A—CR | Closing the Construction Loop: A Platform for Scaling Sustainable Material Reuse

AI Quick Summary

Please read the long description.“Closing the Construction Loop” is a digital platform that enables large-scale reuse of building materials by integrating AI-based inventory analysis into early project planning. It streamlines the reuse process across stakeholders—owners, planners, contractors, and buyers—before demolition occurs. The platform reduces waste, emissions, and costs by transforming reuse from a reactive process into a coordinated, scalable strategy. Through open APIs and inclusive design, it connects existing marketplaces and supports new circular value chains. [Brief introduction of the idea]“Closing the Construction Loop” is a digital platform that enables large-scale reuse of building materials by integrating AI-based inventory analysis into early project planning. It streamlines the reuse process across stakeholders—owners, planners, contractors, and buyers—before demolition occurs. The platform reduces waste, emissions, and costs by transforming reuse from a reactive process into a coordinated, scalable strategy. Through open APIs and inclusive design, it connects existing marketplaces and supports new circular value chains.a. What challenge in the circular building and construction industry does your idea address? (max. 50 words)Our platform addresses the systemic inefficiencies in current material reuse processes. Existing exchanges are isolated and reactive, depending on post-demolition availability. This leads to storage burdens, delays, and underutilization of reusable components—limiting the ecological and economic potential of circular construction.b. What is your vision for solving this challenge, and why is your approach innovative? Who will benefit from a solution to this problem? (max. 200 words)Our vision is to make building material reuse a default practice by embedding it into the early planning stages of transformation and construction projects. The platform uses AI and machine learning to analyze building plans, inventories, and demolition quotes—automatically identifying reusable components and their value before materials are removed from site.This proactive, data-driven workflow is a radical departure from current models, which rely on ad hoc listings after demolition. By enabling reuse planning at scale and upstream, our solution eliminates costly storage, reduces design uncertainty, and accelerates adoption.Buyers benefit from advance visibility into available materials, enabling better design and logistics. Owners monetize existing inventory and avoid disposal costs. Contractor’s plan dismantling with accurate data. Planners and architects gain access to verified components with known dimensions, costs, and availability.What sets this platform apart is its systemic logic: it connects and enhances existing reuse exchanges, supports third-party integrations via open APIs, and creates a shared ecosystem for circularity. It fosters a new market infrastructure for reused materials—supporting not only environmental goals, but also innovation, entrepreneurship, and regulatory transformation.c. How could your idea positively impact the planet, people, or economy in the future? (max. 100 words)The platform prevents waste, reduces emissions from raw material extraction and new production, and promotes long-term circularity. It also supports healthier environments by reducing dust, toxins, and heavy waste logistics linked to demolition. The early, planned reuse of components extends their lifecycle, fosters new jobs in dismantling and reuse logistics, and reduces building costs—especially in resource-limited contexts. By opening access to reuse inventories, it supports social equity and local economies.d. What assumptions or ideas do you want to test? What do you plan to work on during the booster program, and what is your goal to deliver at the end? (max. 200 words)We want to test the assumption that early-stage reuse planning, enabled by automated inventory extraction, creates tangible value for key stakeholders in construction projects. Specifically, we aim to understand what information owners, planners, and contractors actually need to adopt reuse workflows—and how this can be integrated into their existing processes.During the booster program, we will focus on: • Engaging with potential users to assess platform usability, data expectations, and integration needs. • Validating key market needs, barriers, and motivators for using the platform. • Testing our AI-based methods for extracting and structuring reuse data from real project documents. • Gathering feedback from planners, buyers, and dismantlers to iteratively shape the platform’s logic and interface.As a result, we aim to deliver: • A validated platform prototype including the core functionalities (inventory extraction, reuse potential assessment, and component directory). • A clear articulation of user requirements and market fit. • A set of use cases based on interviews and pilot inputs. • A documented foundation for the next development phase—covering technical feasibility, user desirability, and practical implementation potential.e. Has your idea been tested before? If yes, what were the results, and what remains to be tested? (max. 100 words)Individual elements have been validated through prior research. Machine learning models have been used successfully for wall detection and inventory extraction from floorplans. Structured data extraction from quotes is feasible using OCR and language models. What remains is integrating these components into a functional tool, testing end-to-end usability across real users, and evaluating the platform’s effectiveness in facilitating reuse during a live case study.f. Who is in your team, and what expertise or roles do they bring? (max. 150 words)Felix von Overbeck (Architecture, HSLU) brings over 10 years of experience in UX/UI design and digital project management. Tim Schwander (Architecture, HSLU) contributes sociocultural design expertise and focuses on concept development and user engagement. Sven Reber (Architecture, HSLU) has eight years of practical experience in BIM-based modeling and execution planning, supporting the integration of reuse data into workflows. Lux Gianinazzi (PhD, ETH AI Center) is an expert in machine learning, language models, and graph algorithms and leads the technical backend. Our interdisciplinary team bridges architecture, data science, and design, working iteratively across practical, technical, and conceptual domains to drive circular building innovation. Our research partner is the Lucerne University of Applied Sciences. We are supported by a letter of endorsement from Prof. Dr. Andrea Weber-Hansen. Our implementation partner Y-VI combines computer science, neuroscience, and design to deliver customized AI solutions with high precision and performance.g. How do you plan to secure the 10% third-party funding required? (max. 100 words)We are in dialogue with academic and municipal stakeholders for in-kind contributions and co-financing of the pilot phase. Several partners in the reuse ecosystem—including building exchanges and construction firms—have expressed interest in supporting integration testing and real-world application. In parallel, we will approach environmental foundations and innovation-oriented sponsors who align with our goals of decarbonization, digitalization, and resource conservation in construction. These avenues are expected to fully cover the required 10% share.

