In our first blogpost, we introduced the ECS-Chip project and the motivation behind it: corrosion remains one of the most underestimated and least predictable threats to electronics operating in harsh environments. While failures are often visible, the processes leading up to them rarely are. The ambition of ECS-Chip is to change that by enabling insight before damage occurs.
Six months on, the project has reached a natural next step. The exploratory and alignment work is complete, and the collaboration is now moving from pre-development into active development and prototype testing.
Aligning the foundations
The past months have focused on writing proof of concept code and testing system dependencies before putting it all together and deploying any systems in the field. What exactly needs to be built? How will different users interact with the system? What kind of data is required to support predictive insights - and how should it flow through the system?
For Antire, this phase was about system thinking rather than feature building. The team worked closely with the project partners to define roles, interfaces, and responsibilities, while translating research-driven objectives into something that can be supported by a robust digital architecture.
A key milestone in this phase was establishing reliable communication with the sensor hardware at development-board level. While still early-stage, this confirmed that data can be transferred from the physical device into a digital environment in a controlled and secure way. That validation marked the end of pre-development and gave the confidence needed to move forward.
At this point, the project partners are aligned on how to move forward from design into implementation, ensuring a coordinated transition from early concepts to practical development work.
Project partners
Bringing together a collaborative team, funded by EUDP.
Building the system before the prototype
One of the defining characteristics of the ECS-Chip project is that much of the digital infrastructure must be ready before the final sensor prototype exists.
Antire is currently developing the architecture that will handle data ingestion, processing, and visualization once real measurements become available. The setup is based on field gateways that connect to the sensor devices and forward data into a central application environment, where it can be structured, stored, and later analyzed using machine learning and AI models developed by DTU.
At this stage, development and testing are primarily local. The team is working with simulated and development-board data to validate integrations, system behavior, and configuration flows. This approach allows technical decisions to be tested early, without being dependent on final hardware availability.
Flexibility remains a core design principle. The system is designed to support both cloud-based and on-premise deployments, ensuring it can adapt to different operational and regulatory contexts across industries.
Choosing focus to enable progress
An important theme throughout this phase has been focus.
Early discussions naturally included a wide range of possible use cases, always-connected monitoring, offline operation, edge-only analytics, and combinations of the above. Rather than attempting to solve everything at once, the team made a deliberate decision to prioritize one primary use case and build the system around that.
This allows the architecture to remain modular and extensible, while avoiding unnecessary complexity at an early stage. The goal is not to deliver a fully finalized solution today, but to establish a solid, adaptable foundation that can evolve as the project progresses.
Battery-powered operation and low measurement frequency are part of this thinking as well. Environmental and corrosion-related processes develop slowly, which means meaningful insight can be generated without continuous high-frequency data collection. This supports longer device lifetimes and simpler deployments, both important considerations for real-world use.
What comes next
With pre-development complete, the project is now firmly in its development phase. The coming months will focus on integrating system components, refining data handling, and preparing for prototype testing.
The aim is that by the end of September, the first integrated prototype - combining hardware, connectivity, and software - will be ready to be shared with industrial partners for testing and validation. That milestone will mark the transition from internal development to external learning in real operational contexts.
And with that, the story naturally continues.
This second blogpost marks the bridge between concept and execution. The next chapter will focus on what happens when the system leaves the lab environment and begins interacting with real-world conditions and what that teaches us about predicting corrosion before it becomes a failure.
This EUDP funded project brings together a collaborative team: PAJ Group, who are leading the hardware design, manufacturing and industrialization; DTU, focusing on R&D, testing, qualification, calibration, and develop a AI machine learning (ML) model to interpret sensor data; and Antire, ensuring the stable and secure dataflow between the sensor and the AI/ML model, and the end-users.
Access here the first ECS-Chip post where we introduce the full project.
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