Breeze Technologies develops compact air quality sensors that use cloud and AI technology to collect data in real time, creating hyperlocal maps to better understand and improve air quality.Learn about Breeze Technologies
Air pollution is the single biggest environmental health threat today, killing 7 million people and costing the world economy 5 trillion USD per year. Air quality data can only come from a limited supply of measurement stations, which are bulky, limited in scope, and usually unable to transmit data in real time. Extracting insights from these public data sources is challenging due to the high cost of equipment, inability to analyze data among stakeholders, and limited context on data interpretation.
Breeze Technologies deploys its own low-cost air quality sensors that detect all common air pollutants. Sensors gather air quality data in real time and send it to Microsoft Azure where AI and trained machine learning algorithms generate hyperlocal air quality maps. Using cloud calibration technology, the sensors recalibrate every 30 seconds to produce highly accurate data. Using the localized maps, air quality challenges are then matched with a catalog of more than 3,500 clean air actions. AI recommends the most efficient interventions, potentially raising the effectiveness of clean air action plans tenfold.
Managing and improving air quality
Breeze Technologies works with corporate partners and citizen scientists to gather data about air quality at the hyperlocal level. They can then share that data with cities, building managers, and citizens to help understand and improve air quality, inside and outside.
How Breeze Technologies work
Sensors collect air quality data in real time. Data is sent to Azure, where adaptive calibration removes external influences like humidity or temperature fluctuations and sensor drift. Azure AI matches data to its location to create hyperlocal air quality maps. AI then makes clear-air recommendations, helping communities mitigate air pollution.
How Breeze Technologies uses Azure
- Azure Cosmos DB to store configuration files and settings
- Azure Database for MySQL to store sensor data
- Azure Machine Learning Service & Studio for data science development and testing
- Azure Container Registry for private Docker container registry
- Azure Container Instances to run user-facing and backend apps
- Azure Functions for sensor data reception, calibration, processing, and aggregation
- Azure Blob, Table, and Queue Storage to store city land register data