Recycle-Revolution as A Modular UX Framework for AI-Powered Sustainability Initiatives and Environmental Impact

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@article{1715710,
      author = {Emmanuel Adegbe},
      title = {Recycle-Revolution as A Modular UX Framework for AI-Powered Sustainability Initiatives and Environmental Impact},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {2847-2852},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715710.pdf},
      abstract = {The problem of the unmanageable waste crisis worldwide and the lack of recycling behavior efficiency shed more light on the limitations of current sustainability technologies and their tendency to focus on data gathering and information provision rather than on long-term behavioral change. The present work presents a conceptual modular UX design, Recycle-Revolution, which will incorporate artificial intelligence, behavioral science, and sustainability operations into a unified, behavior-forming ecosystem. The framework addresses typical issues of digital sustainability platforms, such as disjointed interfaces, poor engagement, poor habit formation, and limited ability to measure environmental impact, by integrating reinforcement and adaptive artificial intelligence into user-centered design. Recycle-Revolution is based on Sustainable Human-Computer Interaction, behavior change theory, AI-based personalization, and modular systems theory. It suggests a five-layer structure consisting of user experience interfaces, behavioral intelligence, AI intelligence, sustainability operations, and measurement of environmental impact. This framework enables repeated interaction loops, in which user behaviors are decoded by AI, strengthened by behavioral systems, and linked to processes in the real-world environment. Modularity is the property that guarantees scalability, interoperability, and adaptability across different environments (smart city environments, campuses, households, and corporate sustainability programs). Placing AI as an engine of behavioral adaptation, rather than a tool of pure analysis, the framework shifts sustainability technology from passive information delivery to active systems that can shape habits. In practice, Recycle-Revolution proposes a reusable, theoretically grounded model that can enhance the precision of recycling, foster long-term engagement, and generate data-driven feedback to inform environmental policy and planning. The framework illustrates how behavior-centered, modular UX design can bridge the gap between digital interactions and measurable environmental impact, enabling long-term sustainability.},
      keywords = {Behavior Change; Artificial Intelligence; User Experience (UX) Design; Recycling Behavior; Modular Systems Design; Sustainability Technology.},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715710}
  }