Project

# Title Team Members TA Documents Sponsor
55 Waste Segregation System (Team members: syedr3, rutvadp2, konarkd2)
 Ahmed Raza
Konark Dhingreja
Rutva Pandya
 Maanas Sandeep Agrawal design_document1.pdf
final_paper1.pdf
photo1.jpg
photo2.jpg
presentation1.pptx
proposal1.pdf
video
# Problem
Inefficient waste segregation is a critical environmental challenge. While recycling facilities exist, their effectiveness is severely limited by improper waste sorting at the source. Manual sorting is prone to errors, time-consuming, and often results in recyclable materials being sent to landfills. There's a clear need for an automated system that can accurately segregate waste at the disposal point.

# Solution
Our solution is an intelligent waste segregation system that automatically identifies and sorts waste into appropriate categories using computer vision and mechanical automation. The system comprises a main intake chamber with a camera for material identification, connected to four separate collection bins (for glass, plastic, metal, and non-recyclable waste). A pre-trained machine learning model running on an Arduino processes images to identify materials, while a tilting platform drops items into their matching bins.

# Solution Components
## Vision and Processing Subsystem
- HD camera for waste item imaging
- Custom PCB with Arduino for system control and ML model execution
- Pre-trained TensorFlow model for material classification
- LED indicators for bin status and error conditions

## Mechanical Sorting Subsystem
- Routing mechanism with 4-way directional control
- Emergency stop mechanism for system blockages
- Anti-jamming detection system

## Power and Housing Subsystem
- Converts standard outlet power to the required sensor, microcontroller, and communications module demands Example RFA (cont.)

# Criterion for Success
Our solution will be considered successful if it achieves:
Material identification accuracy of >70% under various lighting conditions,
Sorting speed of at least 1 item every 20 seconds,
Ability to handle items up to 500g in weight, and
Less than 20% system jamming rate during continuous operation

Drum Tutor Lite

Zhen Qin, Yuanheng Yan, Xun Yu

Drum Tutor Lite

Featured Project

Team: Yuanheng Yan, Zhen Qin, Xun Yu

Vision: Rhythm games such as guitar hero are much easier than playing the actual drums. We want to make a drum tutor that makes playing drums as easy as guitar hero. The player is not required to read a sheet music.

Description: We will build a drum add-on that will tutor people how to play the drums. We will make a panel for visual queue of the drum and beats in a form similar to guitar hero game. The panel can be a N*10 (N varying with the drum kit) led bar array. Each horizontal bar will be a beat and each horizontal line above the bottom line will represent the upcoming beats.

There will be sensors on each drum that will fire when the drum heads is hit. The drums will be affixed with ring of light that provides the timing and accuracy of the player according to the sensors.

Of course with a flip of a switch, the drum could be a simple light up drum: when the player hits the drum, that particular drum will light up giving cool effects.

The system will be on a microprocessor. Or for more versatile uses, it could be connected to the computer. And a app will be written for the tutor.

Project Videos