SilentSense

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Inspiration

City life is exciting but noisy. Traffic, construction, and neighbors constantly disrupt sleep and mental health. We wanted a solution that helps people take control of their sound environment and improve urban living.

What it does

SilentSense monitors noise levels, identifies sources, and gives personalized strategies to reduce disruption. It tracks how noise affects sleep and provides actionable insights. Users can also share anonymous data to help cities plan quieter neighborhoods.

How we built it

Smartphone app using built-in microphones for noise detection AI/ML models to classify noise sources Optional IoT sensors for more precise measurements Cloud storage for community noise mapping (optional) Integration with smart home devices for automated noise mitigation

Challenges we might run into while building

Accurately classifying diverse noise sources Ensuring user privacy while collecting community data Designing an interface that’s simple, informative, and engaging

Accomplishments we might be proud of after building

Developed a functional prototype that monitors noise in real time Built AI models that can distinguish between traffic, construction, and home noises Created a sleep correlation dashboard with actionable insights Conceptualized a community heatmap to support urban planning

What we learned

Noise classification is complex but can be approached with smart feature engineering User privacy must be prioritized even in community-driven apps Clean, intuitive design is critical for adoption and engagement

What's next for SilentSense

Expand AI to recognize more noise sources Integrate fully with smart home systems for automated responses Gamify sleep improvement and noise reduction challenge Partner with city councils to use noise data for urban planning

Built With

• english