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607 10th Street Suite 306, Golden, CO 80401

Projects

Predictive Financial Analysis with Machine Learning Software

Project 1

This software allows the owner / operator to predict incoming business through many different machine learning parameters. This uses different machine learning algorithms with input parameters along with historical financial data to forecast the business’ income. Once the forecast is predicted, the software can suggest various human resource plans, product buying plans, marketing plans and accounting plans. Machine Learning and TrainingFor an example, a casino would use this to predict how much staff they would need for a given day or week. This analysis is based on various casino input parameters i.e. coin-in, jackpots, coin-out, theo-win, automobile traffic “pass-by”, and weather: temperature, humidity, precipitation. From there, the business owner is able to plan their human resources, marketing strategies, financial plans with increased accuracy.

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Product Placement Analysis with Machine Learning Traffic and Movement Software

Project 2

This software module looks at the business’ surveillance cameras and has the ability to; analysis the camera movement, translate those movement into x and y coordinates, insert those coordinates into a database. On the reporting side, this software has the ability to display the movement coordinates for a given timeframe. Within this display, the owner / operator has the ability to select a sub-section (ie food section or a slot machine) of the coordinates and the software will display data about the sub-section. This sub-section data consists of machine learning analytics, and other useful business decision making data. In other words, this gives the business owner / operator machine learning data based on surveillance movement to make better business decisions.

For example, a casino owner / operator selects a camera, then they select a date range they want to analyze, let’s say they select last weekend. The software will then display the dots of movement, then they highlight a slot machine. Then the software displays machine learning data that tell them how the slot machine is perform in the past and in the future. Then the owner / operator can easily make a decision to keep, move or remove that slot machine. This software will optimize their casino 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.