Transforming the automotive maintenance paradigm
Aniket Palkar and Ajit Kolhe explain how KPIT and AWS are collaborating to help OEMs leverage AI and ML to increase vehicle uptime and reduce maintenance costs.
Artificial Intelligence
Challenges in ADAS development – mastering next-level data-logging and replay necessities
Andreas Klegraf of ETAS and plc2’s Stefan Krassin explain how efficient data logging enables ADAS developers to measure, log, and process relevant data.
New horizons in cloud-connected hybrid and BEV battery systems
FEV’s Ceren Acar provides unique insight into cutting-edge, cloud-connected battery management systems for hybrid and electric vehicles.
Achieving automotive safety and security standards: a practical integrated approach
Bill Taylor of UL Solutions discusses an efficient, integrated approach for meeting the ever-growing need for standards compliance, including functional safety, cybersecurity, SOTIF, and more.
Driving the future – key trends shaping the automotive industry
Experts from Qt Group, Elektrobit, Mapbox, and Territory Studio discuss the fundamental forces driving change in the automotive industry.
Edge data management for software-defined vehicle
Experts from NXP and ITTIA explain how to develop advanced applications using smart edge data management for software-defined vehicles.
Design optimization in automotive product development using AI/ML algorithms
KPIT experts explain how to use physical testing and simulation data to address everyday design challenges in automotive applications.
Solving electric vehicle challenges with predictive machine learning
Chris Handley of HERE Technologies explores the challenges of EV adoption and the solutions that HERE Technologies has developed to address them.
The right solution at the right time: scalable driving simulators, from DESKTOP to DiM500
VI-grade’s Michael Hoffmann provides an in-depth overview of a scalable family of driving simulators, from the desktop-based simulators to the DiM500.
Navigating the complexities of automotive ISP tuning and image quality for vision-based perception systems
KPIT’s Radhesh Bhat explains the challenges of tuning the automotive ISP and how having a sophisticated ISP tuning tool environment helps achieve the desired image quality.
Electric vehicle battery data analytics
AVL’s Gerhard Schagerl and Alwin Tuschkan explain how to use electric vehicle battery data analytics to support design decisions, optimize operation, and predict issues in the field.
The adaptive battery digital twin: how to maximize the use of a BMS application layer with cloud connectivity
Stéphane Turlier of Electra Vehicles and NXP’s Maciek Krawczyk discuss current and future considerations for EV battery packs and management systems.
Increase productivity with machine learning for intelligent online monitoring
AVL experts explain how to use machine learning to intelligently monitor the health of the unit under test and the overall system.
Engineering data science – driving the future of mobility
FEV’s Dr Umesh N. Hivarkar explains the role engineering data science will play in shaping the future of mobility.
Making artificial intelligence and machine learning safe
NXP’s Andres Barrilado explains how AI and ML will make their way into automotive safety functions as we consider how to avoid systematic failures and define new problem statements around inference to provide safety-related functions.
Exploring behaviour AI: automotive applications
Humanising Autonomy’s Raunaq Bose and Pier Paolo Porta of semiconductor design company Ambarella discuss AI applications for the automotive and urban mobility industries.
Winter is coming: how AI predicts slippery road conditions and enables automated driving
Experts from Continental, IBM, and Zeiss present a general introduction to AI and explain how to leverage it to predict upcoming road conditions.
Expediting e-powertrain durability testing with artificial intelligence
AVL’s Matthieu Clauet and Hongbo Sun explain customer pain points during the durability testing process and how to achieve optimum validation and development results using AI.
AI-based fast dynamic DoE methodology for motorcycle race engine performance optimization
Experts from AVL and Ducati discuss the advanced methodologies, tools, and facilities that helped optimize the engine performance of the motorcycle that won the 2020 MotoGP Constructors World Championship.
Accelerating automotive aftersales diagnosis and repair by leveraging artificial intelligence
Experts from SOMIT Solutions and KPIT discuss an AI-based diagnostics solution, which seamlessly integrates root-cause diagnosis with the corresponding repair/service information.