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International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
B. The system identified several cases with restricted Future enhancements could involve refining the algorithms
visual fields, suggesting possible glaucoma. for greater precision, expanding the dataset to include a
broader range of eye conditions, and integrating the system
5. Visual Acuity Test
with advanced machine learning models for improved
A. The system performed well in detecting reduced visual
adaptability. With these improvements, the system could
sharpness.
become an indispensable tool for early diagnosis and
B. It successfully identified common refractive errors like
proactive management of eye diseases on a larger scale.
myopia, hyperopia, and astigmatism.
VIII. FUTURE SCOPE
6. Contrast Sensitivity Test Future improvements could focus on expanding the range of
A. The system demonstrated strong sensitivity to changes eye conditions detected by the system, refining the
in brightness and contrast. algorithms for greater accuracy, and expanding the dataset
B. Abnormalities were noted in a few cases, pointing to include more diverse patient profiles. Additionally,
toward cataracts or retinal issues.
integrating the system with mobile or portable devices could
VII. CONCLUSION further increase its accessibility, making it even more
This study presents a novel approach to the early detection effective for use in rural or underprivileged regions.
of eye disorders using Smart Vision technology integrated REFERENCES
with eye-tracking systems. The system demonstrated a high [1] Risk of cataract and glaucoma among older persons
accuracy rate (92.8%) in diagnosing common eye conditions with diabetes in India: a cross-sectional study based
such as glaucoma, cataracts, and diabetic retinopathy. The on LASI Wave-1 (07, 2023).
non-invasive, real-time nature of the system makes it a
promising tool for early diagnosis, particularly in areas with [2] Prevalence of Diabetic Retinopathy in Urban India:
limited access to advanced healthcare. The Chennai Urban Rural Epidemiology Study
(CURES) Eye Study (04, 2010).
The results suggest that eye-tracking technology, when
combined with machine learning algorithms, can provide a [3] The prevalence and risk factors for cataract in rural
valuable diagnostic tool for ophthalmologists and healthcare and urban India (03, 2019).
providers, enabling them to detect eye diseases earlier and [4] OpenCV Eye Tracking: Step-By-Step With Code by
intervene before irreversible damage occurs.
Amit Yadav (12, 2024).
The project's impact lies in its ability to facilitate early [5]
disease detection without requiring invasive procedures or The Effect of Cataract on Eye Movement Perimetry by
T. J. L. Mezer, D Tzur-Peled, H M. Dahan, M T. Kiss, D.
high-cost equipment, potentially reducing the long-term
G. Niv (2015).
impact of preventable blindness. This approach offers a cost-
effective and scalable solution for improving eye health [6] Eye Movement Abnormalities in Glaucoma Patients: A
outcomes, particularly in underserved communities. Review by McDonald et al (2020).

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