Project Idea Metadata

• Project Idea Name: A—CR | Closing the Construction Loop: A Platform for Scaling Sustainable Material Reuse
• Date: 4/7/2025 3:28:54 PM
• Administrators:
  • Sven Reber

Project Idea Description

[Brief introduction of the idea]

“Closing the Construction Loop” is a digital platform that enables large-scale reuse of building materials by integrating AI-based inventory analysis into early project planning. It streamlines the reuse process across stakeholders—owners, planners, contractors, and buyers—before demolition occurs. The platform reduces waste, emissions, and costs by transforming reuse from a reactive process into a coordinated, scalable strategy. Through open APIs and inclusive design, it connects existing marketplaces and supports new circular value chains.

a. What challenge in the circular building and construction industry does your idea address? (max. 50 words)

Our platform addresses the systemic inefficiencies in current material reuse processes. Existing exchanges are isolated and reactive, depending on post-demolition availability. This leads to storage burdens, delays, and underutilization of reusable components—limiting the ecological and economic potential of circular construction.

b. What is your vision for solving this challenge, and why is your approach innovative? Who will benefit from a solution to this problem? (max. 200 words)

Our vision is to make building material reuse a default practice by embedding it into the early planning stages of transformation and construction projects. The platform uses AI and machine learning to analyze building plans, inventories, and demolition quotes—automatically identifying reusable components and their value before materials are removed from site.

This proactive, data-driven workflow is a radical departure from current models, which rely on ad hoc listings after demolition. By enabling reuse planning at scale and upstream, our solution eliminates costly storage, reduces design uncertainty, and accelerates adoption.

Buyers benefit from advance visibility into available materials, enabling better design and logistics. Owners monetize existing inventory and avoid disposal costs. Contractor’s plan dismantling with accurate data. Planners and architects gain access to verified components with known dimensions, costs, and availability.

