Introduction

Real-time systems (RTS) play a critical role in automotive, aerospace, robotics, industrial automation, telecommunications, medical devices, and embedded systems. These systems require precise timing constraints to ensure safety, reliability, and deterministic performance. With the rise of autonomous systems, IoT, and AI-driven automation, the need for efficient real-time computing is greater than ever.

This course provides a comprehensive understanding of real-time systems, covering hard and soft real-time constraints, scheduling algorithms, real-time operating systems (RTOS), embedded real-time applications, and cybersecurity. Participants will gain hands-on experience in real-time programming using FreeRTOS, Linux RT, and real-time hardware platforms (ARM, DSP, FPGA).

Objectives

By the end of this course, participants will be able to:

1. Understand the fundamentals of real-time systems and applications.
2. Differentiate between hard, soft, and firm real-time constraints.
3. Implement real-time scheduling algorithms for task prioritization.
4. Develop real-time applications using FreeRTOS, RT-Linux, and embedded platforms.
5. Optimize real-time communication for automotive, industrial, and medical applications.
6. Apply real-time system design principles for safety-critical systems.
7. Ensure cybersecurity and fault tolerance in real-time embedded systems.

Who Should Attend?

This course is ideal for:

• Embedded Systems Engineers working with real-time operating systems.
• Software Developers & Firmware Engineers developing real-time applications.
• Control System Engineers working in robotics, automotive, and industrial automation.
• Aerospace & Defense Engineers designing real-time avionics and navigation systems.
• Automotive Engineers working with ADAS (Advanced Driver Assistance Systems) and in-vehicle communication.
• Medical Device Engineers developing real-time patient monitoring and diagnostic systems.
• Researchers & Academics studying real-time computing, AI, and IoT applications.

Course Outline

Day 1: Fundamentals of Real-Time Systems

Session 1: Introduction to Real-Time Systems

• Definition and classification of real-time systems.
• Hard, soft, and firm real-time constraints.
• Real-time applications in automotive, aerospace, medical, and industrial automation.

Session 2: Real-Time System Architecture

• Real-time system components: Processor, memory, I/O, and network interfaces.
• Deterministic behavior and latency analysis.
• Interrupts, timers, and event-driven execution in real-time applications.

Session 3: Real-Time Scheduling Basics

• Periodic vs. aperiodic tasks in real-time scheduling.
• Common real-time scheduling algorithms: Rate Monotonic Scheduling (RMS), Earliest Deadline First (EDF), Least Laxity First (LLF).
• Task synchronization and priority inversion handling.

Hands-On Workshop: Implementing real-time scheduling algorithms in Python/MATLAB.

Day 2: Real-Time Operating Systems (RTOS) and Task Management

Session 1: Introduction to RTOS

• Features and characteristics of real-time operating systems (RTOS).
• Comparison of FreeRTOS, RT-Linux, VxWorks, QNX, and Zephyr OS.
• Task scheduling and multithreading in RTOS.

Session 2: RTOS Programming and Multitasking

• RTOS task management: Task creation, scheduling, and execution.
• Synchronization mechanisms: Mutexes, semaphores, and message queues.
• Real-time inter-process communication (IPC).

Session 3: Memory Management and Real-Time File Systems

• Dynamic and static memory allocation in real-time systems.
• Real-time file systems and persistent storage mechanisms.
• Flash memory and wear-leveling techniques for embedded RTOS.

Hands-On Workshop: Developing a multitasking FreeRTOS application on an ARM Cortex-M board.

Day 3: Real-Time Embedded System Design

Session 1: Real-Time Embedded Hardware Platforms

• ARM Cortex, DSPs, and FPGAs for real-time computing.
• Low-power real-time processing for IoT and edge AI applications.
• Real-time hardware acceleration techniques.

Session 2: Real-Time Communication Protocols

• CAN Bus, Modbus, Ethernet/IP, and TSN (Time-Sensitive Networking) for real-time communication.
• Wireless real-time communication: 5G, LoRaWAN, and industrial IoT.
• Deterministic networking for real-time control.

Session 3: Power Management and Energy Efficiency

• Low-power design techniques for real-time embedded systems.
• Power optimization in battery-powered IoT and wearable devices.
• Energy-efficient scheduling and dynamic voltage scaling (DVS).

Hands-On Workshop: Implementing real-time communication protocols in an IoT application.

Day 4: Real-Time Applications in Critical Industries

Session 1: Real-Time Control Systems in Robotics and Automation

• Real-time motion control for robotic arms and autonomous vehicles.
• PID, adaptive control, and AI-based real-time decision-making.
• Safety-critical real-time applications in industrial automation.

Session 2: Real-Time Systems in Automotive & Aerospace

• Real-time control in autonomous vehicles and Advanced Driver Assistance Systems (ADAS).
• Fly-by-wire and real-time navigation systems in aerospace applications.
• Real-time safety monitoring for self-driving cars and UAVs.

Session 3: Medical and Industrial IoT Real-Time Systems

• Real-time processing in medical imaging and patient monitoring.
• Industrial IoT and real-time predictive maintenance.
• Edge AI for real-time healthcare and smart manufacturing.

Hands-On Workshop: Implementing a real-time robotic motion controller in MATLAB/Simulink.

Day 5: Cybersecurity, Fault Tolerance, and Future Trends

Session 1: Real-Time Cybersecurity and Safety Standards

• Cyber threats in real-time embedded systems.
• Secure boot, encryption, and real-time network security.
• Compliance with ISO 26262 (Automotive), DO-178C (Aerospace), and IEC 61508 (Industrial Safety).

Session 2: Fault-Tolerant and Redundant Real-Time Systems

• Fault detection, isolation, and recovery (FDIR) techniques.
• Redundancy strategies for mission-critical real-time systems.
• Self-healing real-time systems and AI-driven fault diagnostics.

Session 3: Future of Real-Time Systems

• AI-powered real-time systems and neuromorphic computing.
• Quantum computing for high-speed real-time applications.
• Digital twins and real-time simulation for smart cities and Industry 4.0.

Final Project Presentation: Participants develop and present a real-time system for an industrial or autonomous application.

Final Assessment & Certification

• Knowledge Check: Final assessment covering real-time system concepts.
• Project Presentation: Participants present their real-time system prototype.
• Certification: Certificate of completion awarded upon successful participation.