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Scalable Step-by-Step Approach of Sustainable Bioplastic Production from Food Waste
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Open source IoT-based collection bin applied to local plastic recycling.

Alex Gabriel1, Fabio Cruz1

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This summary is machine-generated.

Local recycling of plastic waste reduces environmental impact. This study details smart collectors that provide real-time data, optimizing collection routes and improving recycling efficiency.

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Area of Science:

  • Environmental Science
  • Engineering
  • Computer Science

Background:

  • Plastic waste poses significant environmental challenges, necessitating effective management strategies.
  • Current recycling logistics chains generate greenhouse gas emissions due to energy consumption and transportation.
  • Localizing plastic waste recycling can mitigate transportation impacts and enhance collection processes.

Purpose of the Study:

  • To design, assemble, and set up smart collectors for local plastic waste recycling units.
  • To enable on-line data generation regarding collected plastic waste quantities.
  • To optimize the plastic waste supply chain through data-driven insights.

Main Methods:

  • Development of hardware, system architecture, and software for smart waste collectors.
  • Integration of on-line data collection capabilities into the collector system.
  • Engineering design and technical specification of the proposed system.

Main Results:

  • The designed smart collectors provide real-time data on waste collection.
  • A network of these collectors can reduce unnecessary travel by notifying when full.
  • Territorial data generation aids in optimizing the plastic waste collection supply chain.

Conclusions:

  • The developed smart collectors offer a viable solution for localized plastic waste recycling.
  • Real-time data and optimized logistics contribute to reduced environmental impact.
  • Future developments can further enhance the efficiency and scope of these systems.