Eco-Eye: Object Detection System for Blind People

Visually impaired individuals face significant challenges when it comes to navigating their environment. This project presents a cost-effective and efficient solution for improving mobility through a smart navigation system designed for the visually impaired. Utilizing Raspberry Pi, a camera, and advanced object detection techniques, the system eliminates the need for traditional ultrasonic sensors. By incorporating computer vision, object detection algorithms, and text-to-speech (TTS), the system identifies objects and provides real-time feedback via audio. Furthermore, the system includes an emergency alert feature that allows the user to press a dedicated button to send an email to a guardian, containing their location and a picture of the surroundings. This solution aims to enhance mobility, safety, and independence for visually impaired individuals, while being simple, scalable, and user-friendly. The system is also designed to be affordable and accessible, with future potential for more complex features such as obstacle classification, path guidance, and AI-based personalized navigation.

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Publication Details

Journal
International Journal of Advanced Research in Science Communication and Technology
Published
2025-04-03
DOI
https://doi.org/10.48175/ijarsct-24834
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Eco-Eye: Object Detection System for Blind People

Ajay Singh Raghuvanshi, Prof. Dipali Mane, Rahul Kolhe, Mohit Patil et al.
International Journal of Advanced Research in Science Communication and Technology
Video Surveillance and Tracking Methods
article

Eco-Eye: Object Detection System for Blind People

Ajay Singh Raghuvanshi, Prof. Dipali Mane, Rahul Kolhe, Mohit Patil, Vaishnavi Bharambe
article en

Abstract

Visually impaired individuals face significant challenges when it comes to navigating their environment. This project presents a cost-effective and efficient solution for improving mobility through a smart navigation system designed for the visually impaired. Utilizing Raspberry Pi, a camera, and advanced object detection techniques, the system eliminates the need for traditional ultrasonic sensors. By incorporating computer vision, object detection algorithms, and text-to-speech (TTS), the system identifies objects and provides real-time feedback via audio. Furthermore, the system includes an emergency alert feature that allows the user to press a dedicated button to send an email to a guardian, containing their location and a picture of the surroundings. This solution aims to enhance mobility, safety, and independence for visually impaired individuals, while being simple, scalable, and user-friendly. The system is also designed to be affordable and accessible, with future potential for more complex features such as obstacle classification, path guidance, and AI-based personalized navigation.

International Journal of Advanced Research in Science Communication and Technology
Abasaheb Garware College (IN)
Openalex Percentile: Top 95%
Video Surveillance and Tracking Methods
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