BetaDelta
Project Overview
The purpose of the BetaDelta Website is mainly to provide real-time updates on the availability of residential study rooms to the South 40 WashU student body. Study room availability will be uploaded to the BetaDelta website via Wifi dongle, based on information from light, motion, and sound detectors, which will be connected through a raspberry pi system. The raspberry pi will be encased in a 3D printed shell and will placed in the optimal position in a given study room, based on its shape and size.
Information from each of the three sources will be displayed with its corresponding study room, where motion and sound will report its most recent activity and the light reporting a status of either "on" or "off." The website will have a couple of additional key highlights, the first of which will be easily accessible logs of past weekly study room availabilities. This will allow students to predict the timing and location of future study sessions. The second key highlight will be the ability to see which subjects are being studied in rooms around the South 40, where students are open to collaboration on a user-input basis. The third key highlight is that study rooms indicating signs of vacancy will be displayed on the BetaDelta website in order of probability of being available. The probability of availability will be based on how recently motion (the most weighted component) and sound have been detected in each study room as well as whether or not its light is on.
Team Members
- James Tiffany
- Rebecca Smith
- Nial Alwash
- Nathan Schmetter (TA)
Objectives
Create a device that:
- Is contructed with a raspberry pi
- connected to a light, motion, and sound detector
- Has a 3D printed casing
- Can update the BetaDelta website through a Wifi dongle
Create a functional website, BetaDelta, that can provide real-time information:
- Whether or not room occupied
- Ranking of study room availability probability
- What subject is being studied
- Log of study room usage
Create a demo-room for simulation
Challenges
- Learn Python
- Learn how to 3D print
- Design circuit involving R-Pi with sensors
- Learn how to connect R-Pi with website thru internet connection
Budget
| Item | Quantity | Price | Vendor | Link |
|---|---|---|---|---|
| Raspberry Pi | 1 | $0 | Lab | |
| Micro SD Card (8GB) | 1 | $9.95 + $7.14(Adafruit shipping) = $17.09 | Adafruit | https://www.adafruit.com/products/3259 |
| Light (LDR) Sensor | 1 | $6.95 | Adafruit | https://www.adafruit.com/product/1980 |
| 1uF Capacitor | 2 | $11.98 | Uxcell | http://www.uxcell.com/1uf-50v-105c-radial-electrolytic-capacitor-5x11mm-p-162619.html |
| Motion sensor | 1 | $9.95 | Adafruit | https://www.adafruit.com/product/189 |
| Sound detector | 1 | $6.95 | Adafruit | https://www.adafruit.com/products/1063 |
| Breadboard Wires | 1 | $7.29 | Amazon | http://www.amazon.com/Solderless-Flexible-Breadboard-Jumper-Wires/dp/B005TZJ0AM |
| 4 Digit Display | 1 | $11.95 | Adafruit | https://www.adafruit.com/products/881 |
| Perfboard | 1 | $12.50 | Adafruit | https://www.adafruit.com/product/571 |
| Website | For 3 months | $2.99(X3) = $8.97 | WordPress | https://wordpress.com/#plans |
| Total | $93.93 |
Gantt Chart
