AI-Eco Sort Station
Let AI do the sorting, you just throw the trash!
Why AI?
I believe the AI should "Streamline and enhance efficiency in tasks that are either undesirable or require precision beyond common human capabilities."
Automating Unpleasant Tasks:
Using AI to handle waste sorting, a traditionally unpleasant and tedious task.
Enhancing Sorting Accuracy:
AI-driven image recognition technology ensures high accuracy in identifying and categorizing waste materials.
Data Collection and Optimization:
Collects valuable data to optimize waste management strategies, collection routes, and schedules.
Background
As environmental awareness grows, smart waste sorting has become a crucial component of urban management and sustainable living...
DSNY Litter Basket (Map) by NYCOpenData
In high-density areas (such as Midtown Manhattan), although the number of trash bins is relatively high, it may still be insufficient to meet the demand from the large volume of foot traffic, potentially leading to overflowing bins. Trash bins in high-density areas may require more frequent cleaning, while those in low-density areas might be overlooked in waste collection schedules.
How the Garbage and Recycling System Work in the United States?
Insight
Due to factories being located in different areas, waste must be transported through transfer stations and MRFs before it can be processed into raw materials.
There is a shortage of opportunities to educate the public. A major challenge in waste management stems from the incorrect sorting of waste, which complicates the recycling process.
Opportunity
Cost Savings:
Lowers waste management costs by reducing manual sorting .
Reduce Disposal Costs at MRFS:
Pre-sorting waste reduces the need for further processing at recycling centres.
Places that require sorting are in great need of manpower while also demanding efficiency. (Even AI sorting is applied)
Education opportunity
To educate users about proper waste management, recycling practices, and environmental sustainability.
Storyboard
Promoting Environmental Behavior
Encourages correct waste sorting through instant feedback, enhancing users' environmental awareness.
Making Waste Disposal More Engaging
Offers an interactive interface that makes the disposal process engaging and educational, allowing users to track their environmental contributions.
Encouraging Community Participation
The bin can foster community involvement and pride in local recycling efforts, enhancing public commitment to sustainability.
The colors of lights change according to trash categories
When metal is recycled
When Plastic is recycled
NightLight
Optimizing Space Utilization:
The design maximizes available street space, making it ideal for crowded urban environments by keeping streets cleaner and less cluttered.
Public Health Improvement:
Improves public health by reducing risks of contamination and pests associated with poor waste management.
Positive Environmental Impact:
By increasing recycling rates and reducing contamination, the bin reduces landfill use, lowers pollution, and conserves natural resources.
Floor
Screen
Camera & Flash
Side Camera
Water Outlet
Lighting
Blocking mechanism
Battery
Sorting Mechanism
Glass
Paper
Organic
Metal
Cardboard
Plastic
Unsorted
Design Document
AI-eco Sorting station
Jan, 2024 - April, 2024
Individual
Professor Ignacio Ciocchini provided valuable feedback during the development of this project.
You can rotate the Model
