SmartVision
Blind Navigation System
Raspberry Pi Ultrasonic Sensor Computer Vision GPS Module Haptic Feedback <50ms Response
System Components
🖥️
RASPBERRY PI
Central processing unit
📡
ULTRASONIC
40kHz obstacle detection
📷
CAMERA
30fps visual input
🛰️
GPS MODULE
Location & navigation
🔊
SPEAKER
Audio alert output
📳
HAPTIC MOTOR
Vibration feedback
System Architecture
ULTRASONIC 40kHz pulses CAMERA 30fps stream GPS Location data RASPBERRY PI 4 OpenCV · Python · GPIO SPEAKER Audio alerts HAPTIC MOTOR Vibration patterns NAVIGATION Route guidance SENSORS PROCESS OUTPUT
Live Detection Demo
walking path
🪑
CHAIR
0.8m
🚪
DOOR
1.5m
📦
BOX
CLEARED
⚠ OBSTACLE AHEAD · 0.8m · LEFT TURN
40kHz 30fps <50ms
Signal Processing Pipeline
SENSOR
INPUT
40kHz · 30fps
ADC
CONVERT
GPIO pins
CV
PROCESS
OpenCV
AI
CLASSIFY
TFLite model
ALERT
OUTPUT
Audio + Haptic
GPS
PARSE
NMEA data
ROUTE
CALC
OSM API
TURN-BY
TURN
TTS engine
MERGE
LAYER
Priority queue
SPEAKER
OUT
PWM audio
End-to-end latency
<50ms
System Summary
SmartVision · Blind Navigation System
🧠
PROCESSING CORE
Raspberry Pi 4 running Python + OpenCV for real-time vision processing and sensor fusion.
Quad-core ARM
📡
OBSTACLE DETECTION
Dual-mode sensing with 40kHz ultrasonic waves and 30fps camera stream for full coverage.
40kHz · 30fps
🛰️
NAVIGATION
GPS-based turn-by-turn routing with OpenStreetMap integration and TTS voice guidance.
±2m accuracy
⚡
RESPONSE TIME
Full sensor-to-alert pipeline completes in under 50ms — faster than human reaction time.
<50ms latency
🔊
MULTIMODAL OUTPUT
Layered alerts via audio speaker and haptic vibration motor with priority-based queueing.
Audio + Haptic
🤖
AI CLASSIFICATION
TFLite on-device model classifies obstacle types — chair, door, person, vehicle — in real time.
TFLite · On-device
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