Human-Machine Interface


Enabling intelligent systems in practice


With a long-standing track record in automotive and industrial applications, Melexis addresses these system-level requirements through a broad portfolio of sensing technologies, spanning far-infrared (FIR) arrays, inductive sensing, and magnetic solutions, including its Triaxis position sensing technology.


Unlike traditional Hall-based sensors that measure a single magnetic fi eld component, Triaxis technology captures three magnetic fl ux components (Bx, By, and Bz) within a single device. This enables accurate 2D and 3D position sensing, including rotary, linear, and joystick motion, while reducing dependence on complex mechanical alignment or magnet structures. Compared to mechanical sensing solutions, Triaxis sensors maintain accuracy across temperature variation, mechanical tolerances, and external stray magnetic fields, supporting stable performance in real-world conditions where consistency over time is critical.


In practice, this means enabling stable performance where it matters. While touchscreens have proliferated as feedback devices across both industrial and automotive


HMI systems, there are many functions where they remain unsuitable. Triaxis can be deployed within joysticks, precision jog wheels, and critical switches such as on/off controls, allowing tactile interaction to be combined with high-resolution, reliable 3D magnetic position feedback.


Within robotic systems, position sensing also exists within the control loop, for example in actuators, where measurement accuracy and timing directly infl uence motion stability and system response under continuous operation. Triaxis sensors are used in robotic joints, motor position sensing, and end- effectors, where compact integration and tolerance to mechanical variation are critical. Unlike optical encoders or contact- based solutions, they operate reliably in environments subject to dust, vibration, and thermal variation, maintaining consistent feedback under real operating conditions. Optical solutions can also introduce cost and integration overhead, particularly where alignment, protection, or environmental sealing is required. In contrast, magnetic sensing simplifies implementation while supporting smooth motion, repeatability, and accurate trajectory control in systems where


robustness and scalability are key design constraints. Ca pturing user input, however, is only one part of the challenge. In AI-driven systems, how this data is acquired, processed, and communicated is equally critical. Melexis’ sensors and magnetometers combine precise measurement with confi gurable digital outputs, enabling deterministic communication with microcontroller units (MCUs) in both centralized and distributed architectures. Integrated signal conditioning and diagnostic features further support system-level reliability, allowing faults, drift, or degradation to be detected and managed within the broader control system.


Conclusion


As AI systems transition from controlled digital environments into the complexity of the physical world, the defi nition of performance begins to shift. It is no longer suffi cient to optimize models in isolation; system capability is increasingly determined by how effectively real-world


signals are captured, validated, and acted upon.


In this context, sensing becomes the point at which uncertainty is either constrained or allowed to propagate. Measurement quality, timing, and resilience to environmental and electrical disturbance directly


infl uence how confi dently AI systems can operate, particularly in applications where autonomy, safety, and human interaction converge.


Looking ahead, the systems that succeed will not be those with the most advanced algorithms alone, but those that achieve balanced performance across sensing, processing, and control. This requires closer alignment between hardware and software, where sensing technologies are designed with system-level awareness and AI models are developed with an understanding of real-world measurement constraints. Melexis supports this transition through its portfolio of sensing solutions, enabling the reliable, high- quality data that next-generation AI systems depend on to operate with confi dence beyond the lab and into real-world deployment. https://www.melexis.com/


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Want to be part of the action? Then contact: Tony Patman | 01622 687031 | tpatman@cieonline.co.uk www.cieonline.co.uk Sophie Scott | 01622 699193 | sscott@cieonline.co.uk Components in Electronics May 2026 31


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