| Group |
2019-18 |
Status |
completed |
| Title |
Mixed Drink Dispenser |
| Supervisor |
F. Khendek |
| Description |
Our project will be to create a drink dispensers that can be deployed at festivals or air commune type of events. This will reduce line ups and increase sales compared to traditional bars. Due to the nature of the project, we will be incorporating software, electrical, computer and mechanical features.
Features:
• Distribute mixed drinks in real-time
• Order through a phone app (if user has a phone and internet)
o Make payments (by credit card) through the phone app
• Order on the machine screen, slow (if user has no phone)
o Make payment by card (maybe cash) through the machine
• Get available drink menu from online through app (if internet)
• Get available drink menu from displayed QR code on machine (if no internet)
• Machine location displayed to users through phone app
• ID card image processing to detect age of person (scan id card to validate if it is valid)
• Validate that the ID is a Canadian government issued card (more training required for other countries)
• Sensor to detect when machine needs cleaning and refilling
• Notify technician over app when error occurs, liquids are low or cleaning required
• Pumps to make drinks
• Multiple terminals to handle parallel orders
Things to explore:
• Water cleaning system after every drink served
• Hygiene with sugary liquids and contamination
• Full soda stream that mixes flavor, CO2 and water?
• Containers for liquid
• System design for ease of maintenance
• How to do feedback for drink ratios? Mass scale or flow sensors?
• Potential for prepaid chip based sales
|
| Student Requirement |
Software skills:
• Programming language knowledge (Java, C#) – SOEN 321, COEN 390
o To create the mobile application
o To communicate with the database
• Machine learning
o To incorporate image processing and potentially facial recognition
Computer skills:
• Design real-time control circuit with microcontroller – COEN 317, COEN 320
Electrical & mechanical skills:
• Oscilloscopes and multimeters – ELEC 311, 312
|
| Tools |
Software:
• Programming environment will most likely be Android Studio
o Android phone
• Database
• Cloud service/provider or server
• GPU for machine learning
Hardware:
• Microcontroller to control valves
• Pumps & tubes
• 3D printer to design/create parts
• Microprocessor to be used as the main computer
|
| Number of Students |
5 |
| Students |
William Bergamin, Michael Yablonovitch, Constantina
Roumeliotis, Alex Gendron, John-Nicholas Cheng Tarantino |
| Comments: |
|
| Links: |
|