Martin Malčík
Founder
Perfect-Air
Perfect-Air provides hyperlocal air quality data by combining proprietary calibration stations with satellite and other available data sources. This allows users to monitor pollution levels at the street level, enabling informed decisions to improve health and quality of life.
- Artificial Intelligence
- Data & Analytics
- Clean Technology
- Hardware
- Internet of Things
- Software Only
Updated 18 months ago
Funding
Raised to date
$957.2KRaised 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.
Funding rounds are not available yet.
Founders
Product
Problem
Existing air quality monitoring systems often lack the granularity needed to understand pollution variations within urban areas. Relying on sparse, regional sensors or coarse models, they fail to capture hyperlocal pollution hotspots and temporal fluctuations that impact individual health. This lack of precise data limits the ability of citizens and organizations to make informed decisions and take effective action to mitigate exposure.
Solution
Perfect-Air addresses this problem by deploying a network of proprietary, low-cost air quality sensors that provide real-time, street-level pollution data. These sensors are strategically placed to capture variations in air quality caused by traffic, construction, and other localized sources. The sensor data is combined with satellite imagery, weather information, and other publicly available datasets using advanced calibration and machine learning techniques. This fusion of data sources enables Perfect-Air to generate highly accurate, hyperlocal air quality maps and forecasts. Users can access this information through a mobile app or web dashboard to monitor pollution levels, plan routes, and receive personalized alerts.
Target Audience
Perfect-Air's primary customers include individuals concerned about air quality, city governments seeking to improve public health, and businesses looking to optimize operations and protect employees.
Features
- Dense network of calibrated air quality sensors providing real-time, street-level data
- Proprietary calibration algorithms that improve the accuracy of low-cost sensors
- Machine learning models that fuse sensor data with satellite imagery and weather information
- Hyperlocal air quality maps and forecasts with high spatial and temporal resolution
- Mobile app and web dashboard for accessing real-time data, historical trends, and personalized alerts
- API access for integration with smart city platforms, building management systems, and other applications