FLEXOO at ICFPE 2026: Flexible sensor systems for Physical AI

2026-08-14

FLEXOO invited to speak in OE-A session at ICFPE 2026

FLEXOO has been invited to present at the 16th International Conference on Flexible and Printed Electronics (ICFPE 2026), one of the leading international events for flexible and printed electronics.

As part of the OE-A Session, Dr. Jan Birnstock, CTO of FLEXOO, will deliver a presentation on how flexible sensor systems enable real time multimodal monitoring in complex applications.

Physical AI requires a new data layer

As AI increasingly moves beyond digital environments and into the physical world, access to high-quality real-world data is becoming a critical challenge.

At FLEXOO, we believe that future intelligent systems require a new physical data layer capable of capturing relevant physical information directly where processes and interactions occur. Flexible, large-area sensor systems can provide this foundation, enabling continuous monitoring across previously inaccessible surfaces and components.

From sensing to physical intelligence

The presentation will explore how flexible sensor technologies can capture the data required for next-generation Physical AI applications.

By combining multiple sensing modalities within ultra-thin, large-area sensor architectures, these systems can provide real-time insight into physical states and interactions that are difficult to capture using conventional approaches.

Rather than relying solely on isolated measurements, flexible sensor systems enable distributed sensing across large surfaces, creating new opportunities for intelligent monitoring, prediction and control.

Applications in robotics and battery systems

The presentation will highlight how these technologies can be applied in two rapidly evolving fields.

In robotics, flexible sensor systems provide detailed information directly at the point of interaction and support tactile-first approaches to Physical AI.

In battery energy storage systems (BESS), they enable real-time, cell-level intelligence for predictive monitoring, safety enhancement and system optimization.

Although these applications differ significantly, they share a common challenge: the need for better physical data to support intelligent decision-making.