EDAG Group’s Post

My takeaway from the CAR Symposium at RuhrCongress Bochum 🚗 ,   Last week i had an opportunity to participate in Digital Transformation in automotive topic , keynotes and panel discussion Car Symposium event. Hereis my key insight on it.   🎤 Transforming the automotive value chain with GenAI and accelerating digital transformation Key potential opportunities shared from @Jachim Franz at Microsoft and @Thomas Dannenmann at Qualcom like AI based prototyping , generating design and development, accelerate sw coding, simulation , Transforming knowledge work, Impact on engineering and products , sales, marketing , administration and production. Digital Chassis for Software Defined Vehicle , AI Enabled CockPit.   🎤 Always Connected - Coding mindset Tobias J. Nadjib shared how coding mindset at Volkswagen Infotainment GmbH is ready for accelerating the SDV Digital Transformation with efficient way of software development and integration and left shift automated test.   🎤 Semiconductors and new automotive era Peter Fintl at Capgemini shared the concept of custom AI based semiconductor design for better availability and capability   🎤 How to speed up with software platforms ? Jan Becker at Apex AI shared what is Software defined vehicles for consumer and manufacturer, how innovators are speeding up software platform development   🔎 Overall it was well organized by Car Future Team at RuhrCongress Bochum. Personally it was a great learning from several talk and interaction on transformation happing in the automotive industry . 💡 Probably you know there is a phrase Software is never done. Let's see how future of mobility realizes. #CarSymposium #CarSymposium2024 #DigitalTransformation #GenAI #SDV #Bochum Volkswagen Infotainment GmbH

Welcome back to 𝗧𝗵𝗲 𝗖𝗼𝗴𝗻𝗼𝘀! In this week's edition, we dive into some more fascinating realms of: 🔍Object Detection:  Object detection is a computer vision technique that involves identifying and locating multiple objects within an image or video. It typically employs deep learning models to recognize objects and their respective bounding boxes. This technology finds wide applications in fields such as autonomous vehicles, surveillance, retail analytics, medical imaging, and augmented reality, facilitating tasks like object tracking, anomaly detection, inventory management, and visual search. 🚀Semiconductor Manufacturing and its Machines: The semiconductor industry faces a significant challenge due to the chip shortage caused by increased demand for semiconductors in digital devices. Manufacturing semiconductors involves complex processes in specialized factories known as fabs. These processes include manipulating atoms using machines to create integrated chips on silicon wafers. Despite their complexity, semiconductors are essential components in nearly all electronic devices. Don't miss out on this week's captivating discussions! Follow the link below to access the latest edition of 𝗧𝗵𝗲 𝗖𝗼𝗴𝗻𝗼𝘀 and expand your horizons with us. Link-https://lnkd.in/g56DtMYu Happy reading, and as always-stay curious! 📚

In today's automotive engineering landscape, the integration of advanced Electrical/Electronic (E/E) systems has revolutionized vehicles into complex, interconnected machines. Yet, this progress introduces unique challenges, especially within the realm of Model-Based Systems Engineering (MBSE). Generative AI offers advanced capabilities in MBSE to enhance the efficiency and quality of automotive systems engineering. For more details about leveraging Generative AI in automotive MBSE, please visit www.teratics.com #GenerativeAI #AI #Automotive #LLM #sdv #MBSE #AI4MBSE #SystemsEngineering #VModel Hans-Leo Ross Muralikumar Balasubramaniam Raajaguru Mylsamy Karthik R

Axerela plans AI chiplets for automotive Technology News | January 10, 2024 Dutch edge AI chip designer Axelera is planning a version of its in memory computing AI architecture for automotive chiplets.: … computing AI architecture for automotive chiplets. “We are … Netherlands tells eeNews Europe Automotive. Belgian research lab … chiplet technology for automotive that includes European … already targeting chiplets for automotive applications, and Renesas … #car #cars #awesome

Today’s need for #sustainable mobility solutions and the emergence of exciting new vehicle concepts has inspired designers to rethink the ways they can minimize weight, lower manufacturing costs, and meet modern performance targets. Altair’s comprehensive solutions can help organizations develop reliable and innovative mega- and gigacasting components. Blending industry knowledge and innovative technologies, Altair’s artificial intelligence (#AI) and generative design approach, validated by advanced #simulation, helps deliver better products through multidisciplinary #automotive design exploration. Download the eGuide and learn more: https://lnkd.in/gp-Nj2nK #WSimulation #Altair #OnlyForward

