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“Enabling Ternary Hash Tree based Integrity Verification for Secure Cloud Data Storage” has been added to your cart. View cart
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Home Projects Java Assisted Vision: a Transformative Web App for the Visually Impaired
RoundImage Towards Secure Graphical Password Authentication via Rounded Image Selection in IoT
RoundImage Towards Secure Graphical Password Authentication via Rounded Image Selection in IoT ₹5,500.00
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Transchain: Blockchain-Based Management of Allografts for Enhancing Data Provenance
Transchain: Blockchain-Based Management of Allografts for Enhancing Data Provenance ₹5,500.00

Assisted Vision: a Transformative Web App for the Visually Impaired

₹5,500.00

Aim:

           The primary aim of this project is to detect, monitor, and provide mental health support for pregnant women by analyzing free conversational speech in naturalistic settings. The system leverages cloud-based communication, AI-driven audio analysis, and human–AI hybrid interaction to screen for depression and anxiety while providing emotional support through chat and voice-based systems.

 

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Categories: Java, Social Cause Tags: Java Projects, Lidar, Social Cause
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Description

Aim:

           The primary aim of this project is to detect, monitor, and provide mental health support for pregnant women by analyzing free conversational speech in naturalistic settings. The system leverages cloud-based communication, AI-driven audio analysis, and human–AI hybrid interaction to screen for depression and anxiety while providing emotional support through chat and voice-based systems.

Abstract:

         Visually impaired individuals face significant challenges in mobility, object recognition, reading printed content, and identifying essential information such as expiry dates on products. Traditional tools like white canes or guide dogs provide only limited support and lack contextual awareness. With over 285 million people worldwide experiencing visual impairment (WHO), there is a growing demand for intelligent assistive technologies.

         This project proposes an AI-powered smartphone-based system that integrates real-time Computer Vision (CV), Machine Learning (ML), Optical Character Recognition (OCR), and Text-to-Speech (TTS) to assist visually impaired users. The system detects obstacles, identifies objects, reads printed text, and scans product labels to extract expiry dates through image processing and OCR. Designed for real-time offline usage, the application offers voice-based guidance, improves safety, and enhances independent navigation in complex environments

Proposed System:

         The proposed system is a smartphone-based AI assistive tool that integrates real-time computer vision and speech output to guide visually impaired users. Key features include:Real-time object detection using MobileNet. Obstacle detection & distance estimation for safe navigation.OCR (Optical Character Recognition) to read printed or handwritten text aloud.Scene understanding, identifying objects like people, vehicles, doors, traffic lights, etc.Voice-guided assistance for navigation and environmental alerts. On-device processing (no need for constant internet), ensuring speed and privacy.User-friendly interface with minimal touch interaction.This system bridges the gap between limited traditional tools and advanced AI capabilities, providing actionable information that improves mobility and independence.

Advantages:

  • Real-time assistance with fast object detection and alerts
  • Cost-effective, using only a smartphone—no additional hardware required
  • Enhances safety by alerting users about obstacles and moving objects
  • Works offline using on-device ML models
  • Improves independence by enabling navigation without external support
  • Multi-functional (object detection, OCR, navigation) in a single app
  • Voice-based interaction reduces need for physical touch
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