In practice

More than twenty years
of operational truth.

From an aluminium smelter to structural health monitoring: SenSe grew from environments where continuous, reliable data is essential.

2004

Born in harsh conditions

More than 264 RS485 inputs across three sections of an aluminium smelter in Delfzijl had to be recorded every five seconds, 24/7 under severe electromagnetic interference.

A clean Linux platform and proprietary acquisition protocol achieved over 99% data reliability.

Early web historian

Industrial data online

Customers gained portal access to real-time and historical screens at an early stage of the web.

IJkdijk & Smart Dairy Farming

Independent data platform

SenSe was selected as an independent collection and publication platform for the Dutch IJkdijk projects. SenSe was also used within Smart Dairy Farming at Wageningen University & Research.

Today

Billions of operational data points

Machines, processes and structures across industries and countries continue to be captured every few seconds.

From test environment to field

Measure, understand and validate in the real environment.

SenSe measurement charts beside the real monitored site
Current measurements directly beside the monitored situation.
Engineers testing sensors in a real R&D environment
Testing sensors and data processing in a practical R&D setup.

EnerGQ

Used SenSe for energy meters in its early years and later developed its own platform from lessons learned.

StabiAlert

Uses SenSe for structural health monitoring, including international StabiView projects.

OnlineQMS

A separate descendant for compressed, event-based, multi-signal high-frequency datasets.

OnlineQMS · StabiView

When SenSe identifies dynamics, OnlineQMS captures the complete event.

StabiAlert sensors autonomously detect an abnormal event and send the compressed high-frequency data block through edge-buffered communication to OnlineQMS. Raw and conditioned signals, peaks and frequency content then become available for analysis.

OnlineQMS analysis of automatically detected high-frequency data
Function and peak analysis of an automatically detected HF event.
OnlineQMS report containing raw and conditioned accelerometer data
Multiple high-frequency signals stored as one coherent event block.

OnlineQMS is a separate event-data platform derived from SenSe. StabiView is its StabiAlert application.

Benefit from more than twenty years of field experience.

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