The next generation of quantum sensors goes even further: navigation that works without GPS signals and therefore can’t be jammed, subsurface gravity mapping to detect underground voids, water resources and mineral deposits, and, further out, research-stage applications such as chemical and biological sensing. But as this technology steps out of controlled laboratories, how close are we to seeing quantum sensors transform our everyday world?

The physics behind quantum sensing

Traditional sensors measure macro-level mechanical or electrical changes, and engineers invest substantial resources in shielding these instruments from external ‘noise’, such as temperature fluctuations, vibration or electromagnetic signals.

But quantum sensors take a different approach. They use quantum elements like neutral atoms, electron spins, and photons to measure tiny environmental changes. Since a quantum state is highly sensitive to its surroundings, the very disturbance you want to measure appears clearly in the signal. And because these particles are identical everywhere and fixed by nature, quantum sensors don’t drift the way classical sensors do and need far less recalibration.

The basic process is surprisingly simple: initialize the quantum state, let it interact with what you want to measure, then read out the change.

Why it’s interesting now

Three things are converging.

First, the tech components needed to build quantum sensors are becoming smaller, cheaper and more accessible. Advances in silicon, optics, lasers, materials and computing are turning technologies that once belonged almost exclusively in laboratories into engineering platforms.

Second, demand is growing for measurements conventional sensors can’t provide. GPS, for example, is vulnerable to jamming and spoofing. Quantum gravimeters, magnetometers and inertial sensors offer potential alternatives for positioning and navigation without relying entirely on satellite signals.

Third, governments are investing heavily in the technology. The EU Quantum Technologies Flagship has committed an expected €1 billion over ten years across quantum computing, communication, simulation, sensing and metrology.

The result: quantum sensing is shifting from academic research towards commercially relevant products and protected IP.

Four sectors, four live opportunities

As quantum sensing matures from laboratory breakthroughs into market-ready hardware, four key industries are uniquely positioned to capture immediate, high-value opportunities:

1. Defense & aerospace

GPS-denied navigation: Quantum accelerometers and gyroscopes could let submarines, aircraft and defense systems navigate without satellite signals. With no external signal, there is nothing to jam. Long-term accuracy is still being proven and these systems are in field trials, but programs such as Lockheed Martin’s DARPA contract with AOSense and Q-CTRL are working towards deployment.

Secure, ultra-precise timing: Chip-scale atomic clocks are no longer theoretical. They are actively deployed in the field within military GPS receivers, unmanned aerial vehicles (UAVs) and secure communication arrays to maintain mission-critical synchronization in electronic warfare environments.

2. Medical imaging

Wearable, next-gen scanners: Optically pumped magnetometers (OPMs) enable high-resolution brain and fetal heart imaging without the cryogenic cooling required by traditional SQUID systems. Magnetic shielding is still typically needed, so this is a step towards point-of-care diagnostics, not a full replacement of hospital systems. 

3. Civil engineering & geophysics

Subsurface gravity mapping: Quantum gravimeters map microscopic density changes beneath Earth’s surface that traditional seismic imaging fails to detect. Commercial pioneers such as Muquans (Exail) and AOSense are conducting field trials with major energy companies for deep-reservoir monitoring, sinkhole prevention and mineral exploration.

4. Automotive

Battery current mapping: Quantum sensors can track current inside EV battery packs, from milliamps to kiloamps, without drift or recalibration. This has been demonstrated and could provide an estimated 10% increase in range, but it is still moving from demonstration to product.

From physics lab to commercial reality

If there’s so much potential, why aren’t quantum sensors everywhere yet?

Proving something in a lab is different from making a product, and the hurdles don’t hit every sensor equally.

Some are already practical. Atomic clocks, gravimeters and the SQUID magnetometers used in hospitals are mature products you can buy today, with chip-scale atomic clocks starting around $2,000. Room-temperature magnetometers are close behind, held back mainly by manufacturing scale. Navigation sensors are in field trials, while chemical sensing remains a research goal.

