Kurt Munson, engineering manager, HBM Prenscia, says engineering teams are increasingly realizing the potential of bus data, and while it’s very valuable, it comes with some caveats, ahead of his presentation at the Open Technology Forum.
The Open Technology Forum is free to attend and part of Automotive Testing Expo.
What is the background to your presentation?
Engineers in the fields of test and measurement and maintenance are no longer just processing data coming from analog sensors using traditional data acquisition hardware. They are increasingly accessing a mixture of various data types, including low-cost digital data from communication buses and connected vehicles. Bus data serves as an inexpensive source of readily available parameters in a complex electronic system.
What are the most valuable areas that bus data can be used in?
Bus data from connected vehicles offers huge potential benefits such as understanding customer usage, improving the product validation process and reducing unexpected failures. Additionally, bus data analysis is commonly used to validate algorithms on ADAS and autonomous vehicles, to show the reduction of energy consumption and emissions, or to enhance numerical simulation to demonstrate safety and reliability.
What are the challenges with bus data?
Bus data raises a number of challenges in terms of its analysis, because it’s often low-quality, inconsistent and incomplete, and certain types of data are not included. What is therefore required is a dedicated, digital bus data processing tool that will perform analytics on huge quantities of unevenly sampled, heterogeneous sensor data and do it in a scalable fashion and at high speed.
HBM Prenscia has recently delivered a step-change in the processing of measured data with nCodeDS, a breakthrough streamed processing architecture that enables processing speeds more than 10 times higher than those of existing tools. Even greater speed benefits are evident when applied to the increasing amounts of low-quality, low-sample-rate, time-stamped data such as that from the automotive CANbus. Connected vehicles, for example, make these sources of data readily available and offer the promise of transformational information. Importantly, nCodeDS addresses data quality concerns by providing the ability to clean up missing or incorrect values from digital bus data prior to further analysis.
How do you see this developing?
The use of digital data results in optimized designs that deliver reduced overall cost, weight and energy consumption. In the case of bus data analysis, engineers need to be able to convert overwhelming volumes of data into actionable decisions without requiring the intervention of a data scientist. This requires a scalable, server-based solution such as nCodeDS.
Catch Kurt’s presentation “Gain actionable insights from streamed data analytics with nCode” in the free-to-attend Open Technology Forum at Automotive Testing Expo. View the full proram here. HBM Prenscia will also be at Booth 10017 at the Expo. Get your free entry badge here.
