“Human-state data will become as strategic as vehicle telemetry”
Benjamin MüllerBenjaminMüllerInternational Editor for ADT, aIT, AP & All-Electr.
3 min
Neumo’s Niall Berkery on stage at the AUTOMOBIL-ELEKTRONIK Kongress in Ludwigsburg.Matthias Baumgartner
The more vehicles rely on AI and shared control, the more critical the driver’s actual cognitive state becomes. Niall Berkery, CEO and co-founder of Neumo, explains why cognitive-state sensing could become a key input for safer automation.
Niall Berkery is CEO and co-founder of Neumo, a company developing contactless brainwave-sensing technology for vehicles. At the 30th AUTOMOBIL-ELEKTRONIK Kongress, Berkery joined MicroVision CEO Glen de Vos on stage for the session “Technologies to Watch”.
ADT: Looking ahead three to five years, what will be the biggest bottleneck in turning SDV and AI strategies into scalable, industrialised vehicle platforms?
The biggest bottleneck will not be compute or AI models; it will be context. Today’s SDV platforms have unprecedented visibility into the vehicle, but very limited understanding of the human operating it. Without reliable, real-time insight into the driver’s cognitive state, AI systems are forced to make decisions based on external observations alone. To deliver safe, personalised and trustworthy automation at scale, vehicles need to understand not only what the driver is doing, but why. Industrialising SDVs requires integrating human-state intelligence as a native sensor input alongside cameras, radar and vehicle telemetry.
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Which decision being made today will most strongly determine where value is created in the future automotive ecosystem?
The defining decision is who owns the intelligence layer that interprets human behaviour. OEMs that own the relationship between vehicle perception, driver understanding and AI-driven personalisation will differentiate themselves far beyond horsepower or screen size. Human-state data will become as strategic as vehicle telemetry, enabling safer driving, more personalised experiences, adaptive automation and entirely new digital services. The winners will not simply collect more data; they will generate better insights.
Where do current approaches to SDVs and next-generation E/E architectures still fall short in real-world programmes?
Current SDV architectures are becoming increasingly software-centric, but they still rely heavily on camera-based observation of driver behaviour. Cameras can detect where a driver is looking or whether their eyes are closed, but they cannot directly measure cognitive workload, impairment, mental fatigue or attention capacity. As vehicles become more intelligent and increasingly share control with the driver, understanding cognitive readiness becomes essential. The missing sensor in today’s architecture is not another camera; it is a way to directly measure human cognitive state.
How is vehicle intelligence evolving beyond traditional computing concepts?
Niall Berkery holds a BSc in Electrical Engineering from the Dublin Institute of Technology. He began his career in Japan as an engineer and product planner before building and scaling companies in the automotive and mobility sectors, including leadership roles at Pioneer, Agero and TeleNav.Benjamin Müller
What defines the next generation of in-vehicle intelligence?
The next generation of in-vehicle intelligence will be multimodal. It will combine vehicle dynamics, environmental perception, occupant sensing and, critically, direct measurement of the driver’s cognitive state to create a real-time understanding of what is happening both inside and outside the vehicle. That enables vehicles to anticipate risk before it becomes visible behaviour, personalise the driving experience based on the driver’s condition and adapt automation to the driver’s readiness to take control. True intelligence begins when the vehicle understands the person, not just the machine.
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Where do you see the biggest breakthrough needed to unlock true vehicle intelligence?
The biggest breakthrough is moving beyond behavioural inference to direct measurement of cognitive state. The automotive industry has relied on cameras to infer whether a driver may be distracted or fatigued. But many of the highest-risk conditions, including cognitive overload, impairment, stress and mental fatigue, occur before they become externally visible. Neumo’s contactless brainwave-sensing technology represents a new sensing modality for the vehicle. By measuring neural activity directly from a headrest without requiring wearables, we provide real-time insight into driver condition that cameras cannot capture. We believe this human-state intelligence will become a foundational input for next-generation SDVs, enabling safer automation, more personalised mobility experiences and a fundamentally more intelligent vehicle.
