of Speech Signal Using CNN-LSTM. Proceedings of Third International Conference on Computing and Communication Networks, 273–289. https://doi.org/10.1007/978-981-97-2671-4_21.
  13. Pasha, A., ur Rahman, S. Z., Tauheed, S., Basha, S. M., & Anwar, B. H. (2024). Comparative Analysis of Ranking Machine Learning Classifier Models for Parkinson's Disease (PD) Prediction. In Disruptive Technologies for Sustainable Development (pp. 237-241). CRC Press.
  14. Ahmed, S. T., Venkatesan, V. K., & Venkatesan, M. (2024). Augmented Intelligence Based COVID-19 Diagnostics and Deep Feature Categorization Based on Federated Learning. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(5), 3308-3315.
  15. Bhavatarini, N., Ahmed, S. T., & Basha, S. M. (2024). Reinforcement learning-principles, concepts and applications. MileStone Research Publications.
  16. Seetharaman, S. K., & Syed, T. A. (2025). An Automated Medical Diagnosis System for Neoplasm Medical (MRI) Image Classification using Supervised and Unsupervised Techniques.