M.Tech in Embedded Systems
Semester-wise syllabus for an M.Tech in Embedded Systems
Semester 1:
Foundation Courses
1. Advanced Microprocessors and Microcontrollers
- Architectures (ARM, AVR, PIC, RISC-V), interrupts, memory management.
2. Embedded C Programming & Real-Time Operating Systems (RTOS)
- Embedded C syntax, RTOS concepts (scheduling, tasks, synchronization).
3. Digital Signal Processing (DSP) for Embedded Systems
- Filters, transforms (FFT), DSP implementation on microcontrollers.
4. Hardware Description Languages (VHDL/Verilog)
- FPGA programming, synthesis, simulation.
5. Lab Work
- Microcontroller programming (ARM/PIC), Embedded C projects, DSP implementation.
Semester 2:
Core Design & Specialization
1. Embedded System Design
- Design methodologies (model-based, UML/SysML), case studies (medical/automotive systems).
2. VLSI Design & Testing
- CMOS/ASIC design, FPGA prototyping, testing techniques.
3. Communication Protocols
- Wired (CAN, SPI, I2C) and wireless (Zigbee, BLE, LoRaWAN).
4. Embedded Linux
- Kernel customization, device drivers, cross-compilation.
5. Elective 1
- Options: Embedded Security, Automotive Systems, Wireless Sensor Networks.
6. Lab Work
- Protocol implementation, Linux-based projects (e.g., Raspberry Pi), VLSI tools (Cadence/MATLAB).
Semester 3:
Advanced Topics & Project Initiation
1. Internet of Things (IoT)
- Architectures, MQTT/CoAP protocols, cloud integration (AWS/Azure).
2. Elective 2
- Options: Embedded AI/ML, Robotics, Cyber-Physical Systems.
3. Elective 3
- Options: Low-Power Design, Autonomous Systems, Advanced DSP.
4. Project Work (Phase 1)
- Proposal, literature review, tool selection (e.g., Altium, Simulink).
5. Lab Work
- IoT projects (sensor networks), robotics applications (ROS).
Semester 4: Dissertation & Finalization
1. Dissertation/Thesis
- Implementation, testing, and submission with industry collaboration.
2. Seminar & Viva Voce
- Presentation of findings, defense, and industry feedback.
Electives (Across Semesters 2–3)
- Automotive Embedded Systems: CAN protocol, ADAS, AUTOSAR.
- Embedded AI: TinyML, edge computing, neural network optimization.
- Robotics: ROS, motion control, sensor fusion.
- Cybersecurity: Secure boot, encryption, side-channel attacks.
- FPGA-Based Design: High-level synthesis, acceleration.
Tools & Skills Integration
- Software: MATLAB/Simulink, Eclipse, Keil, Wireshark.
- Hardware: Oscilloscopes, logic analyzers, Raspberry Pi, Arduino.
- Soft Skills: Technical writing, project management, Agile practices.