A novel technique of using a rocker to determine if either the beverage was taken out of cooler or pushed back into the cooler
A way to decrease the cost of this system significantly
motivation of project, Identify the State of innovatory of a cooler
The measurables needed in order to collect data to Identify product
Using color profiles from certain bottles and cans in order to identify them
A novel technique of using infrared sensor to identify if there is either a can or bottle in a cooler shelf
#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.
- Color of label
- Color of liquid
- Color of bottle cap
- Motion detection to determine container type using Infra red LED and Photodiodes
- Switch button to identify items being placed into cooler # # What does it measure?
- Motion detection
- 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?
- Infrared emitter and detector Diode
- Rocker switch
- Pre-calculated color profile on Coke products labels, bottle caps, and container contents built from collected data
- 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.