Turtle Makers

When Emily recently visited Calgary to see relatives, she was happy to learn from her aunt that the Canadian city had taken the sustainable move of establishing curbside composting, moving the pick-up of curbside recycling and composting to once a week, and limiting the pick-up of curbside landfill to only once every two weeks. A municipal app notifies households of different disposal schedules. What Emily heard next from her aunt, however, surprised her. Although Calgarians generally support sustainable waste disposal, many have complaints against the newly-established system. Most rooms of households have only one waste disposal container ('the trash can'), so someone in the household is forced to sort through each room's trash can by hand. Children are especially prone to mistakes in sorting their waste into recycling, compost, and landfill. It often falls to the head of the household to regularly pick through garbage cans in order to comply with the sustainable waste disposal policy, so many don’t. These problems have resulted in contamination of waste streams, frustration among users, and subversion of a well-meaning policy for sustainability. If the complaints continued, the city will be forced to end the program. Turtle Makers had to respond. Bin Bot is the new smart sustainable waste system. One unit includes sections for compost, recycling, and landfill waste for easy division of waste streams in each room of the house. The most disruptive characteristic of BinBot is in its use of AI: BinBot uses machine learning and a image recognition software to learn from heads of households what household items go into each section as the Bin is normally used. After its short household-specialized training, BinBot is ready to operate. Whenever a user is unsure of where their waste should go, BinBot indicates the correct section for them using its training set and a lit-up LED. This is not only an aid to frustrated household heads; BinBot becomes an educational tool for children to learn sustainable waste practices. Even grown adults are often confused or forget how to correctly dispose of trash. BinBot will institutionally change how we think of waste disposal, and solve endemic waste stream pollution.

Alyssa designed and built the system for the triggered capture, training, and classification of photos of waste taken by the BinBot. She is a senior at MIT studying Mathematics with Computer Science, and is interested in new applications of machine learning. Emily is the ideas (wo)man. An environmental engineer, her background is in waste disposal, sustainable agriculture, and eco-leadership. She is passionate about disruptive green technology, and wants to lead the creation of sustainable interactions between people and the planet. Jake is the person responsible for interfacing with the hardware elements of the system. During the project, he created a python wrapper for controlling gpio pins and created an interface for Alyssa to trigger the LEDs. In addition, he designed our basic circuitry. We are Turtle Makers, the creators of BinBot.