ET3491 Embedded Systems and IoT Design Syllabus - Anna University

ET3491 EMBEDDED SYSTEMS AND IoT DESIGN

L T P C

3 0 2 4

COURSE OBJECTIVES:

• To understand the design of embedded systems and embedded processors
• To study the real time operating systems and scheduling techniques
• To learn the communication protocols used in embedded systems
• To understand the fundamentals of Internet of Things and its applications
• To gain experience in designing and programming embedded systems and IoT devices

UNIT I EMBEDDED SYSTEMS OVERVIEW

Embedded System Basics - Characteristics and Applications - Embedded Processors - Microcontrollers and Microprocessors, Processor Families - ARM, PIC, AVR. System on Chip (SoC), Hardware software co-design. Real Time Systems - Characteristics and Classification, Temporal parameters of a real time system - Deadline, Execution time and Period, Hard, Soft and Firm real time systems

UNIT II REAL TIME OPERATING SYSTEMS

Real Time Operating System (RTOS) - Kernel, Task and Task States, Process synchronization and Mutual exclusion - Semaphores, Monitors, Critical section, Task scheduling - Priority Based Scheduling, Rate Monotonic Scheduling (RMS), Earliest Deadline First (EDF), Preemptive and Non Preemptive scheduling, Scheduling Algorithms, Intertask Communication and Synchronization

UNIT III EMBEDDED COMMUNICATION PROTOCOLS

Overview of Communication Protocols, UART - Asynchronous Serial Communication, Synchronous Communication - SPI, I2C Bus Protocol, CAN Bus. Wireless Protocols - Bluetooth, WiFi, Zigbee, NFC, LoRaWAN. Protocols layering in Embedded Systems

UNIT IV INTERNET OF THINGS FUNDAMENTALS

IoT Overview and Architecture - IoT Layers, IoT Applications and Services. IoT Platforms and Frameworks, Cloud for IoT, Fog and Edge Computing. IoT Security, Privacy and Safety considerations. IoT Standards and Protocols

UNIT V IoT DESIGN AND APPLICATION

Sensors and Actuators for IoT, Wearables and Ubiquitous Computing, Smart Homes, Smart Cities, Industrial IoT (IIoT), Healthcare IoT applications, Environmental Monitoring, Agriculture IoT. Data management and analysis in IoT systems, Machine Learning at the edge, Case studies of IoT systems

THEORY: 45 PERIODS

PRACTICAL EXERCISES: 30 PERIODS

TOTAL: 75 PERIODS

COURSE OUTCOMES:

At the end of the course the students will be able to

1. CO1: Design and analyze embedded systems using appropriate processors and architecture
2. CO2: Apply scheduling algorithms to real time systems
3. CO3: Implement real time systems using RTOS and communication protocols
4. CO4: Design IoT systems with appropriate architecture and platforms
5. CO5: Develop IoT applications for various domains and analyze system performance

TEXTBOOKS:

1. Rajesh Kumar and Vikram Kumar, "Real-time Systems", McGraw-Hill Education, 2016. (Unit I-II)
2. Kazem Sohraby, Daniel Minoli and Taieb Znati, "IoT Essentials", John Wiley & Sons, 2019. (Unit III-V)

REFERENCES:

1. Shibu K V, "Introduction to Embedded Systems", 2nd Edition, McGraw-Hill Education, 2017.
2. Dhananjay Gadre, "Mastering Embedded Linux Programming", Packet Publishing, 2nd Edition, 2015.
3. Tom Igoe, "Making Things Talk", O Reilly Media, 2007.