Built for Rigorous Science
We develop scalable, high-resolution air quality and environmental monitoring solutions intended to support atmospheric physics and translational health research.
Built for Rigorous Science
Academic research requires more than raw data; it requires defensible accuracy and ease of use. WeatherSens supports research programs to capture local observations and works to produce validation-grade datasets through careful QA/QC and colocation exercises. We work to provide the data always in the right format for your research.
With typical prototype performance already at: ~±0.5°C, ~±3% RH, ~±10% PM, we can produce quality data at scale. WeatherSens Sentry-I is engineered for easy large scale distribution while maintaining accuracy.
Track exact exposure levels in specific neighborhoods, capturing spatial variability that broad municipal networks miss. Our networks ensure data integrity and consistency across diverse environments.
High-frequency sampling with flexible data output via API and web UI in multiple formats (JSON, netCDF, etc.). We prioritise metadata discipline to make datasets research-ready for assimilation and analysis.
Solutions by Research Domain
Deploy dense mesonets for urban and regional climate monitoring, multi-pollutant observation, and microclimate studies. Capture spatial variability that broad municipal networks miss.
Provide observational datasets to support model evaluation, downscaling and ML workflows. Get data at the level that matters for your model or enforce your areal average estimations.
Provide higher-resolution exposure data to help studies linking environmental stressors and health outcomes. Colocated deployments help quantify local exposure variability for epidemiological analysis.
As a Finnish technology SME, we can join grant consortia as a dedicated hardware and data partner—providing sensing architecture and operational support to research-led proposals.
Applications
Partner with us
We are always looking for new partnerships to advance environmental research.