Software Defined Vehicle (SDV) Foundation Bootcamp

Electric Mobility & Automotive

Venue : T-works
Date : 12th - 13th March 2026
Duration : 2 Days
Registration : ₹10,000+ GST

Open toautomotive system, software, embedded, and E/E architecture professionals from OEMs and Tier-1/Tier-2 suppliers who want to understand Software Defined Vehicle fundamentals.

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Core Learning Pillars

  • SDV Foundations & Architecture

    Evolution to SDVs, signal-oriented vs service-oriented architectures, SDV building blocks

  • Key SDV Technologies

    In-vehicle networks, AI/ML, cloud and edge computing in automotive systems

  • Software Architecture & Middleware

    SDV software stack, microservices, containerization, APIs, AUTOSAR (Classic & Adaptive)

  • Vehicle OS, HPC & Platforms

    POSIX, RTOS, QNX, Automotive Linux, Yocto basics, HPCs and hardware accelerators

  • Connectivity, OTA & Communication

    OTA architecture, Ethernet backbone, TSN, V2X, 5G, real-time communication

  • Security, Lifecycle & Future Trends

    SDV cybersecurity, secure boot, IDS, DevOps, CI/CD, autonomous software basics, future innovations

✔ Comprehensive introduction to Software Defined Vehicle (SDV) architecture

✔ Clear comparison between traditional vehicle and SDV paradigms

✔ Exposure to HPCs, Automotive Linux, POSIX, AUTOSAR, and middleware

✔ Coverage of OTA, TSN, V2X, cloud-edge computing, and connectivity

✔ Introduction to SDV cybersecurity and future technology trends

✔ Industry-aligned content mapped to real automotive project use cases

Key Highlights

✔ Understand core SDV concepts and architectures

✔ Differentiate traditional ECUs from SDV-based systems

✔ Interpret SDV software stacks and middleware choices

✔ Understand the role of HPCs, OS, and embedded Linux

✔ Apply SDV concepts to real automotive project scenarios

✔ Assess technical challenges and ToCs (Terms of Concern) in SDV programs

✔ Build readiness for advanced SDV, ADAS, and autonomous vehicle roles

Program Outcome

Program Details

    • Evolution of automotive electronics to SDVs

    • Differences between traditional and SDV architectures

    • Key Components of SDVs: Sensors, actuators, control units and communication

    • systems

    • Signal Oriented vs Service Oriented Architectures

    • In-vehicle networking protocols (CAN, LIN, FlexRay, Ethernet)

    • Cloud and Edge Computing for SDVs

    • Role of A1 and Machine Learning in SDVs

    • SDV software stack layers

    • Middleware and application layer software

    • Role of microservices and containerization

    • Use of service-oriented architectures (SOA) and APIs

    • Powertrain, ADAS (Advanced Driver Assistance Systems), and infotainment systems

    • Cybersecurity and over-the-air (OTA) updates

    • Data management and logging requirements

    • Analysing different HPCs in the market

    • Role of Hardware Accelerators in HPCs

    • Introduction about S32G274a HPC Gold box

    • Overview of Automotive Embedded Linux

    • Yocto build project- a basic Introduction

    • Overview of Vehicle OS - POSIX vs RTOS vs QNX

    • Middleware overview: Classic Vs Adaptive AUTOSAR

    • Importance of Hypervisors in SOA Architecture

    • Containerization in SDV

    • Edge Vs Cloud native Computing

    • Introduction to OTA

    • Ethernet as Backbone

    • V2X Communication Overview

    • TSN Overview

    • Advanced OTA Use Case: Gateway Server +4 Client architecture

    • V2X communication types: V2V (vehicle-to-vehicle), V21 (vehicle-to-infrastructure), V2P

    • (vehicle-to-pedestrian)

    • Bluetooth, Wi-Fi, 5G, and emerging standards for SDVs

    • Real-time communication and latency management

    • Agile development methodologies for SDVs

    • DevOps and CI/CD pipeline in automotive software

    • Software verification, validation, and compliance (ISO 26262, ASPICE)

    • Levels of vehicle autonomy

    • Sensor fusion and path planning algorithms

    • Role of machine learning and A1 in perception and decision-making

    • SDV data lifecycle management

    • Role of cloud in processing, storage, and remote diagnostics

    • Edge computing for real-time decision making

    • Threat landscape in automotive software

    • Security protocols and encryption methods

    • Key management and secure boot mechanisms

    • Base Platform Selection for Safety-Critical Apps

    • Cybersecurity in SDV: Secure communication, IDS, Blockchain, Quantum Resilience

    • Edge Security & Cloud Security Comparison

    • Continuous Homologation

    • Role of A1 and quantum computing

    • Digital twins and predictive maintenance

    • Emerging technologies: 6G, software-defined connectivity

Step into the future of automotive software

Upgrade your skills for next-gen automotive platforms—HPCs, Automotive Linux, AUTOSAR, OTA, V2X, and Cloud-Edge computing.

Register