InnoTrace – Connecting Operational and Environmental Data for Automated EPD and LCA

InnoTrace is an innovation project that brings together technology developers and manufacturing companies to develop and pilot a method for automated, data-driven Environmental Product Declarations (EPDs) and Life Cycle Assessments (LCA). The project focuses on using industrial IoT sensors and a cloud-based data platform to collect, process, and contextualize both energy and production data directly from the shop floor.

The partners behind the project have already initiated the development of a modular IoT sensor system, including a 3-phase power sensor, as well as a digital platform for sensor data aggregation and visualization. Through this project, we aim to further develop these components, integrate them with real-time production data from MES and ERP systems, and demonstrate how they can be used to generate structured and accurate environmental data for EPD and LCA processes.

🧩 What We Will Do

Together with manufacturing partners, we will:

• Further develop and refine our IoT sensor system, focusing on industrial robustness, configurability, and scalability

• Continue building out our IoT data platform, adding integration capabilities with existing production systems (MES/ERP)

• Establish data pipelines that combine time-synchronized energy and production data on a per-batch or per-product basis

• Develop interfaces and data models that support structured export to EPD/LCA tools (e.g. ILCD, PEF, Digital Product Passport)

• Pilot the system in real manufacturing environments, demonstrating improved data quality, traceability, and reduced reporting effort

⚙️ Technology Scope

The technological foundation of the project includes:

• An in-development 3-phase IoT power sensor designed for plug-and-play use in industrial settings, with support for wireless communication (e.g. LoRaWAN)

• A modular IoT data platform, capable of collecting and managing large-scale sensor data streams

• Embedded AI and event logic, enabling local analysis of energy patterns and process anomalies

• APIs and integration layers for connecting with external systems and sustainability reporting tools

🎯 Project Objectives

1. Link operational data (energy + production) to environmental performance, enabling more accurate and real-time sustainability reporting

2. Reduce manual work and improve precision in EPD and LCA documentation

3. Provide a scalable architecture suitable for SMEs and larger factories alike

4. Demonstrate industrial pilots that validate technical, environmental, and business impact

5. Ensure compatibility with future EU requirements for transparency and product traceability (e.g. Digital Product Passport, CSRD)

💡 Innovation Highlights

• Fusion of real-time IoT sensor data with structured MES/ERP process data

• Application of embedded analytics for smarter, lower-latency environmental monitoring

• Built for interoperability and alignment with common EPD/LCA tools

• Designed to make sustainability reporting scalable, traceable and less resource-intensive

♻️ Expected Impact

• Easier and more precise EPD and LCA generation

• Increased transparency and trust in reported environmental metrics

• Lower threshold for compliance with green regulations, especially for SMEs

• Improved ability to act on environmental insights in production

👥 Who Should Be Involved

• Manufacturers interested in automating and improving sustainability reporting

• Technology developers focused on IoT, MES/ERP integration, or digital twins

• EPD and LCA tool providers seeking high-quality, real-world data sources

• Research actors working on circular economy, digital product passports, or green innovation