"Voice operated assistant system for blind people Using Machine Learning"

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Prof. Dr. Neelam A. Kumar, Ms. Gitanjali Suryavanshi, Ms. Rutuja Bhawsar, Ms. Divya Talekar, Ms. Sudiksha Waghmare

Abstract

Addressing the challenges faced by the visually impaired, there is a pressing need for innovative solutions. With 250 million people experiencing vision impairment and 40 million facing blindness, daily navigation remains a significant hurdle. Existing technologies, while beneficial, often require assistance from others.


To empower individuals who are blind, the development of an integrated machine learning system is proposed. This system aims to distinguish and classify objects in real-time, offering voice feedback and distance estimation. The inclusion of a warning mechanism, triggered based on object proximity, ensures enhanced safety by alerting users to the closeness or distance of identified items. The intersection of computer vision, machine learning, and audio processing holds the key to creating a transformative technology for the visually impaired, fostering independence and accessibility in their everyday lives.

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