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This paper describes an urban experimentation initiative developed within the Fenicia Urban Living Lab (ULL) in Bogotá, Colombia, aimed at validating a technological innovation management model through a participatory cyber-physical system (CPS) for urban waste management. The model is designed to support the co-creation of socio-technical solutions in smart cities, especially in developing contexts. The experiment involves residents, drones, and mobile applications to generate georeferenced images of street waste, which are analyzed by a custom AI model to classify waste types and identify critical accumulation points. These insights are integrated into a Digital Twin (DT) platform built on 3D spatial models and geospatial analysis tools. The CPS is evaluated using a KPI framework aligned with three strategic objectives: Quality of Life, Productivity, and ICT-based Sustainability. Preliminary results show improved detection efficiency, increased citizen engagement, and the potential for data-driven decisions at the neighborhood level. Additionally, governance acts as a transversal enabler, strengthening stakeholder coordination and institutional learning. This paper advances the literature on Urban Living Labs and socio-technical experimentation by validating the proposed innovation management model in real urban conditions. It also expands the Waste–Energy–Information nexus, demonstrating how digital twins and participatory sensing can promote inclusive and circular urban transformations.

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From Data to Decision: Validating a Technological Innovation Management Model Through a Digital Twin-Based Waste Experiment in an Urban Living Lab

  • 会议论文

  • 发表日期：

    2026年

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  • Augusto Velasquez-Mendez,
  • Jorge de Jesús Lozoya-Santos,
  • José Fernando Jimenez-Vargas,
  • Juand David Salguero-Medina,
  • Gabriel Felipe Dicelis-Ramos,
  • Juan Esteban Cardona Quinto,
  • Francisco Alejandro Santamaria-Ibarra,
  • Andrés Felipe Manrique-Moreno

摘要

This paper describes an urban experimentation initiative developed within the Fenicia Urban Living Lab (ULL) in Bogotá, Colombia, aimed at validating a technological innovation management model through a participatory cyber-physical system (CPS) for urban waste management. The model is designed to support the co-creation of socio-technical solutions in smart cities, especially in developing contexts. The experiment involves residents, drones, and mobile applications to generate georeferenced images of street waste, which are analyzed by a custom AI model to classify waste types and identify critical accumulation points. These insights are integrated into a Digital Twin (DT) platform built on 3D spatial models and geospatial analysis tools. The CPS is evaluated using a KPI framework aligned with three strategic objectives: Quality of Life, Productivity, and ICT-based Sustainability. Preliminary results show improved detection efficiency, increased citizen engagement, and the potential for data-driven decisions at the neighborhood level. Additionally, governance acts as a transversal enabler, strengthening stakeholder coordination and institutional learning. This paper advances the literature on Urban Living Labs and socio-technical experimentation by validating the proposed innovation management model in real urban conditions. It also expands the Waste–Energy–Information nexus, demonstrating how digital twins and participatory sensing can promote inclusive and circular urban transformations.