ForTune II – Sensor gateway for edge AI applications

Fortune II Demonstrator
© Fraunhofer IZM I Francis Viebeck

Predictive and proactive maintenance aims to ensure that machines and systems are maintained in line with requirements in order to avoid unplanned downtime and quality losses in production.

In the Fortune II research project, Fraunhofer IZM has developed a self-sufficient, adaptive solution for AI-supported condition monitoring for Industry 4.0.

Possible applications

Fortune II Demonstrator
© Fraunhofer IZM I Francis Viebeck

ForTune is ideal for companies that want to efficiently monitor and optimize their machines and processes. The technology can be used in various industries to analyze operating conditions, improve maintenance, and increase overall plant efficiency.

Areas of application

  • Civil engineering and construction: monitoring of excavators, cranes, special machines, and conveyor systems, for example
  • Metalworking industry: condition monitoring of milling, drilling, and grinding machines, for example

Your advantages

  • Early detection of changes: multiparameter measurements enable proactive monitoring and identification of deviations in system behavior.
  • Real-time data processing: the sensor gateway can connect a large number of sensors for condition monitoring applications and processes the data in real time.
  • Powerful analyses: with the help of a powerful coprocessor, complex analyses and extensive AI algorithms can be implemented efficiently.
  • Integration of analog interfaces: a special microcontroller ensures the connection to analog interfaces, which are often missing in conventional systems.
  • Broadband communication: modern network interfaces are available for data transmission, enabling seamless integration into various systems.

Get in touch

Want to learn more about ForTune II? Hit us up for more info and a personalized consultation!

Working Group

»Sensor Nodes & Embedded Microsystems«

The »Sensor Nodes & Embedded Microsystems« working group develops autonomous and energy-efficient sensor nodes for smart farming, smart factory, and smart city applications. Hardware-based AI algorithms help preprocess captured data directly in the sensor chips - saving on data transmissions, reducing operating costs, and ensuring fast access to high-quality insights. Our clients benefit from less maintenance, more reliable data quality, and much longer battery lives leading to fewer replacements in the field.

Key Research Area

Development of embedded hardware systems with edge AI

The growing volume of data worldwide is bringing new challenges in data processing. Traditionally, the information generated at the data source is sent to the cloud for processing. However, this approach has several disadvantages: from potential security breaches when handling sensitive data to high energy consumption in data centers and time delays in data transmission and processing, which can be particularly problematic in critical applications.

 

Download | ForTune II

Predictive Maintenance Multi- Sensor Condition Monitoring

 

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