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607 10th Street Suite 306, Golden, CO 80401

Solutions

Forensic Video Exploitation and Analysis – FOVEA

Developed for the Department of Homeland Security, FOVEA gives operators tools to efficiently review security footage to build a case or review active alerts. This software adds video analytic capabilities to any surveillance system. Creating an instantly safer environment and increasing the intelligence available for security operations to make informed decisions by reviewing footage to build evidence quickly.

project 1
project 1
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Product Placement Analysis with Machine Learning Traffic and Movement Software

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This analysis tool utilizes the existing surveillance cameras to track and analyze customer movements throughout the facility. This gives the business owner the data to make better business decisions.

For example, a casino owner can better understand traffic flow each week to place machines in prime areas depending on the time of day, maximizing revenue and optimizing the floor. 

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Fast Food Restaurant “Drive-off” Analysis with Video Surveillance Machine Learning Software

Project 3

This software is used to machine learning and re-learning algorithms to identify “drive-off” situations in fast food / quick service restaurants. This will use the surveillance cameras’ footage outside of the fast food to create and deploy what are called “drive-off” triggers. These triggers are coordinates in the camera where drive-off points occur. Once a drive-off trigger has been activated, the software will take a picture of the situation, feed it into the software’s machine learning module. Then ML module will compare the current picture with other pictures from the past and make a decision whether or not this is a true drive-off situation or not. If this is a drive-off situation, then the software will notify management of the situation. Then management can adjust the business’ operation to accommodate for the increasing in drive-through traffic in real-time. After the fact, the software can apply machine learning predictive analysis and suggest human resource levels, food supply and other business needs to management. This way management can make better decisions to run their business based on optimized machine learning data.