Get a new view into the potential scope of contamination with EnviMetric by using machine learning to rapidly compare a site against a database of thousands of projects.
- Make data-driven decisions with a statistical model that assesses the probability that a contaminant reached a certain distribution.
- Equip your PM’s with thousands of data points across hundreds of sites, a level of experience that’s impossible without data science.
- Focus groundwater and soil sampling on the areas that provide the most valuable information, leading to faster, more cost-effective cleanups.
Case Study: Jadco-Hughes
An EnviMetric analysis was conducted after the third five-year review (FYR) on the Jadco-Hughes Facility (JCF), the site, using a subset of data matching the Appalachian Highlands physiographic province and eco-region. The EnviMetric contaminant dispersion model captured 100% of the plan view contamination extent as presented in the EPA’s 3rd FYR. If the EnviMetric model had been used to aid in the site characterization process, it would have suggested the need for further site investigation downgradient, significantly reducing costs.
Funded by the National Science Foundation
Funding behind EnviMetric is provided by the National Science Foundation as part of a series of grants provided to organizations exploring innovative research and technology solutions.
About Azimuth1
Azimuth1 is a lean data science and development firm with a portfolio of products dedicated to increasing public safety through geospatial analysis. We operate at the intersection of quantitative analysis, programming, and industry expertise in public safety and environmental engineering. The result is a best-in-class solution for police officers, emergency responders, and environmental project managers that uses data science and real-world experience to fuel better decision making.
Building software for environmental professionals and public safety