Multi-modal sensing and edge AI systems
One accountable team for the hardware and the AI: ruggedised sensor units, synchronised channels and inference that runs at the machine.
A single microphone is easy to fool. Fusion is the engineering answer
A single microphone is easy to fool. A forklift passes, a compressor two bays away cycles, a door slams, and an acoustic monitor that looked excellent in the lab starts producing alerts nobody can explain. Fusion is the engineering answer: the accelerometer that felt nothing tells you the sound did not come from the asset.
With our industrial partner NeuroControls GmbH we co-develop sensor units that cover vision, audio from audible to ultrasonic, vibration, lidar and environmental sensing across the NeuroControls platform — with the inference running on the unit rather than in a data centre. Synchronisation is not a detail: without a shared clock across channels, fusion is guesswork.
Deployment is deliberately incremental. One pilot line first, integrated with your PLC, SCADA or MES, running long enough to see a shift change, a product change and a maintenance event. Then roll-out.
What is included
Sensor selection, placement and synchronisation across modalities; ruggedised sensor units and data acquisition from NeuroControls GmbH; sensor-fusion models; inference on the edge device; alerts and dashboards; integration with PLC, SCADA or MES; handover to your OT/IT team. Delivered as a pilot line first, then roll-out.
Sensor selection and placement
Chosen for the failure mode, not the catalogue, and positioned with the enclosure, the noise sources and the maintenance access in mind.
Synchronised multi-modal acquisition
Channels sampled on a shared clock so fusion models see the same event at the same instant.
On-device inference
Models sized for the unit's compute and power budget, with latency and memory measured on the target board rather than estimated.
Integration and handover
Alerts and dashboards wired into PLC, SCADA, MES or your maintenance system, and documentation written for your OT/IT team.
Four stages, each with an output you can check
Sensing design
Failure mode, modality, placement and sampling decided against the physics of the asset and the acoustics of the hall.
Instrumented pilot line
Units installed on one line, data collected across the real process window, models trained and validated on it.
Integration
Edge inference, alerting, and the interface to the systems your operators already watch.
Roll-out
Fleet provisioning, monitoring, drift strategy and the MLOps to keep a fleet of units honest.
Sectors that buy this most often
What clients ask before they start
Do we have to buy your hardware?
No. Where you already have suitable sensors — an end-of-line test cell, a weld monitor, an existing vibration system — we work with those first. The NeuroControls units come in when fused, synchronised data is what the problem actually needs.
What happens when the network goes down?
Nothing. Inference runs on the unit, so detection continues; results buffer locally and sync when the link returns. That is the point of edge deployment.
Can it run in an explosion-protected area?
Only with certified hardware, which is a separate conversation and a longer lead time. Paint shops, solvent areas and electrolyte filling all fall into this category — tell us early so it is designed in.
Ask about Multi-modal sensing + edge AI
Tell us the asset or process and what goes wrong. We answer every enquiry within 48 hours on working days, and the first call is free.
- NDAs signed before the first call if you prefer
- Anonymised or synthetic samples are fine to start
- Your data is never used to train models for anyone else
Services clients combine with this one
Ready to find out if it works on your machines?
Start with a free 30 to 45 minute discovery call. Bring the problem, the recordings you already have and your questions. We will tell you honestly whether sensing-based AI is the right tool and what the next step would cost in days, not months.