Building Data-Centric SDV Systems on NXP S32 Automotive Processing Platform

Data Foundations for AI: Preparation, Quality, and Maintenance

Overview

This hands-on workshop introduces developers to building deterministic, data-centric SDV and Edge AI pipelines on NXP S32 automotive platforms using the ITTIA DB Platform. Participants learn how CAN messages and other sensor signal data is ingested, managed, analyzed, and transformed into AI-ready insights for battery management, predictive maintenance, anomaly detection, and real-time vehicle intelligence using NXP S32, GoldVIP, and eIQ Auto. Through practical labs, attendees build production-ready pipelines with deterministic data management, power-fail safety, explainable AI, and real-time analytics directly on automotive edge platforms.

Workshop Dates and Times:

• Europe: 2026 June 29–30 at 3:00 PM CET
• Asia: 2026 July 7–8 at 9:00 AM CST/SGT/HKT
• America: 2026 July 9–10 at 2:00 PM ET / 11:00 AM PT

Workshop Location: Online

Online Tutorial Workshop Syllabus

Session I: Edge Data on NXP S32 Cortex-M Control Node with ITTIA DB Lite

Session II: Edge AI on an NXP S32G Vehicle Network Processor with ITTIA DB

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Workshop Sample Applications

During this hands-on workshop, you will be trained to design, build, and deploy a real-world, data-driven AI application, gaining practical skills you can immediately apply to embedded and edge systems.

Real-Time Battery Intelligence at the Edge

Workshop participants take on the role of an embedded automotive engineer designing a single-ECU Battery Management System (BMS) for a Software-Defined Vehicle (SDV). Using NXP S32G-based ECUs as the hardware foundation, they begin by capturing real-time battery signals, including cell voltage, current, and temperature, directly on the device. All data is ingested deterministically and stored using the ITTIA DB Platform, ensuring power-fail-safe persistence and structured time-series management.

Participants then build an on-device AI pipeline to estimate State of Charge (SoC) with high accuracy under varying operating conditions such as charge cycles, dynamic loads, and temperature changes. State of Health (SoH), focusing on understanding long-term battery degradation and performance evolution. Rather than relying solely on static models or lookup tables, the system continuously refines SoC estimation using both real-time and historical data stored locally on the ECU. The system learns battery behavior across operating conditions such as charge cycles, load variations, and thermal changes.

As the battery operates, the system maintains accurate SoC tracking in real time, even under transient conditions and noisy signals. As the battery operates, the system tracks degradation patterns, detects subtle anomalies, and updates SoH metrics in real time. The ITTIA DB Platform persistently stores raw signals, feature windows, and AI inference results, enabling continuous validation and refinement of SoC estimation. Workshop participants can analyze trends such as charge/discharge behavior, current profiles, temperature effects, capacity fade, and internal resistance growth, ensuring reliable and explainable battery state estimation directly on the vehicle.

Course Details

Edge Data AI Certification for Embedded Devices

Workshop attendees will receive a Certificate of Course Completion for the ITTIA DB Platform on NXPS32G. This certification validates hands-on expertise in deterministic data management, on-device data processing, and Edge AI-ready data handling using the ITTIA DB Platform.

 

 

Past Workshop Participants

ITTIA has delivered highly sought-after, hands-on workshops that attract engineers and innovation leaders from across multiple sectors. Our sessions are trusted by companies building real-world, data- and AI-driven embedded systems, and have been attended by teams from leading organizations committed to advancing intelligent edge technologies, including:

Abbott – Acuity Brands – Advances Energy – Applied materials – Avery Biomedical Devices, Inc. – Badger Meter – Cardios – Cat Wranglers
Cognosos Inc. – Continental AG – CPI – Declarative Futures – EDS – Emtech – Everspin – EXFO – Honeywell – Kellogg Northwestern
L3Harris – Magna International – Mayo clinic – Megavolt Labs – Milwaukee Tool – Mold Masters – Nidec Global Appliances – OTTO Engineering
Philips – Resideo – Schneider Electric – Siemens – Southland Sensing Ltd.  – TITOMA – TTI Floor Care – Wind River – Zetron/Codan

Audience

These immersive, hands-on workshops are built for embedded architects and engineers who are shaping the next generation of data-driven, AI-enabled edge systems and want more than theory, they want results. Through practical, expert-led sessions, participants learn how to select the right device platform, design deterministic real-time firmware, and implement robust on-device data management that elevates data to a first-class system asset. The program goes further by showing how to prepare and integrate optimized AI pipelines directly into embedded workflows, while addressing cybersecurity, functional safety, diagnostics, and long-term lifecycle management from day one. By the end of the workshop, engineers leave with the confidence, skills, and real-world experience needed to build intelligent, trustworthy, and future-proof embedded systems ready for production.

These workshops are highly technical, intended for professional engineers and are not suitable for the general public without relevant qualifications.

Workshop Schedule