Smart Trash Bin
HCID 521 Prototyping Studio | Week 9 | Final Project
It happens everyday, in front of the trash bins around you: decision making. Not until the moment we walk on to the trash bin did we realize there are so many different options out there! While we are trying to get our trash in the right place, we always fail and get confused by the labels written with “Compost”, “Recycle”, and “Waste”. Our arms, holding our trash in hands, go left, right, left, and right, repetitive like a dance move in the 80s, an awful one.
Since this assignment was announced, which required two prototyping techniques in a single problem statement, Michael and I started talking about this problem. We both agreed that we need something, implemented by technology, that assists us to get it right. We envisioned it as an expert of categorizing trash, standing right beside the bins, telling you where your trash should go. We both agreed that it should be built upon the existing trash bins. What we came up with was a basic interactive system of detecting/analyzing/indicating trash.
Our testing took place in the HUB during a less crowded weekday afternoon. We built up our prototype by two laptops, an iPhone, and an Arduino. With a box embedded with several LED indicators, the prototype was actually a “Wizard of Oz” model, which was controlled by us manually. Basically we placed the box on the trash bin, and set up a video call from the iPhone embedded in the box, to the laptop at another corner of the room, so one sitting at the laptop is able to see what is happening in front of the trash bin.
Observing people is always fun, especially seeing them throwing out trash with completely different ways. During testing, some reacted the way we expected, while others reacted with the system in various patterns. Many people noticed the system, but chose to ignore it, or got confused about how the system worked and reacted different from the system implied. Others simply ignored the system. We figured out it might be the fidelity of prototype, the responding time of the system, and the time they took for throwing out trash were too short to engage a categorizing system in it.
Also, we actually came up with some new ideas of making people grouping their trash in the right way. One is that we observed most of the users looked into the trash bin before they threw out the trash. This action implied that they confirmed their action based on environment/surrounding/social effect. Started from this, we thought the trash bin itself could be renovated in appearance, like, cover it up with some printouts (whether they’re transparent or not) to create an illusion of a full bin, and make people decide where their trash should go more intuitively.
Overall we have been pretty excited about implementing skill sets we have learned this quarter in the studio and integrating them into the final project, which brought us more techniques and insights in improving design/research/evaluation process.
