Quietaura
A smart wearable enhancing safety for the deaf with haptic feedback, sound recognition, and emergency alerts. It detects critical sounds like car horns, ensuring awareness, and real-time response.
Created on 22nd February 2025
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Quietaura
A smart wearable enhancing safety for the deaf with haptic feedback, sound recognition, and emergency alerts. It detects critical sounds like car horns, ensuring awareness, and real-time response.
The problem Quietaura solves
Our device empowers the deaf and hard-of-hearing community by making daily tasks safer and more convenient:
Alert System – Detects sounds like doorbells, fire alarms, and sirens, notifying users through vibrations or visual cues.
Communication Aid – Facilitates interaction in noisy or silent environments with real-time assistance.
Health Monitoring – Tracks vital signs and sends emergency alerts when needed.
Navigation Assistance – Provides sensory feedback for safer movement in public spaces and street crossings.
By integrating these features into a seamless wearable, we enhance independence, awareness, and overall quality of life.
Challenges we ran into
From our first prototype to the second prototype, we faced several challenges. The biggest challenge was making the device compact, as the initial version used an Arduino Uno, making it bulky. To solve this, we replaced it with the Nano 33 BLE, reducing the size by 50% and making it easier to wear.
Another challenge was power management since the Nano 33 BLE operates at 3.3V, which affected the motor driver and buzzer performance. We optimized power distribution to ensure strong vibrations without excessive battery drain.
We also faced microphone sensitivity issues when switching to 3.3V operation. To fix this, we adjusted the sound detection threshold and tested different placements for better accuracy. Additionally, the system initially picked up too much background noise, causing false alerts. We solved this by adding a delay between detections and considering future improvements with machine learning for sound classification.
By overcoming these challenges, our second prototype is now more compact, power-efficient, and reliable, bringing us closer to creating a practical assistive device for the deaf.