Smarter vehicles and infrastructure with deep learning.

Solutions for Automotive

As a driver of innovation, the automobile has always been a pioneer for new technologies. Artificial intelligence has now also found its place in all aspects of the automobile, from vehicle technology to production engineering. AI applications ranging from driver assistance systems to autonomous vehicle functions can be found in vehicle development. In vehicle construction, artificial intelligence can be used to realize potentials in production and quality assurance. With modern vehicle systems, the complexity of products and production increases. The use of artificial intelligence is one way to make this new complexity manageable.

Data Spree answers current questions of the automotive industry with AI-based image processing. People, vehicles, roadways and other objects can be detected and classified via neural networks, thus laying the foundation for modern driver assistance systems and autonomous vehicle functions. But also in the context of production, AI-based image processing opens up many possibilities for new standards of efficiency and quality.

Intelligent Car Functions

Today's modern driver assistance systems or autonomous vehicle functions must be able to map logical requirements that can no longer be implemented with simple rule-based algorithms and conventional image processing. With the help of AI-based image processing, functional scopes can be implemented that can detect and classify persons, other road users, traffic signs, lanes or other objects and obstacles in real time, even under the most diverse conditions. Particularly autonomous and semi-autonomous functions are based on a technical reliability that can only be guaranteed by AI-based image processing, even in situations with many variants and environmental factors. Together with the latest developments in camera and control unit technology, artificial intelligence is therefore an essential component for the automobile of the future.

Key Applications
  • Detection and classification of road users
  • Detection and classification of traffic signs
  • Environment orientation and mapping
  • Implementation of autonomous and semi-autonomous vehicle functions

New Ways of Efficient Production and Quality Control

The production of ever more complex systems with consistently high quality, low costs and high cycle rates requires new ways of dealing with challenges in a modern way. Today, AI-based image processing also allows the comprehensive automation and safeguarding of multi-variant and versatile production processes. Conventional rule-based image processing quickly comes up against limitations in the interpretation of variances, chaotic sorting or error images. Thus, AI-based image processing can also be used to improve quality assurance processes by detecting and classifying different defect images of different characteristics in different production steps. Through machine learning, AI-based image processing systems can be trained and adapted to new production processes or defect images without having to replace the system or equip it with new sensor technology. Artificial intelligence is therefore particularly suitable for reacting flexibly to changes and further developments in production.

Key Applications
  • Quality assurance
  • Continuous process improvement
  • React quickly and flexibly to product changes
  • Automation of highly complex manufacturing processes

Test Track Monitoring

As the demands on vehicle functions increase, so do the requirements on the test infrastructure in vehicle development and testing. With AI-based image processing it is possible to reliably monitor the roadway and to detect and correctly classify vehicles, lane changes, persons or foreign objects on the roadway. This also allows the safe testing of autonomous vehicles and functions without endangering employees. But also the tracking and monitoring of standard test drives under different visibility and weather conditions is reliably guaranteed by AI-based image processing. Artificial intelligence thus manages to harmonize authenticity and safety during vehicle testing.

Key Applications
  • Detecting and classifying vehicles
  • Collision monitoring
  • Detect lane changes and overtaking
  • Vehicle and speed tracking
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