For that second group, three challenges stand out:

• Complete systems, not single parts. Quantum sensors need lasers, vacuum chambers, cooling and electronics working together. That doesn’t fit a normal supply chain and is costly to scale, though chip-scale clocks show miniaturization can help.
• Sensitivity cuts both ways. The same sensitivity that makes them powerful also means that heat, stray magnetic fields and vibration can disrupt the quantum state, a phenomenon known as decoherence. Shielding the sensor and extracting a clean signal is a large part of the engineering effort.
• Cost. Defense-grade systems cost $50,000 to $500,000, while classical sensors continue to improve and maintain a 10x to 100x cost advantage. If quantum sensors don’t approach cost parity by around 2030, adoption may stay limited to cases where no classical option exists.

Are you ready for the quantum shift?

Quantum sensing is not a single technology on a single timeline. Some of it is already here, some is a few years out, and some is still in the lab. Just as early computers evolved from room-sized machines into handheld devices, engineers are working through the remaining hurdles, and the most promising uses are those where no classical sensor can do the job at all.

At Verhaert, we help forward-thinking businesses prepare for this shift. By combining feasibility evaluations, system integration concepts and physics lab prototyping, we bridge the gap between emerging science and realistic product roadmaps, paving the way towards the quantum future.

The post Making sense of the future: Understanding the potential of quantum sensors appeared first on Verhaert Masters in Innovation.

The evolution from IoT to AIoT

In the history of embedded systems, we have moved from the discrete digital logic of the 1960s to the hyper-connected IoT era of the late 2000s, enabled by the ability to connect even small devices reliably to the cloud. This connectivity unlocked entirely new classes of applications, but it also introduced a strong dependency on continuous communication.

Today, we are seeing the next evolution with AIoT (Artificial Intelligence of Things). Advances in hardware and software now make it possible to embed intelligence directly at the edge, allowing devices to operate more autonomously and remain functional even when cloud connectivity is limited or temporarily unavailable. In practice, this leads to hybrid architectures where local intelligence complements the cloud rather than replaces it.

As expectations for ‘smart’ products continue to rise, addressing this paradox within fixed time and budget constraints requires a shift in design philosophy. This shift involves combining the right state-of-the-art technologies to increase engineering efficiency and reduce development complexity.

The rise of the crossover MCU: Bridging the power-performance gap

For years, engineers had to choose between the efficiency of a smaller and more integrated Microcontroller (MCU) and the high-performance complexity of an Application Processor (MPU). The emergence of so-called crossover MCUs has broken this dichotomy. By integrating multiple heterogeneous cores – such as a Cortex-M7 for performance and a Cortex-M4 for real-time tasks – these chips now offer MPU-level power with MCU-level efficiency.

This shift allows us to move away from expensive, power-hungry System-on-Modules (SOM) while retaining the ‘number-crunching’ ability needed for advanced encryption and on-device (artificial) intelligence.

Zephyr: The new standard for embedded portability

As MCUs become more complex, software must become more abstract. The Zephyr RTOS is becoming the “Linux of the embedded world”. Its vendor-independent architecture allows developers to write code that isn’t tied to a specific piece of silicon. Zephyr supports over 900 starter kits, demonstrating its broad adoption across MCU architectures and platforms.

In a landscape where regulatory requirements are becoming mandatory, Zephyr’s built-in security features, from secure boot to encrypted over-the-air (OTA) updates, provide more standardized options for compliance that was previously a custom-build challenge.

The edge AI paradigm: Intelligence without the tether

One of the defining characteristics of next-generation smart products is the ability to process data locally through Edge AI. Rather than relying exclusively on cloud-based intelligence, devices can make decisions closer to where data is generated.

This approach addresses several challenges associated with cloud-dependent IoT architectures, including:

• Latency: Local processing enables faster response times for time-critical actions.
• Privacy: Sensitive data remains on the device, reducing exposure and increasing user trust.
• Energy efficiency: Limiting high-bandwidth data transmission can significantly reduce power consumption.

Recent advances in AI techniques now allow complex neural networks to be optimized so they can run efficiently on cost-effective, low-power hardware.

