Data Acquisition
Industrial data acquisition is the first and most fundamental step of any IoT project. It describes the direct capture of measured values, states, and process parameters – at machines, sensors, controllers, and systems.
Data acquisition ends at the point where the sensor or controller provides the measured value – for example temperature, pressure, or energy consumption. What happens next is handled by the following building blocks: preprocessing, transmission, analysis.
Modern data acquisition also works with older machines from the 1980s and 1990s – through retrofit solutions with smart sensors and gateways. This makes even existing legacy systems IIoT-capable, without any intervention in the existing controller.
What can concretely be captured?
Our partners capture these data sources in real IIoT projects – proven and scalable.
Sensor data
Smart sensors measure temperature, vibration, air quality, or consumption – wired via IO-Link or wireless via LoRaWAN and Modbus.
Controller data
PLCs and IPCs are connected across manufacturers. Via OPC UA or OPC UA over MQTT, data flows securely and bidirectionally into cloud or edge systems.
Product data
Serial numbers, material batches, or CO₂ footprints are captured directly from production – via RFID, digital nameplates, or QR codes.
Retrofit of existing systems
Machines from the 1980s and 1990s are made IIoT-capable with retrofitted sensors and gateways – without any intervention in the controller.
Worker data
Mobile devices, wearables, and AR glasses capture movements, work steps, and positions of frontline workers in real time.
Material handling data
Fill levels, withdrawals, and container movements are captured directly at the source – for automated reorders and transparent warehouse processes.
Where do companies struggle with data acquisition?
In industrial practice, these are the most common hurdles – regardless of industry or company size.
Heterogeneous machine parks
Machines of different ages and manufacturers use different protocols. Uniform data acquisition is barely possible without standardization.
No direct access to the controller
Many systems do not allow direct data access at PLC level – either for security reasons or because interfaces are missing.
Manual data acquisition as a cost driver
Production data is still captured manually by tally sheet or Excel. This costs time, is error-prone, and delivers no real-time information.
Retrofit without production downtime
Retrofitting older machines without interrupting ongoing operations is technically and organizationally demanding.
Data quality and consistency
Captured raw data is often unstructured, incomplete, or inconsistent – and therefore directly unusable for analysis.
What does structured data acquisition concretely deliver?
Companies in our network achieve measurable results with proven data acquisition.
Real-time insight into production
Machine and process data is immediately available – the foundation for fast decisions and automated responses.
Foundation for all further digitalization steps
Without clean data acquisition, no condition monitoring, no predictive maintenance, no AI analytics. Data acquisition is the necessary first step.
Standardized communication
OPC UA, MQTT, and IO-Link connect machines of different manufacturers and generations into a consistent data stream.
Retrofit without new investment
Existing systems are made IIoT-capable without having to replace them – protecting investments and significantly shortening the ROI period.
Higher data quality through automation
Automatic acquisition eliminates manual errors and delivers consistent, reliable data points for analyses and reports.
Scalable from one sensor to the entire fleet
Data acquisition solutions from our network start small and grow with you – from the first machine to cross-site rollout.
Our experts for Data Acquisition
These companies successfully use Data Acquisition.
