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ZENODO
Article . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
ZENODO
Article . 2026
License: CC BY
Data sources: Datacite
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Smart Vision Care System Using Ai Based Eye Activity Recognition Air Blower Control

Authors: Mrs. A.K. Nivedha M.E.; S.Pappathi; J. Priyadharshini; K.Sivapriya; B. Subasini;

Smart Vision Care System Using Ai Based Eye Activity Recognition Air Blower Control

Abstract

The rapid increase in digital device usage has led to significant eye-related problems such as eye strain, dryness, and reduced blinking rate. Continuous exposure to screens without proper eye care can negatively impact human vision and overall health. To address this issue, this project proposes an AI-based Smart Vision Care System that monitors eye activity in real time and provides automatic relief mechanisms. The proposed system utilizes a camera to continuously capture the user\\\'s eye movements and applies image processing techniques using artificial intelligence to detect eye states such as blinking frequency and eye closure duration. By analyzing these parameters, the system can identify signs of eye fatigue or strain. When abnormal eye activity is detected, the system automatically activates an air blower to provide cooling and relaxation to the eyes without requiring any manual intervention. The system is developed using software tools such as Python and OpenCV for eye detection and recognition, along with hardware components including a microcontroller, camera module, and air blower. This integration of AI and embedded systems ensures accurate monitoring and timely response. The main objective of this project is to reduce eye strain, improve user comfort, and promote healthy screen usage habits. The proposed system is cost-effective, efficient, and suitable for students and professionals who spend long hours in front of digital devices. In the future, the system can be enhanced by integrating alert notifications and mobile applications for better user interaction and monitoring.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green