The design of most subsystems of a vehicle are becoming more and more critical, because of the timing for the modern projects. The subsystem related to the active chassis controls belongs to that basket and their design and refinement is becoming even more critical with the new non-traditional powertrain architectures. In such applications, indeed, the integration of all the vehicle subsystems increases its complexity. The presentation shows a new method to merge together the typical offline simulation with track data measurements and prevision of the expected performance of new components design done by a DiM150 dynamic driving simulator (see https://lnkd.in/d8uQyQza). In particular, the presentation shows an overview of the Danisi Engineering’s blended methodology based on the virtual mules: simulation models suitable to be driven in real time on the driving simulators. The methodology enables a mirroring of the vehicle development approach: from the classic one (widely based on physical prototypes) to the new blended method based on the virtual mule, comprehensive of hardware in the loop and software in the loop applications. The presentation reports some application examples, in which the described methodology is applied embedding one or more components based on Artificial Intelligence (AI) or Machine Learning (ML). Applications range from obstacle avoidance with Reinforcement Learning, where the RL training of the agent is based on vehicle dynamics simulations, to the development of a traction control that uses an ML vehicle model, which is tuned and validated with other vehicular systems using driving simulators. #Unibo #ArtificialIntelligence #MachineLearning #Automotive #Industrial #Electronic #Engineering

Hardware in the Loop Market (HIL) Top Leaders, Future Scope and Outlook 2030 To Get More: https://lnkd.in/e7ufhkR7 When #analyzing intricate real-time embedded systems, the hardware in the loop (HIL) method is employed. The #hardware in the loop system manages the test #platform and offers a useful platform for simplifying the plant. High-quality results are provided by HIL market technology, which also cuts down on #expenses and labor requirements. Since #hardware in the loop (HIL) is a time- and money-efficient #method, it is utilized in many of the key #applications in the worldwide hardware-in-the-loop market. In turn, this is anticipated to support future #expansion of the worldwide market. With open-loop HIL, the #device being tested receives a replay of recorded or model-generated #scenario data without any feedback #ignals from the DUT influencing the behavior of the scenario. Contrarily, closed-loop HIL provides a #model-based simulation of the physical #environment and traffic, along with feedback signals from the device being tested to the simulation #environment. Examples of applications for this type of HIL include autonomous driving, #multiple vehicle interaction, platooning algorithms, and the #validation of complex application behavior in #complex environments. Hardware in the Loop Market,(HIL) Key Players are: 1. Typhoon HIL, Inc. 2. Airbus Group SE 3. Robert Bosch Engineering And Buisness Solutions 4. Konica Minolta Business Solutions India Pvt. Ltd. 5. NI (National Instruments) #HardwareInTheLoop #HILTesting #SimulationTechnology #AutomotiveTesting #Engineering #EmbeddedSystems #RealTimeSimulation #ControlSystems #CyberPhysicalSystems #TestAutomation #VirtualPrototyping #IoTDevelopment #SystemIntegration #TestBench #TechnologyInnovation

In order to measure image chromatic distortion between 1/8 and ½ a pixel, we needed to measure image features one order of magnitude smaller: We achieved 0,01 to 0,03 pixel ... In order to prove the amount of bias in an image, we used image compression as a metric: 4 bias sources added together amount to 1/3 of lost image compression. One third of the compressed image file is bias. In order to show how bad telemetry was, we showed how image scale accuracy could be made more accurate, 10e-5 to 10e-10 m scale accuracy improvement, 5 digits more, by removing one single bias source, there are 3 more at least. In doing so, the image center moves 3 pixels, and the aim shifts... We can prove our approach retains true object geometry, its imposed in the math formulation we use. Our approach leads to the only missing knowledge in #digitalimaging: How to model a zooming lens. ISO (International Standard Organization) identified this very specific gap in technology as THE missing factor slowing adoption of what is already the second most deployed digital technology after the microchip. R&CV: Robotics & Computer Vision, Optimizing Performance, Limitless Vision I'm the CEO, and we're #hiring in #canada #computervision

𝗧𝗵𝗲 𝗗-𝗦𝗧𝗔𝗡𝗗𝗔𝗥𝗧 𝗣𝗮𝗿𝘁𝗻𝗲𝗿𝘀𝗵𝗶𝗽: 𝗦𝗽𝗼𝘁𝗹𝗶𝗴𝗵𝘁 𝗼𝗻 Hexagon Manufacturing Intelligence Let us introduce to you today a second industry partner of D-STANDART: Hexagon Manufacturing Intelligence, a part of Hexagon AB, the global leader in #digitalreality solutions, combining #sensor, #software and #autonomoustechnologies. Hexagon’s origins can be traced back to 1975 Sweden, although the company was formally incorporated as Hexagon AB in 1993. Starting from 2000, Hexagon focused on a new mission and became a leader in sensors and software that would ultimately form the backbone of its digital reality solutions portfolio. Today, the company has over 24000 employees in 50 countries. Hexagon’s Manufacturing Intelligence division brings its expertise on computer-aided engineering software development to the D-STANDART project. Five affiliates over Europe (NL, ES, IT, FR, BE) are involved in several project stages from #AI surrogate model to digital threads, including the work on #manufacturing defects and #modelling. HMI has also a central role in the commercial exploitation of D-STANDART, as well as the project’s dissemination and training activities. Edwin de Vries Andrew Main Dr. Anil Veetil Wolfram Reinhardt Marieme I. El Ghezal مريم إيمان الغزال Marco Veltri #HorizonEU #materialsustainability #composites #fatiguetesting #modelling #materialdata #CAE #digitalthread #DigitalProductPassport #dstandart #HaDEA #EC