Detection of Contaminants and Pollutants using Artificial Intelligence

Detection System

Our application works through many intricate and basic algorithms where the first step is to train the AI in single or clusters of specific matter. After proper training, we can provide a sample to the AI for evaluation using an image enlargement device such as a microscope or folded mirror lenses connected to GPUs, CPUs and live video or camera feeds. The AI then evaluates, labels, and classifies which matter is selected for detection. We gather the AI’s results and provide it to our clients.

The user can choose between the manual application or incorporating drones, robots, and channel systems for autonomous and simplified sample collection. New sensors and technologies can be added to the AI detection system for expanded detection techniques and capabilities. A new hand held UMMDA (Universal Multipurpose Matter Detection Apparatus) patent application has been filed for use in the medical industry. Watch the USPTO publications for the publication of the patent application and its diagrams.

Current Micro-Organism Detection

Current processes, techniques, and technologies for microbe and contaminant identification MAY take up to 24 hours to several days. Hand collected samples must be obtained without disruption (cross-contamination) and transported to a lab. The time between the moment the specimen is collected and the final result depends on the sophistication of equipment used and the expertise of the humans involved in the process. Our new AI detection method is faster, more accurate and less costly in all industries.

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THE FUTURE OF MICRO-ORGANISM DETECTION

How do we obtain micro-organisms and matter without contaminating the sample or exposing the end-user to harmful matter?

Using drones and robots eliminates most of the cross contamination where the AI system is designed to detect abnormal collection processes.

Once the sample is obtained, a drone or robot deposits the sample into a receptacle also connected to a transport system that brings the sample to the AI detection area.

Global Virus Network ("GVN")

The best way to increase accuracy is through a high number of samples. Our application can utilize millions of data points to ascertain the singular form (and clusters thereof) of microbes, contamination, and matter from pictures and other sensors. Our data is proprietary, and our training sets are unique. The more information we have, the more accurate the system becomes.

With increased amounts of continuous data, we can track contaminants and outbreaks over time and throughout the environment, providing valuable information that will tell us the epicenters of outbreaks and where they’re headed. In the coming years, data from our collections can be used to create a Global Virus Network (“GVN”) for the early detection of outbreaks and contaminants.

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Project Claire in action. Contaminants in drinking water

Project Claire in action video #2. Contaminants in drinking water