The compliance catalyst: The role of the Cyber Resilience Act

Meeting high product requirements now includes meeting a new legal reality: the European Cyber Resilience Act. Security can no longer be a ‘patchwork’ effort added late in the cycle; it must be an architectural pillar.

The synergy of this ‘power trio’ provides a strategic path to compliance:

• Hardware-rooted trust: Crossover MCUs provide the physical foundation for secure boot and native encryption.
• Lifecycle management: Zephyr enables the secure OTA updates required to manage vulnerabilities throughout a product’s mandated support window.
• Data sovereignty: Edge AI naturally aligns with privacy-first mandates by reducing the attack surface of the product.

From complexity to synergy

The challenge of modern product development is that sophisticated features often lead to technical complexity, longer development cycles and higher costs. At the same time, products must meet increasingly strict security and regulatory requirements, often invisible to the end user, but critical for market access and long-term viability.

Understanding how the synergy between crossover hardware, scalable OS layers and edge intelligence can reduce engineering effort is key to delivering products that are intuitive and powerful, but also secure and compliant by design.

We are moving toward a future where ‘smart’ is no longer a feature, but an inherent, autonomous quality that evolves over time.

The post Beyond “connected”: The architecture of the next generation of intelligence appeared first on Verhaert Masters in Innovation.

Edge AI makes products think smarter

Edge AI brings artificial intelligence directly to the device, or “the edge”, rather than relying solely on internet communication and cloud computing. Sensors, IoT devices and embedded systems can process data locally, make real-time decisions and adapt their behavior instantly. By offloading computation from the cloud, Edge AI enables faster responses, lower latency, reduced data transfer and improved privacy; all while optimizing power consumption and performance for embedded devices.

Why Edge AI makes your product breakthrough

Edge AI isn’t just about smarter technology; it’s about overcoming the everyday limitations that stop products from reaching their full potential.

• Limited or unstable data connections?
  Traditional cloud-based AI struggles when connectivity is poor. Edge AI makes real-time decisions locally, ensuring your product functions intelligently anywhere, anytime, without relying on constant internet access.
• Simple sensors, big insights
  Even basic sensors can deliver high-end performance with Edge AI. Through sensor fusion, devices combine data from multiple sources to act as virtual, intelligent sensors. For example, a washing machine can estimate drum fill by analyzing vibration and motor sound, avoiding the need for supplementary (more expensive) weight sensors.
• Need a longer product lifetime?
  Edge AI continuously monitors product health, predicting maintenance needs before failures occur. Changes in sound or vibration patterns can indicate wear in critical components, extending the product’s lifetime and reducing costly downtime.
• User interaction matters
  Edge AI enables local processing of audio and video, allowing products to interact intuitively with users while preserving privacy. From personalized feedback to detecting behaviors in sensitive environments (like for example, smoking detection in toilets), devices become smarter and more user-friendly.
• Harsh environments or complex interfaces?
  Edge AI supports intuitive interaction even in challenging conditions. Industrial terminals, for instance, can recognize hand movements contactlessly, ideal when workers wear thick gloves, making conventional touchscreens ineffective.

Turning Edge AI into customer value

By addressing these product-level challenges, Edge AI drives multiple benefits that customers care about:

• Improved user experience with immediate, intuitive responses.
• Personalized interfaces and automated behavior insights.
• Stronger privacy as raw data remains on the device.
• Predictive maintenance that reduces downtime and operational costs.
• Sustainability through lower energy consumption and optimized local processing.
• Enhanced business insights for smarter product evolution.

From concept to market: Making innovation happen

At Verhaert, we integrate AI and embedded systems seamlessly, from concept to market-ready solutions. Our multidisciplinary teams ensure high performance, low power consumption, secure data handling and intuitive interfaces. With Edge AI, we don’t just build devices, we create breakthrough technology that transforms user experience, strengthens customer relationships and positions your product as a market leader.

Unlock the full potential of your products. Harness Edge AI to innovate smarter, faster and more sustainably, while delighting users and reducing costs.

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