Enabling technology to accelerate your innovation

We have a vast library of both deep learning and classical computer vision algorithms that can be easily optimized and adapted for your use case. This includes detection and classification, tracking, segmentation, anomaly detection, tracking, image registration, and many more.

To look into active burners, we deployed our shear interferometer technology. This allows for an accurate view on small stress locations in the materials under heavy thermal load.

To investigate nozzle effectiveness and the impact of flow characteristics, we used our patent Schlieren technology. This technology provides insights on how and when the thermal boundary layer was reduced maximally.

This smart wearable tech can detect anomalies in people behavior and then notify caregivers. Its intuitive interface with voice control is ideal to support people with special needs allowing multi-modal communication integration trough text, voice or video.

This high-quality silicon image sensor maintains a minimal footprint, while maintaining radiation hardness & performing in demanding environments. Developed by ISAE-SUPAERO, this ultra-compact camera can be used in nuclear power plant inspections, monitoring & decommissioning or deep space missions.

Contactless identification technologies such as facial recognition have boosted tremendously during the pandemic. But what about people’s privacy? Our computer vision technology detects masks, estimates distances, detects and counts people. Because the data is processed locally, no image ever leaves the sensor.

This DEXO product combines a force-feedback exoskeleton arm, software and a control center. With DEXO, complex robotic teleoperations are made more intuitive and effective thanks to its capability to render force or guidance information during operations. Associated with virtual or augmented reality rendering, these technologies can also be useful in interactive training, upper body rehabilitation and remote operations in dangerous surroundings.

Based on our experience in reference design and design knowledge to apply in IoT devices, we developed a state-of-the-art 3D antenna for 2.5GHz Wi-Fi. Wi-Fi with great range and coverage were essential for the lowest cost of goods possible meeting certification requirements.

Monte Carlo simulations can be verified quickly and efficiently based on IMU data. Our technology will deduce a predicted trajectory and help determine the incrementation of errors.

Our video and audio router technology platforms ensures the highest quality of data transmission, low latency and jitter design measures, for flawless Wi-Fi QoS.

This e-Xstream software provides the unique combination of material engineering, process simulation and structural engineering to bring additive manufacturing efficiency and performance to the next level.

This software tool developed by Componeering designs conceptual and preliminary fiber-reinforced layered composite laminates structures, and analyses mechanical and thermic properties.

The Gallium-Nitride (GaN) gate driver, developed by MinDCet is an integrated circuit which improves high-performance power supply and battery systems. This makes it ideal for efficient power supplies.

This SABCA flight control actuation system can be used in heavy machinery for manufacturing, construction and transportation. The core parts include the specialized control processor, electronics and embedded control algorithm software.

This SABCA radiation-hardened processor intended for hard real-time processing, can be used in mechanism control, power control, robotics, positioning systems, medical devices and other sectors that need reliable instrument control.

This multi-sensory AI system (based on machine learning) analyzes measurement data and compares it with personal threshold values. With this information it can generate an automatic alarm where necessary so that the treatment can be adjusted based on the current state of health.

The oil degraded working of gearboxes is characterized by different vibrations when compared to nominal behavior. The ML we developed is built to detect the difference between both states very accurately.

Detecting, localizing and measuring distance of objects, posture, people, vessels, and many more. This technology is LIDAR or RGB-D-based and segments objects out of the point cloud. Special model-based algorithms focus on capturing movement dynamics.

This 16-bit digital, I2C temperature sensor with high-accuracy and low-drift omits (re)calibration. It’s ideal for industrial and medical sectors because low-power use, long-term stability and reliability.

Our flow control elements and system design could be used to control fluid flow and pressure in truck cooler coolant control valve selection, water pipe connector design, immersed corrosion sensor housing design, compressor inlet T sensor and more.

Our thermal control system can be configured in multiple applications such as algorithm development (compressor inlet temperature sensor module), flow control, sensor noise filtering and drift compensation (corrosion sensor), virtual sensors and sensor fusion.

By classifying samples (data blocks) from a data set with a bearing errors (BEAF), we set up an ML where the probabilities for all classes are plotted. Based on this information we can detected several types of errors and improve maintenance of these structures.

Our Optical Coherence Tomography (OCT) technology has been customized so it can scan larger arteries to measure blood flow, lumen and other clinical parameters. In addition, this OCT scans those parameters in 3 dimensions.

We built an ex vivo blood vessel measurement device based on Optical Coherence Tomography, so you can look deeper into the skin and even below. This allows measuring blood flow rates in 3D with lumen sizes.

Differential Interference Contrast (DIC) is a well-known optical microscopy technique to improve contrast unstained transparent samples. Our design IP ranges from visual to IR images with space optimization in the same optical column.

We designed a grinding feed ML to ensure grinding wheels could last longer and could not be used once worn out. This feed was based on data from three 3D accelerometers and an ML with the appropriate vector functions to distinct between two states.

Since 2000, Verhaert has been developing and optimizing advanced IMU sensor nodes. Our IPO building blocks cover orthogonalization, offsetting, calibration and optimized Bayesian estimation algorithms for several applications.

This critical environment evaluation solution simulates both digital control domain and physical simulation domains at the same time. As a result critical environments, for example of building setups, can be evaluated more quickly.

A custom laser scanning confocal microscope was developed and built for ESA to investigate cell behavior in orbit. In addition, we had to make sure it could withstand the extreme space conditions.

Verhaert owns IPs to process PPG signals on several levels into relevant clinical and lifestyle information. Our IP covers optical improvements through polarization, multispectral signal correlation and anomaly rejection due to movements and artifacts.

When compared to other impedance sensors, the IP of Verhaert is situated on the principle of mutual coupling. These sensors provide an enhanced way of measuring distance that eliminates the drawbacks from classic impedance measurements.

This low cost sensor for aquatic environments measures the 3D distance between 2 sensor nodes, delivering distance and 2 angles (horizontal & vertical). It avoids having complex triangulation processing and uses a ‘hello’ pulse from both sides.

For fire prediction, propagation within a phase and evolution from one to another is much more important than detecting the stage of the fire. An ML with several classes can determine the speed of propagation from one state to another.