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Digitalization, Circular Economy and Environmental Sustainability: The Application of Artificial Intelligence in the Efficient Self-Management of Waste

Author

Listed:
  • Sergio Luis Nañez Alonso

    (Department of Economics-DEKIS Research Group, Catholic University of Ávila, Canteros St., 05005 Ávila, Spain)

  • Ricardo Francisco Reier Forradellas

    (Department of Economics-DEKIS Research Group, Catholic University of Ávila, Canteros St., 05005 Ávila, Spain)

  • Oriol Pi Morell

    (FIHOCA-Costaisa, Riera de Cassoles St. 61, 08012 Barcelona, Spain)

  • Javier Jorge-Vazquez

    (Department of Economics-DEKIS Research Group, Catholic University of Ávila, Canteros St., 05005 Ávila, Spain)

Abstract

The great advances produced in the field of artificial intelligence and, more specifically, in deep learning allow us to classify images automatically with a great margin of reliability. This research consists of the validation and development of a methodology that allows, through the use of convolutional neural networks and image identification, the automatic recycling of materials such as paper, plastic, glass, and organic material. The validity of the study is based on the development of a methodology capable of implementing a convolutional neural network to validate a reliability in the recycling process that is much higher than simple human interaction would have. The method used to obtain this better precision will be transfer learning through a dataset using the pre-trained networks Visual Geometric Group 16 (VGG16), Visual Geometric Group 19 (VGG19), and ResNet15V2. To implement the model, the Keras framework is used. The results conclude that by using a small set of images, and thanks to the later help of the transfer learning method, it is possible to classify each of the materials with a 90% reliability rate. As a conclusion, a model is obtained with a performance much higher than the performance that would be reached if this type of technique were not used, with the classification of a 100% reusable material such as organic material.

Suggested Citation

  • Sergio Luis Nañez Alonso & Ricardo Francisco Reier Forradellas & Oriol Pi Morell & Javier Jorge-Vazquez, 2021. "Digitalization, Circular Economy and Environmental Sustainability: The Application of Artificial Intelligence in the Efficient Self-Management of Waste," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:2092-:d:500049
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    References listed on IDEAS

    as
    1. Ricardo Francisco Reier Forradellas & Sergio Luis Náñez Alonso & Javier Jorge-Vazquez & Marcela Laura Rodriguez, 2020. "Applied Machine Learning in Social Sciences: Neural Networks and Crime Prediction," Social Sciences, MDPI, vol. 10(1), pages 1-20, December.
    2. Cristina Calvo-Porral & Jean-Pierre Lévy-Mangin, 2020. "The Circular Economy Business Model: Examining Consumers’ Acceptance of Recycled Goods," Administrative Sciences, MDPI, vol. 10(2), pages 1-13, May.
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    Citations

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    Cited by:

    1. Jing Shao & Cedric Aneye & Alyona Kharitonova & Wei Fang, 2023. "Essential innovation capability of producer‐service enterprises towards circular business model: Motivators and barriers," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4548-4567, November.
    2. Robertas Damasevicius, 2023. "Progress, Evolving Paradigms and Recent Trends in Economic Analysis," Financial Economics Letters, Anser Press, vol. 2(2), pages 35-47, October.
    3. Tan Yigitcanlar, 2021. "Greening the Artificial Intelligence for a Sustainable Planet: An Editorial Commentary," Sustainability, MDPI, vol. 13(24), pages 1-9, December.
    4. Chauhan, Chetna & Parida, Vinit & Dhir, Amandeep, 2022. "Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    5. Sehrish Munawar Cheema & Abdul Hannan & Ivan Miguel Pires, 2022. "Smart Waste Management and Classification Systems Using Cutting Edge Approach," Sustainability, MDPI, vol. 14(16), pages 1-21, August.
    6. Rohit Agrawal & Vishal A. Wankhede & Anil Kumar & Sunil Luthra & Abhijit Majumdar & Yigit Kazancoglu, 2022. "An Exploratory State-of-the-Art Review of Artificial Intelligence Applications in Circular Economy using Structural Topic Modeling," Operations Management Research, Springer, vol. 15(3), pages 609-626, December.

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