SustainoVend: A Smart Reverse Vending Machine For Recyclable Waste With Card-Based Points and Automated Segregation

Document Types

Paper Presentation

Research Theme (for Paper Presentation and Poster Presentation submissions only)

Computer and Software Technology, and Robotics (CSR)

School Name

Mindanao State University - General Santos Senior High School

Track or Strand

Science, Technology, Engineering, and Mathematics (STEM)

Research Advisor (Last Name, First Name, Middle Initial)

Crusis, Algem Cris, B.

Start Date

25-6-2026 10:30 AM

End Date

25-6-2026 12:00 PM

Zoom Link/ Room Assignment

Online - https://zoom.us/j/94569671692?pwd=Fj3c3ELOebE6QbqbJOOH9wMuildoEc.1 Meeting ID: 945 6967 1692 | Passcode: research

Abstract/Executive Summary

Improper waste disposal and low participation in recycling remain major environmental concerns, particularly in developing communities where waste segregation systems are limited and inconvenient. Recyclable materials such as plastic bottles, aluminum cans, and glass bottles are often mixed with general waste, reducing their potential for recycling. To address this issue, this study presents SustainoVend, a smart reverse vending machine designed to promote proper waste disposal through automated segregation and a card-based points incentive system. The machine is capable of identifying and segregating PET bottles, aluminum cans, and glass bottles using sensors and a mechanical sorting mechanism, while an RFID-based card system records and displays accumulated points to encourage user participation. This research employed a research and development (R&D) approach focusing on the design, construction, and testing of a functional prototype. The system was tested to assess classification accuracy, segregation accuracy, processing time, point display accuracy, bin full-capacity detection, and waste rejection performance. Controlled experiments were conducted to evaluate the operational efficiency and reliability of the machine. Results of the study showed that the average accuracy percentage of SustainoVend in classifying, segregating, displaying points, detecting full capacity, and rejecting waste is “excellent”. Additionally, the average processing time of the machine in classifying is “good” while for segregating and displaying points, it is “acceptable.” The findings indicate that SustainoVend demonstrates potential as an effective tool for improving recycling participation and waste segregation practices, contributing to sustainable waste management efforts and supporting responsible consumption and production initiatives.

Keywords

reverse vending machine; card-based points; automated segregation; recyclable waste; recycling

Statement of Originality

yes

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Jun 25th, 10:30 AM Jun 25th, 12:00 PM

SustainoVend: A Smart Reverse Vending Machine For Recyclable Waste With Card-Based Points and Automated Segregation

Improper waste disposal and low participation in recycling remain major environmental concerns, particularly in developing communities where waste segregation systems are limited and inconvenient. Recyclable materials such as plastic bottles, aluminum cans, and glass bottles are often mixed with general waste, reducing their potential for recycling. To address this issue, this study presents SustainoVend, a smart reverse vending machine designed to promote proper waste disposal through automated segregation and a card-based points incentive system. The machine is capable of identifying and segregating PET bottles, aluminum cans, and glass bottles using sensors and a mechanical sorting mechanism, while an RFID-based card system records and displays accumulated points to encourage user participation. This research employed a research and development (R&D) approach focusing on the design, construction, and testing of a functional prototype. The system was tested to assess classification accuracy, segregation accuracy, processing time, point display accuracy, bin full-capacity detection, and waste rejection performance. Controlled experiments were conducted to evaluate the operational efficiency and reliability of the machine. Results of the study showed that the average accuracy percentage of SustainoVend in classifying, segregating, displaying points, detecting full capacity, and rejecting waste is “excellent”. Additionally, the average processing time of the machine in classifying is “good” while for segregating and displaying points, it is “acceptable.” The findings indicate that SustainoVend demonstrates potential as an effective tool for improving recycling participation and waste segregation practices, contributing to sustainable waste management efforts and supporting responsible consumption and production initiatives.

https://animorepository.dlsu.edu.ph/conf_shsrescon/2026/BoA_CSR/11