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Halton Academy For Management and Technology Private Limited,
39/2475-B1 LR Towers, South Janatha Road, Palarivattom, Ernakulam, Kerala - 682025, India.

+91-7511-1890-01

4 Francis Street, le2 2bd, England,
United Kingdom.

hello@haltonacademy.com

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.