Whether you are working in an office or simply at home, the desk drawer is the go to place for small but important supplies. Its happened to all of us: You go to the drawer to get an item, whether that be a stamp, paperclip, or a piece of paper. You open the drawer only to find the item missing. Running to the store for such a small item is such a hassle, so you either get by with out it or waste precious time.
With the Smart Office Desk Drawer, that situation will never happen again. Each item is monitored with its own sensor, and when the item is running low, the product is automatically ordered via the Amazon Dash Replenishment Service. If the item isn't mission critical and can wait to be purchased the next time you go into town, the Smart Drawer will simply remind the user via email.
SensorsThe Smart Desk Drawer monitors six items:
- Post It! Notes
- Paperclips
- Stamps
- Tape
- AA Alkaline Batteries
- Office Paper
Each item has its own sensor to detect whether it is running low or completely out. The batteries are monitored with a miniature break beam sensor, similar to the ones found on garage doors. The paperclips and Post It! notes are watched with CDS photoresistors, the stamps a rotary encoder, the tape a SPDT switch, and the paper a load cell. All of the sensors are connected to the Particle Core, a IoT device with a 32 bit ARM processor and CC300 WiFi module.
Once a day, the Particle Core wakes up from sleep and polls all of the sensors. If a sensor detects an item is running out, the Particle Core will either notify IFTTT so an alert email can be sent to the user, or the Core will place an Amazon order on its own using the Amazon Dash Replenishment Service (DRS).
To use Amazon DRS, the user must first register with an Amazon Account using a simple webpage I designed and hosted using Github Pages. You can check it out at https://spadgenske.github.io/SmartDrawer or the code on the gh-pages branch of my repository.
This project is 100% open source, all the schematics, 3D printable files, and code can be found on my Github repository.
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