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Towards a Smarter Waste Management: Developing and Evaluating a Smart Waste Management Decision Support Framework

Author

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  • Inna Sosunova

    (Lappeenranta–Lahti University of Technology, Finland)

  • Ari Happonen

    (Lappeenranta–Lahti University of Technology, Finland)

  • Annika Wolff

    (Lappeenranta–Lahti University of Technology, Finland)

  • Jari Porras

    (Lappeenranta–Lahti University of Technology, Finland)

Abstract

The study 1) explores how to develop an IoT-based smart waste management (SWM) system that improves the waste management processes of a city and 2) researches how to develop SWM system improvement and evaluation decision support framework (DSF), that guides how to achieve all major WM-related goals, applies to different types of cities with different contexts and is not restrained to a single country or region. This study combines in one framework theoretical research, surveys with key WM stakeholders, practical research from international projects and hackathons, and practical knowledge from interviews with city authorities and companies responsible for waste management in the world's greenest cities. The SWM DSF has been tested and evaluated in three stages: 1) by researchers, 2) by a panel of experts, and 3) by representatives of the city administration of two Finnish cities.

Suggested Citation

  • Inna Sosunova & Ari Happonen & Annika Wolff & Jari Porras, 2024. "Towards a Smarter Waste Management: Developing and Evaluating a Smart Waste Management Decision Support Framework," International Journal of Social Ecology and Sustainable Development (IJSESD), IGI Global, vol. 15(1), pages 1-36, January.
    • Handle: RePEc:igg:jsesd0:v:15:y:2024:i:1:p:1-36
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