Leveraging the power of geo based artificial intelligence, to have a better and cleaner world.

In-Situ Environmental Products

The environment is critical to our future. A clean environment is good for our health and our businesses. Kumi Analytics is dedicated to using our technology to help people and businesses better understand, and take care of, the world around them. From healthy oceans to clean land, we need to all work together to maintain an environment that enables us to have healthy productive lives for generations to come.

In-Situ Coral Reef Monitoring

Detect coral reef bleaching, destruction and/or growth. Track coral reef bleaching, reef destruction and redevelopment. Multiple methods for the identification of coral reef health provide the signals necessary to automatically identify and report on the health of coral reef structures – the foundation of life in our oceans.

In-Situ Illegal Dump Identification

Kumi Analytics is able to identify illegal dumps from satellite imagery using a machine learning model. Of recent high consequence is the issue of illegal ocean and land dumping of refuse. Imagery sensors are capable of recognizing the signals of such activities. Kumi Analytics utilizes a range of sensors and machine learning techniques to identify this particular issue – helping companies identify illegal activities on their land as well as local authorities on violations of municipal zoning and environmental laws.

In-Situ Water Pollution Detection

Without water, we would not exist. Clean water is the foundation of a healthy society. It is our duty to do our best to not pollute drinking water while finding a balance with the necessary steps to be productive in our businesses. Kumi Analytics works together with industry and communities to identify where pollution is happening, how it can be cleaned up and how to avoid it in the future. The first step is identifying the cause. Through the use of satellite imagery and a machine learning model, we can identify locations and likely sources of pollution.

Very early detection of mining pollution events e.g. tailing ponds failure, toxic byproduct build-up, etc. Is detectable by multispectral imagery analysis. Constant monitoring by signal change via machine learning is the key to the solution.

  • Identify sources of contamination
  • Assess and mitigate pollution events
  • Monitor health of local environment
  • Establish joint industry / community collaborations