Artificial Intelligence Technology
Figure 4: Emotion recognition involves a 1:n comparison: the current image is compared with many different images. 3. Face print creation
A mathematical representation – the face print – is generated and encoded for comparison. 4. Local comparison
Instead of uploading data to the cloud, the system compares the face print with locally stored reference data (1:1 for ID verification, 1:n for emotion detection or group access). 5. Action triggered
If a match is found, the system triggers the intended process: opens a door, starts a machine, records a timestamp – all within milliseconds.
6. Optional: emotion recognition AI algorithms evaluate facial expressions to assess emotional states such as fatigue, stress, or satisfaction – useful for workload management and safety systems.
Why embedded AI – not the cloud? Many systems rely on cloud-based processing – which can raise concerns around latency, data protection, connectivity, and cost. Embedded AI offers key advantages: Processing at the edge: All data is processed locally on the device – no internet required.
Full GDPR compliance: No personal data leaves the site.
High-speed response: Actions occur within milliseconds – critical for real- time industrial control.
Energy efficiency: Suitable for mobile, battery-powered, or IoT applications.
Low maintenance: No subscriptions, server upkeep, or external infrastructure needed.
AITAD’s embedded systems integrate camera, processor, memory, and I/O on a single sensor board – smaller than a
Figure 5: In embedded AI systems, the sensor and computing unit are housed on a single board. This allows even very high data rates to be processed in real time without any compromises. The analysis results are simply transferred via an interface.
credit card – offering full functionality in a compact, industrial-grade unit.
Business case: fast ROI and scalable benefits
Embedded face recognition doesn’t just make factories smarter – it’s economically viable. Typical returns include: Reduced downtime by preventing unauthorised machine operation
Faster access and logins in production areas
Improved compliance in regulated industries
Eliminated physical media, reducing overheads
Boosted workplace safety, especially where fatigue or stress can lead to accidents
In times of labour shortages and increasing automation, facial recognition systems support smarter workflows and increase resilience – without increasing complexity.
Conclusion: a clear view towards Industry 4.0
Industry 4.0 demands not just connected machines, but connected people. Face recognition with embedded AI provides a secure, efficient, and intuitive bridge between humans and technology. Whether it’s for authorisation, quality assurance, or real-time monitoring, this technology delivers measurable benefits across sectors – from automotive and manufacturing to medical devices and logistics.
For organisations seeking to combine safety, convenience, and data protection in one solution, the answer may be staring them in the face.
www.aitad.de www.cieonline.co.uk Components in Electronics October 2025 15
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