Table 3. Compare The AI Eye gesture control with the rest in literature.

Feature/Aspect	Our Study	Study [1]	Study [2]	Study [3]	Study [4]
Objective	Eye gesture control	Hand gesture control	Voice control	Facial recognition	Multi-modal control
Methodology	Machine learning	Deep learning	Natural language processing	Deep learning	Machine learning
Technology Used	OpenCV, PyCharm, etc.	TensorFlow, Keras	Google API, Keras	TensorFlow	OpenCV, Keras
Accuracy Level	99.63%	96%	95%	97%	99%
Key Findings	Highly accurate	Moderately accurate	Accurate with clear speech	High accuracy	High accuracy
Limitations	Limited gestures	Limited to specific gestures	Ambient noise affects accuracy	Limited expressions	Complex setup
Application Field	Healthcare, defense	Gaming, VR	Accessibility, smart home	Security, accessibility	Various fields
Future Work	Expand gesture library	Improve speed of recognition	Improve noise cancellation	Enhance recognition in varying light	Multi-modal integration