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Team AlternativeChoices October 10, 2012

Preliminary Design Review. Team AlternativeChoices October 10, 2012. AlternativeChoices. Professor Gong Advisor. Vangjush Dedo EE. Stenli Duka CSE. Lusheng Tang EE. Salvador Rivera EE. Inefficient Food Service in US Campuses. Current Food Service

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Team AlternativeChoices October 10, 2012

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  1. Preliminary Design Review Team AlternativeChoices October 10, 2012

  2. AlternativeChoices Professor Gong Advisor VangjushDedo EE Stenli Duka CSE Lusheng Tang EE Salvador Rivera EE

  3. Inefficient Food Service in US Campuses • Current Food Service • Slow and overcrowded during peak hours • Safety hazard inside facilities • Students have no way of knowing if a place is crowded or not • Inefficient use of school resources

  4. How significant is the problem? • Over 2600 Universities and Colleges in US • More than 20 million students • UMass Amherst has over 15 food facilities on campus • More than 25 thousand students enrolled • Improper allocation of school resources • A lot of money is spent on dining • Valuable space wasted

  5. Context: Effect on Individuals • Students waiting • Study time wasted • Late to class • Become angry • Overcrowding • Bad eating environment • Safety hazard

  6. Context: Effect on School • Safety hazard caused by overcrowding • Unhappy students • School reputation negatively affected • Crowd management • Improper allocation of school resources • Workers not placed where needed

  7. Requirements Analysis: Specifications • Real-Time measurement of number of people • Facility specific information • Multiple entrances • Compact design • Information accessible online • Updates every thirty seconds • Detect multiple people leaving/entering

  8. Requirements Analysis: Inputs and Outputs • Input • Sensor data • Output • Current people count in a food facility • Expected amount of people in future • Offer nearby alternate locations with less people

  9. Design Alternatives • PCCI - People Counter with Computer Interface • “Passive Infrared” (PIR) Sensor unit • Connecting cable runs between people counter unit and the computer interface unit • The PCCI is to be located close to the personal computer (within half a meter) • Data can be collected from a single store through a (Microsoft Excel compatible) text file. • $700

  10. Design Alternatives • WF-5001 indoor people counter • Fast pulse narrow beam infra-red • 10 meters sensing distance • Extremely robust construction • Low power consumption • Unaffected by bright sunlight • SD card memory data stored • $200

  11. Design Alternatives • CompuCount 418/900 Server • 418 MHz Unit with typical indoor range up to 200 feet • 900 MHz Unit with typical indoor range up to 1500 feet • Individual IP Address to identify specific locations • CRC-16 Error Checked Radio Data assures data accuracy • $999

  12. Our Solution: AlternativeChoices • PIR Sensors • Located at every entrance • Continuously monitoring • Arduino Yun • Sensor Processing • People counting algorithm • Wireless transmit data to database • Website • Accessible from any browser, mobile friendly • Updated every 30 seconds • Suggests nearby facilities that are less crowded • Future prediction and history

  13. Our Solution: Block Diagram Data Collection Data Storage Power Supply Sensors Database Processing Database Modification DB Connection Wireless Transmission User Interface Real-Time Data Alternatives Future Prediction History Database Processing

  14. Sensors • Requirements • Detect movement • Availability is 200ms • Safe on people • Implementation • PIR (Passive InfraRed) • Process using Arduino Yun

  15. Power • Requirements • Arduino Yun operating voltage is 5V • Sensor operating voltage is 5V • Implementation • 5V power supply • Connected to wall outlet

  16. Sensor Processing • Requirements • Inputs for at least 2 sensors • Flash memory • Processing should take under 200ms • Implementation • Arduino Yun • State Machine

  17. Wireless Transmission • Requirements • Reliable • Occurs every 30 seconds • Easy to implement • Implementation • Arduino Yun with onboard WiFi • IEEE 802.11b/g/n • Connect to school wifi

  18. Database • Requirements • Store people count every 30 seconds • Timestamp for each people count • Location for each people count • Implementation • MongoDB • MongoHQ on Heroku • Access using REST API

  19. User Interface • Requirements • Easy to use • Accessible • Deliver results • Real-Time Data • Alternative Choices • Future Prediction • Implementation • Website • Python using Django • Hosted on Heroku

  20. Proposed MDR Deliverables • Demonstration of People Counting • PIR sensor data processed on Arduino Yun • Data wireless transmitted to database • Demonstration of User Interface • Interpret database • Display real-time people count • Display history

  21. Thank You Questions

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