Seven million people die from air pollution every year. The sensors exist. The data exists. What doesn't exist is a unified view that connects sensor networks, identifies sources, and gets health advisories to the communities breathing the worst of it.
Air pollution is the world's largest environmental health risk. An estimated 7 million premature deaths annually. The monitoring infrastructure exists: government stations, low-cost sensor networks like PurpleAir, satellite atmospheric measurements, and industrial emission tracking systems. But these networks don't talk to each other. A PurpleAir sensor three blocks from an EPA monitoring station operates in a completely separate data universe.
The result is a patchwork. Dense coverage in wealthy urban areas, almost nothing in the developing regions where pollution kills the most people. When coverage does exist, correlating air quality readings with industrial activity, traffic patterns, and weather data to identify pollution sources requires crossing three or four separate databases that use different formats, update at different intervals, and were never designed to work together.
AETHER aggregates these fragmented networks into a single coherent view. It identifies pollution sources by correlating sensor data with industrial and traffic patterns. It generates real-time health advisories for communities. It maps coverage gaps to show where new sensors would have the most impact. And it produces policy-ready reports that connect air quality data to health outcomes in a format decision-makers can actually use.
Six core functions covering the full air quality intelligence stack, from raw sensor ingestion to community health advisories.
Unifies data from OpenAQ, EPA AirNow, PurpleAir, WHO databases, and satellite atmospheric measurements into a single, continuously updated view.
Correlates air quality readings with industrial activity, traffic density, and weather patterns to pinpoint pollution sources by location and time.
Generates real-time, localized health alerts for communities based on current air quality conditions, vulnerable population data, and forecast models.
Identifies regions with insufficient monitoring relative to population density and pollution risk, recommending optimal sensor placement locations.
Produces policy-ready analysis correlating air quality trends with health outcomes, environmental regulations, and industrial activity patterns.
Detects anomalous pollution spikes in real time and traces them to probable sources, alerting relevant agencies and affected communities within minutes.
Where AETHER stands today and where it's heading next.
The scope of AETHER's monitoring network and the problem it's built to solve.
Three steps from download to running operations. No build process, no dependencies.
Grab the AETHER operator files from GitHub. Drop them into your Claude workspace at operators/aether/. No build process, no dependencies.
Set your geographic monitoring region and pollution alert thresholds. Connect local sensor feeds if available. Copy the config template and customize.
Start a conversation. AETHER runs its orientation check, connects to sensor networks, and begins processing. Air quality monitoring, source tracking, health advisories.
Download AETHER. Deploy it for your community or organization. Every sensor integration, every source identification algorithm, benefits every deployment worldwide.
← Return to The Gato Legion