Silencio operates a global network that collects real-world voice and ambient audio data from millions of contributors worldwide. This diverse, ethically sourced audio data is used to train and enhance Artificial Intelligence models for speech recognition and environmental awareness. The platform provides specialized datasets, including multilingual voice commands and noise level metrics, to technology companies building advanced AI and robotics applications.
Funding
$3.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many urban areas suffer from excessive noise pollution, which can negatively impact residents' health and quality of life. Existing methods for monitoring noise levels are often limited in scope and lack the granularity needed for effective mitigation strategies.
Solution
Silencio leverages a decentralized network of smartphones to create a comprehensive, real-time noise map. The Silencio mobile application allows users to securely contribute noise level data, earning cryptocurrency rewards in exchange. This crowdsourced data is then aggregated and analyzed to provide actionable insights into noise pollution patterns across various locations. The platform enables users to identify quieter venues, report noise complaints, and contribute to smarter urban planning initiatives. By combining blockchain technology with environmental monitoring, Silencio empowers individuals to participate in building healthier and more livable cities.
Target Audience
The primary target audience includes urban residents concerned about noise pollution, real estate developers, urban planners, hospitality businesses, and researchers interested in environmental data.
Features
- Mobile application for iOS and Android platforms
- Real-time noise level tracking using smartphone microphones
- Cryptocurrency rewards ($SLC tokens) for data contributions
- Noise map visualization displaying noise levels at various locations
- Noise complaint submission and tracking functionality
- Integration with venue databases to identify quiet spaces
- Data encryption and anonymization to protect user privacy
- API access for developers to integrate noise data into other applications
- Machine learning models to enhance data accuracy and identify noise pollution hotspots