Optimal use of artificial intelligence
Through the correct use of artificial intelligence (AI) and data science, many operating processes can be made significantly more efficient - especially with regard to the validation of autonomous driving functions. Data science is an important prerequisite for the development of AI systems. With the help of data pre-analyses and workshops, MicroNova's consultants identify the specific potential for improvement in your company.
In the field of artificial intelligence, in particular Narrow AI, MicroNova offers services around Machine Learning (ML) and focuses here primarily on so-called Deep Learning.
Deep learning uses algorithms that allow a system to train itself to perform specific tasks. Especially in software development, AI-supported automated testing can significantly accelerate processes.
Whether building the necessary IT infrastructure for scalable AI solutions or optimizing existing AI initiatives: We are looking forward to supporting you in your challenges around the use of AI.
Terms & applications
AI technologies (German)
Webinar recording from September 29, 2020, duration: 18 minutes
- Basic concepts of AI: Data Analytics, Evolutionary Algorithms, Machine Learning and Neural Networks
- Requirements for Artificial Intelligence: handling of large amounts of data, robustness, generalization
- Presentation of the functioning and training of an artificial neural network
- Explanation of supervised learning, unsupervised learning and reinforcement learning
The creation of a so-called digital twin accelerates vehicle development, since ECU software can be tested in a virtual environment - without the need for a real prototype. This approach therefore requires an increasing number of simulation models. Especially with regard to autonomous vehicles, such models can virtually cover a wide range of different scenarios and factors.
Neural networks are particularly suitable for vehicle components that are difficult to reproduce with physical modeling, such as individual parts of an engine. MicroNova Consulting supports companies in data analysis, in the selection of suitable AI technologies for modeling, and in the integration and validation of the individual model components.
Test of AI
The validation of AI systems in vehicles - especially driver assistance systems and autonomous vehicle functions - requires new test methods, such as scenario-based testing. The test environments required for this purpose must be able to integrate the ECU software and must also be massively scalable in order to carry out the high test efforts for autonomous driving functions in an acceptable time. MicroNova Consulting supports you with the conception, introduction and further development of processes, methods and tools for AI-based systems for autonomous driving. Other areas of application include functional safety according to ISO 26262 or the ASAM standard OpenSCENARIO.
Sensor data analysis
For a vehicle to be able to move autonomously on the road, it must be able to recognise its surroundings and to decide correctly which path it must take or which reaction is required. MicroNova Consulting supports companies in the design of solutions for object recognition, e.g. traffic light recognition, and in the calculation of routes based on trajectories.
Implementation of AI projects (German)
Webinar recording from September 29, 2020, duration: 14 minutes
- Implementation of an AI project using the process models CRISP-DM and CRISP-ML
- Project start and business understanding
- Data preparation, data understanding and feature engineering
- AI Modeling and Testing
- Visualization and Deployment
Use our experience to your advantage
MicroNova consultants have many years of practical experience in their respective fields and have direct access to our experts in hardware and software development as well as testing. With MicroNova Consulting you get not only consulting, but also the knowledge and experience from more than 30 years of automotive engineering.