Intelligent sensor systems

More control and efficiency through real-time data collection and processing

Sensors are central key components in the Smart Factory and Smart City sectors. We develop intelligent sensor systems with the aim of collecting process, environmental and environmental data in product manufacturing and urban areas, evaluating it in real time and making it available for the implementation of modern applications.

 

Our range of services

Application-specific data acquisition and processing
We develop intelligent sensor systems with the aim of adapting production processes adaptively and dynamically to changing environmental conditions. Data from production systems are collected and pre-processed for subsequent AI-based evaluation. The result is a more efficient and economical operation of production systems.

  • Data acquisition on the basis of multi-sensor concepts
  • Sensor fusion and local preprocessing in real time
  • Connection to industry 4.0 communication interfaces
  • Application-specific use of RISC, FPGA and GPU technologies

Scalable Industry 4.0 retrofit solutions
Our retrofit solutions make it possible to functionally upgrade existing machines and integrate them into an Industry 4.0 network in order to achieve more transparency, control, plannability and flexibility in production. The focus here is on potential evaluations with a production data acquisition system and permanent retrofit solutions. 

  • Production data acquisition INAsense for potential evaluations
  • Compact OPC UA-based retrofit solutions for machines and systems
  • Application-specific miniature solutions for integration into machine components
 

New: Fraunhofer Energy check

 

Scalable Industry 4.0 retrofit solutions

A key function of Industry 4.0 applications is the acquisition of process data by means of powerful sensor technology.

 

Application area indoor localization with omlox

 

Hardware design and programmable logic devices

 

Image and point cloud evaluation

 

3D printed sensors

 

Seminars