Inspiration
After learning about SDG Goal 12 - Responsible Consumption and Production, I learned that there are almost no efficient solutions for sorting trash in the waste management industries. If there is, the system is very complicated. For example, in my city there are three main bins for people to sort their trash, Metal, Paper, Organic, and Others. But what if the trash you need to dispose of is wet paper, will it go in the paper section or the organic section? This is complicated, so I created a project tackling one of the world's most pressing issues - an Automatic Waste Sorter.
What it does
This project can sort up to 4 different types of waste which is the most common type of waste disposed of by the average human, Metal, Glass, Organic, and Plastic. This project utilizes the use of multiple sensors to sort the types of waste into their designated bins.
How we built it
The project is built with an Arduino Nano as the main microcontroller, 1 inductive sensor, 1 capacitive sensor, 1 moisture sensor, 2 servo motors, and 1 ultrasonic sensor. The purpose of the inductive sensor is to sort metal objects, capacitive sensors help to identify glass objects, using a moisture sensor helps to sense organic objects, while the 2 servo motors help to move the bin and rotate the torque. The main body of the project has been designed on Fusion 360 where it was later printed on an Adventure 4 printer.
Challenges we ran into
A notable challenge encountered during development was determining the optimal duration for the bin servo motor to effectively sort items. Through mathematical calculations and experimentation, the precise spinning duration was successfully identified.
What I learned
The project provided valuable insights into 3D design using Fusion 360 and rapid material printing techniques. Emphasizing accuracy in design iterations was crucial to maximizing efficiency and minimizing production delays.
What's next for Automatic Waste Sorter
Future plans for the Automatic Waste Sorter involve integrating Artificial Intelligence capabilities to enhance object recognition and further refine the sorting process. This advancement aims to bolster the system's ability to accurately identify and categorize diverse objects for improved waste management efficiency.
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