Eco-Genie: Automated Recycling System

Presented by: Steven L., Sebastian C., James R. Pacinda, Yannick K.

Mechanical Engineering Program - Texas Tech University

Back to Capstone Project Eco-Genie Cover Page

Background and Problem Statement

The Eco-Genie project aims to develop an efficient, automated recycling sorter capable of distinguishing and sorting plastics, glass, aluminum, and steel. The primary goal is to enhance household recycling efficiency, minimize contamination, and streamline the sorting process. Traditional recycling methods often lead to inefficiencies due to human error and lack of proper classification, resulting in high contamination rates.

Analysis of Need

Manual sorting of recyclables is labor-intensive and inaccurate. Studies indicate that contamination in single-stream recycling programs significantly increases processing costs and reduces the overall effectiveness of recycling efforts. Eco-Genie will address these problems by implementing automated sorting technology to increase accuracy and reduce labor dependency.

Design Criteria

Sorting Accuracy: Must achieve at least 95% accuracy in classification.
Processing Speed: Should process a minimum of two items per minute.
Power Efficiency: Should operate below 50 watts.
Safety: Must comply with UL certification standards.
Compact Design: Should fit within a standard household space.

Evaluation of Alternative Designs

Several design options were explored before finalizing the Eco-Genie system:

Design A: Optical sensors and mechanical arms for sorting—highly accurate but costly.
Design B: Rotary drum with embedded sensors—balanced accuracy and cost but required frequent maintenance.
Design C (Final Selection): Uses ultrasonic, inductive, and capacitive sensors combined with a linear actuator and tipping mechanism for accurate, cost-effective sorting.

Technical Approach

Eco-Genie will integrate multiple sensors to detect the material type. A microcontroller will process this data and operate a tipping mechanism to sort recyclables into designated bins. A bucket elevator will facilitate material loading, ensuring continuous operation.

Prototyping and Testing

Multiple iterations of the prototype were developed, starting from early concept sketches to fully functional systems. Each version incorporated design refinements to improve efficiency, reduce material waste, and ensure compatibility with various recycling streams. The testing phase validated the system’s ability to correctly classify and sort different materials with minimal errors.

Conclusion

The Eco-Genie project presents a transformative approach to automated recycling. By leveraging advanced sensor technologies and real-time sorting mechanisms, it enhances classification accuracy and significantly reduces human error. With a projected accuracy rate exceeding 95%, Eco-Genie serves as a practical solution for improving waste management systems. Future development will focus on integrating AI-driven recognition algorithms to further optimize material detection and sorting.

The project showcases advanced engineering design, problem-solving skills, and cross-disciplinary collaboration, demonstrating the potential for innovative mechanical systems in sustainable development.