Our story starts with our inspiration

 

Incorrect waste disposal is a significant contributor to climate change

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Every year, the world generates over 2 billion tons of solid waste. 

This waste generates over
1.5 billion tons of CO2 equivalent GHG, contributing nearly as much to climate change as all the cars on U.S. roads. Even though 75% of this waste is capable of being recycled, only 34% is actually recycled. 91% of plastic isn’t recycled and only 5% of food is composted

Our own story with waste management started when our founder, Yash Narayan, took a trip to his local recycling center in San Mateo, CA. He was surprised to see large amounts of recyclable and compostable material being thrown into our landfill. After that visit, he became obsessed with the problem.

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Yash Narayan is passionate about using technology to tackle climate change. DeepWaste started from his deep personal experience and the urgency he sees to solve climate change in the next decade. He is currently a researcher at the Stanford Sustainable Systems Lab and Stony Brook University's Department of Geosciences. Yash has been participating in Hackathons since he was 10 and is a six-time Hackathon winner. He loves nature and has visited several national parks across the world including in Peru, Costa Rica, Tanzania, China, New Zealand, India, and in the US. 

Bin contamination is a huge problem

Errors in waste disposal are not only missed opportunities to recycle or compost, but also lead to the contamination of entire recycling bins. Often, an entire waste bin can end up into a landfill due to a single error leading to contamination.

Data from the National Waste and Recycling Association shows that human confusion in the disposal of waste in waste bins results in nearly 25% of recyclables getting contaminated,  diverting materials that could be recycled in our landfill

When compostable materials such as food scraps gets into a landfill, it is compacted down and covered. This removes the oxygen and causes it to break down into an anaerobic process. Eventually, this releases methane, a greenhouse gas that is 25 times more potent than CO2 in warming the earth

 

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Existing approaches are inaccessible, expensive, slow, and inaccurate

Confusing signs found at waste bins are hard to understand and are incomplete.

Expensive and hard-to-scale “smart bins” at recycling center are unable to prevent the bin contamination that occurred at the time of disposal due to humans.

Current machine learning research suffers from low accuracy (ranging from 22% to low 70%) or is too slow for real-time usage within a mobile application.

None of these approaches target compost classification. Accurate compostable disposal is important because when compost ends in landfills → methane emissions 

 

Effective solution needs to be fast, accurate, and accessible at the time of waste disposal

DeepWaste utilizes the recent breakthroughs in AI for image recognition and the increased computational power on everyday cell phones to provide a novel approach for waste classification that is accurate, low-cost, fast, and accessible.