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  solution

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  A novel technique of using a rocker to determine if either the beverage was taken out of cooler or pushed back into the cooler

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  A way to decrease the cost of this system significantly

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  motivation of project, Identify the State of innovatory of a cooler

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  The measurables needed in order to collect data to Identify product

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  Using color profiles from certain bottles and cans in order to identify them

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  A novel technique of using infrared sensor to identify if there is either a can or bottle in a cooler shelf

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  solution

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#How does it work?

Our system takes several measures on the coke products and identifies them to an established color profile and container characteristics. Then, a statistical test is used to fit data to curves for the purposes of detecting beverages.

1. Color of label
2. Color of liquid
3. Color of bottle cap
4. Motion detection to determine container type using Infra red LED and Photodiodes
5. Switch button to identify items being placed into cooler # # What does it measure?
6. Color
7. Luminosity
8. Motion detection
9. Items being placed into cooler • Does the retailer/bottler/distributor have to do anything different to make your solution work? (if yes, please explain) -No • ## What materials does your solution require?
10. LED
11. Infrared emitter and detector Diode
12. Photoresistor
13. Rocker switch
14. Wires
15. Pre-calculated color profile on Coke products labels, bottle caps, and container contents built from collected data
16. Statistical Tests to determine if it is probable that the product under the sensor in a given moment matches the color profile for a known product with an arbitrary level of confidence.

• ## Best guest on cost to implement Proposed Prototype per cooler shelf:

LED Light x 2 $1 Photoresistor x 2 $1 Infrared emitter and detector Diodes $2 Rocker switch x 2 = $1

Total Approx $5 ( retail)

Current Prototype / cooler shelf:

RGB Color Sensor x 2 $13 Infrared emitter and detector Diodes $2 Rocker switch x 2 = $1

Total Approx $16

Challenges you/your team ran into

We found collecting good data and building a comprehensive color and feature profile on Diet Coke, Sprite, and Coke difficult. • ## What you/your team learned

• Learned Coke’s Business interest in coolers
• Leaned what makes a product scalable
• Identified current market problems
• Used Microprocessors and Microcontrollers to collect data • ## Next steps The next steps are to implement a conclusive color profile and container characteristic of each Coke product with the measures listed above and that will assist in dependable data. We are confident in reaching a significant lower cost by implementing a LED Light and Photoresistor combination. Trouble shooting will continue with being able to identify whether it is a bottle or can.

Built With

• ankim.dk1@gmail.com
• arduino
• established-color-profile-and-container-characteristics.
• pre-procced
• python
• raspberry-pi