TrueLight - AI-Powered Navigation Assistant for Colorblind Users

Inspiration

After browsing r/colorblind on Reddit, we discovered countless posts from colorblind individuals sharing their struggles with everyday navigation. 300 million people worldwide are colorblind (8% of men, 0.5% of women), yet there are virtually no real-time assistive tools for safe navigation. Colorblind glasses cost $300+ and don't work for everyone. We realized the smartphone camera everyone carries could be the solution.

What it does

TrueLight provides real-time visual and audio alerts for colorblind users across all modes of transportation:

Detects objects using YOLOv3 AI (80 classes) and announces hazards
Analyzes colors with OpenCV HSV detection
Adapts to 9 vision types - protanopia, deuteranopia, tritanopia, achromatopsia, low vision, and more
Tests color vision with built-in Ishihara assessment
Tracks moving objects with animated lock-on brackets
Adjusts by activity - walking (5s), biking (3s), driving (1.5s), passenger (2s)
Prioritizes by urgency - low vision mode uses size/proximity instead of color
Natural voice - ElevenLabs TTS for human-like audio alerts
Adaptive UI - never uses colors you can't see

How we built it

Mobile (React Native + Expo)

Real-time camera processing with adaptive frame rates
Animated bounding box overlays
Zustand state management
ElevenLabs natural voice with expo-av audio playback
Ishihara color vision test

Detection (Python + FastAPI)

YOLOv3-tiny object detection (10% confidence threshold)
OpenCV HSV color analysis (30+ color shades)
Transport mode-aware thresholds
Low vision proximity-based prioritization
Always-detect fallback (YOLO → color regions)

Backend (Next.js)

API proxy between mobile and Python
ElevenLabs integration

Challenges

Color accuracy: HSV color space varies with lighting. Expanded from 7 to 30+ colors and built a fallback system that always detects something.

Real-time performance: Balancing accuracy with mobile frame rate. Transport mode-aware intervals adapt from 1.5s (driving) to 5s (walking).

Universal accessibility: Supporting 9 colorblindness types required adaptive color schemes that never use colors the user can't distinguish.

Low vision support: Realized proximity matters more than color. Built size-based prioritization where objects >10% of frame trigger urgent alerts.

ElevenLabs audio playback: MP3 streaming from API required expo-av integration with proper audio session management and cleanup.

Accomplishments

Complete end-to-end ML pipeline with mobile app, proxy, and detection service
30+ color detection including subtle shades (browns, violets, teal, rust, olive)
Transport-aware sensitivity adapting to user activity
Low vision proximity alerts with directional cues
ElevenLabs natural voice fully integrated with audio playback
Ishihara test with manual override
Animated targeting brackets tracking moving objects

What we learned

Colorblind community is underserved - most solutions are expensive glasses, not accessible software
HSV color space >>> RGB for color classification in varied lighting
Real-time mobile ML is achievable with YOLOv3-tiny at 10% confidence
Low vision users need proximity/urgency over color-based prioritization
"Always detect something" philosophy ensures continuous feedback