Ryan works on his design of a smart paper recycling bin that will allow him to track the collection efficiency and relate it to its placement in the building. Our current paper recycling program is part of a pilot that is allowing us to understand the paper disposal needs of the building. With only four bins that have been green lit for collection, it is Ryan’s goal to maximize the collection capacity of these bins by placing them in our building’s most highly trafficked areas.

His design incorporates a load sensor that collects the weight from a hacked bathroom scale, an ultrasonic sensor that can detect the volume of the paper in the bin, and a temperature and humidity sensor that can detect if materials other than paper (such as food and drink containers) have been placed in the bin. He is using an Arduino micro controller to collect the sensor data. The data is being passed on to a Raspberry Pi via serial communication where it is then being hosted on an online IoT dashboard that can be remotely monitored and analyzed from his smart phone.

Ryan has developed a communication system that will send him email and text message notifications if the bin is in need of being emptied or if it suspects there may be materials other than paper in the bin. The bin is also equipped with two methods of data visualization that includes an onboard LCD and Neopixel strip acting as a capacity bar graph.

Future iterations of his design will include the ability to maneuver itself to new locations according to learned algorithms of paper collection and foot traffic. He will also be incorporating a PiTop [4] as the device’s brain which will help provide on board power for greater autonomy.