What sets this platform apart is its systemic logic: it connects and enhances existing reuse exchanges, supports third-party integrations via open APIs, and creates a shared ecosystem for circularity. It fosters a new market infrastructure for reused materials—supporting not only environmental goals, but also innovation, entrepreneurship, and regulatory transformation.

c. How could your idea positively impact the planet, people, or economy in the future? (max. 100 words)

The platform prevents waste, reduces emissions from raw material extraction and new production, and promotes long-term circularity. It also supports healthier environments by reducing dust, toxins, and heavy waste logistics linked to demolition. The early, planned reuse of components extends their lifecycle, fosters new jobs in dismantling and reuse logistics, and reduces building costs—especially in resource-limited contexts. By opening access to reuse inventories, it supports social equity and local economies.

d. What assumptions or ideas do you want to test? What do you plan to work on during the booster program, and what is your goal to deliver at the end? (max. 200 words)

We want to test the assumption that early-stage reuse planning, enabled by automated inventory extraction, creates tangible value for key stakeholders in construction projects. Specifically, we aim to understand what information owners, planners, and contractors actually need to adopt reuse workflows—and how this can be integrated into their existing processes.

During the booster program, we will focus on:

• Engaging with potential users to assess platform usability, data expectations, and integration needs.

• Validating key market needs, barriers, and motivators for using the platform.

• Testing our AI-based methods for extracting and structuring reuse data from real project documents.

• Gathering feedback from planners, buyers, and dismantlers to iteratively shape the platform’s logic and interface.

As a result, we aim to deliver:

• A validated platform prototype including the core functionalities (inventory extraction, reuse potential assessment, and component directory).

• A clear articulation of user requirements and market fit.

• A set of use cases based on interviews and pilot inputs.

• A documented foundation for the next development phase—covering technical feasibility, user desirability, and practical implementation potential.

e. Has your idea been tested before? If yes, what were the results, and what remains to be tested? (max. 100 words)

Individual elements have been validated through prior research. Machine learning models have been used successfully for wall detection and inventory extraction from floorplans. Structured data extraction from quotes is feasible using OCR and language models. What remains is integrating these components into a functional tool, testing end-to-end usability across real users, and evaluating the platform’s effectiveness in facilitating reuse during a live case study.

f. Who is in your team, and what expertise or roles do they bring? (max. 150 words)

Felix von Overbeck (Architecture, HSLU) brings over 10 years of experience in UX/UI design and digital project management.

Tim Schwander (Architecture, HSLU) contributes sociocultural design expertise and focuses on concept development and user engagement.

Sven Reber (Architecture, HSLU) has eight years of practical experience in BIM-based modeling and execution planning, supporting the integration of reuse data into workflows.

Lux Gianinazzi (PhD, ETH AI Center) is an expert in machine learning, language models, and graph algorithms and leads the technical backend.

Our interdisciplinary team bridges architecture, data science, and design, working iteratively across practical, technical, and conceptual domains to drive circular building innovation. Our research partner is the Lucerne University of Applied Sciences. We are supported by a letter of endorsement from Prof. Dr. Andrea Weber-Hansen. Our implementation partner Y-VI combines computer science, neuroscience, and design to deliver customized AI solutions with high precision and performance.

g. How do you plan to secure the 10% third-party funding required? (max. 100 words)

We are in dialogue with academic and municipal stakeholders for in-kind contributions and co-financing of the pilot phase. Several partners in the reuse ecosystem—including building exchanges and construction firms—have expressed interest in supporting integration testing and real-world application. In parallel, we will approach environmental foundations and innovation-oriented sponsors who align with our goals of decarbonization, digitalization, and resource conservation in construction. These avenues are expected to fully cover the required 10% share.

Please read the long description.

“Closing the Construction Loop” is a digital platform that enables large-scale reuse of building materials by integrating AI-based inventory analysis into early project planning. It streamlines the reuse process across stakeholders—owners, planners, contractors, and buyers—before demolition occurs. The platform reduces waste, emissions, and costs by transforming reuse from a reactive process into a coordinated, scalable strategy. Through open APIs and inclusive design, it connects existing marketplaces and supports new circular value chains.