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CMU 2022 Build18 Hackathon: MagicBin

The MagicBin is an enhanced trash detection system that hopes to collectively solve the inherent recycling problems. The system blends machine learning and open-source software with the Raspberry Pi ecosystem. Our object detection software combines OpenCV and MobileNet datasets to effectively differentiate recyclable bottles from other landfill waste. Our dataset combines over 10,000 images to effectively communicate our output along with the object's desired recyclability. Our hardware system, which includes Raspberry Pi, HD PiCam, Arduino MKR ZERO combined with two high-torque servos, can efficiently recognize the output and direct the item to its proper place in our trash bin. Furthermore, our implementation of a lottery-based system using smart contracts encourages users of the MagicBin to recycle on their own, while also rewarding them for their current and future contribution to the MagicBin.

Electrical Systems

Smart Contract Implementation

Materials

  • CanaKit Raspberry Pi 4 4GB Starter PRO Kit - 4GB RAM
  • Arducam Lens Board OV5647 Sensor for Raspberry Pi Camera
  • Adafruit 16-Channel PWM / Servo HAT for Raspberry Pi
  • SparkFun 16x2 SerLCD - RGB Text
  • TP-Link USB WiFi Adapter for PC
  • 5V 2A (2000mA) switching power supply
  • Flex Cable for Raspberry Pi Camera
  • Standard servo - TowerPro SG-5010 - 5010
  • Servo Extension Cable - 30cm
  • OPTIX Acrylic Sheet

Tools/Machinery/Software

  • Rabbit Laser Cutter
  • Dremel 3D40 Printer
  • CAD (Soildworks)
  • Miter Saw
  • Bosch Handheld Drill

Purpose

Our main purpose is to improve the accuracy of recycling and increase recycling amounts through monetary incentives.

Next Step

With an increased budget and additional time, our MagicBin would consist of a newer and improved trained dataset that can detect recyclables beyond bottles. With a larger dataset, we hope to differentiate multiple recyclable materials from other waste products. This would allow our MagicBin to consist of multiple compartments for each identifiable category of recyclable materials. Furthermore, with a higher quality hardware system, our MagicBin could more quickly and efficiently sort our trash concerning its recyclability.

Currently, the national recycling rate sits at only 32.1%, but nearly 80% of all waste can be recycled. Our MagicBin hopes to solve this systemic problem by providing convenience to users. By allowing our trash bin to determine the recyclability of the object, users are now free of the burden to identify their waste products on their own. Furthermore, by separating recyclable items from each other, our MagicBin can reduce potential contamination among some plastics and non-recyclable materials. Overall, by adding more compartments and improving our hardware features, our MagicBin hopes to increase the recycling rate by reducing contamination and improving recycling identification.

License

MIT

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  • Python 80.0%
  • C++ 20.0%