Smart Sensing in Industry 4.0

Smart Sensing

At a glance

Amid global competition, the requirements for efficient production processes in industry are growing all the time. As we move from purely digitally connected infrastructures towards self-organizing products and processes, targeted use of smart technology systems will ensure long-term business success. Here there are any number of variables, levers and details to be taken into account; for many companies, these represent an important first step towards “production of the future.”

A crucial part of this is to define and digitalize the individual stages and manufacturing processes in order to make all relevant data available for downstream documentation, analysis, optimization and further steps. Smart sensing is not merely about gathering sensor data, but also then performing an immediate, application-based analysis and sorting. This allows direct, on-site feedback on the process to be given; it also means process-relevant data can be transferred at this stage, leading to more efficient data transfer and reducing the requirements for latency, data rates and data volume.

Technologies and competence

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Fraunhofer IIS develops innovative algorithms to analyze and evaluate data gathered by low-cost sensors, for instance the inertial sensors used to measure speed and rotation rates, which are already integrated into almost every smartphone. The data provided can be used to determine the state of motion for tools, parts, workpieces and personnel as well as to record, digitalize and analyze processes. By combining and fusing this information with existing positioning solutions, it is also possible to enhance reliability, robustness and precision as well as to record further KPIs. The algorithms can either be directly integrated into existing electronic systems or retrofitted by way of what are known as cyber-physical systems. Using smart sensors and a connection to production systems, cyber-physical systems independently recognize, log and control process steps.

We offer

Innovative algorithms for evaluating sensor data

Sensor fusion, machine learning and statistical signal processing

Data analysis, data validation and quality control

Positioning in real time

Condition and movement classification and

Incident recognition and process recording in real time

Consulting and feasibility studies

Evaluation of systems by way of simulation and testing in a near-application environment or on site

Customer-specific development through to the product

Software licensing

Application area

Determining KPIs in dynamic systems

Quality assurance and monitoring, for instance in assembly and generally in an Industrie 4.0 environment 

Correct handling of tools and objects (adaptable guidelines)

 Positioning and tracking


Automated process documentation