Academics / Graduate Study / MS Programs / Master of Science in Computer Engineering Internet of Things, Edge Computing, and Cyber-Physical Systems Specialization
The Internet of Things (IoT) market is exploding, with one trillion connected devices predicted in the next decade that are producing enormous amounts of data. Countless sensor-based devices are continuously scanning the environment to collect and report data on their surroundings. As a result, the requirement to analyze data in near real-time has become vital across many industries, including wearables, manufacturing, energy, security, healthcare, agriculture, telecommunications, retail, and finance.
Edge computing is igniting a paradigm shift in IoT. where data is captured and processed close to the source. The results include minimizing latency, power, and data transit costs while producing real-time feedback and decision-making. With projections of more than 150 zettabytes of data generated annually, the advantages of edge computing platforms have never been more apparent. By allowing organizations to process more data and generate more complete insights, edge computing is quickly becoming standard technology for those heavily invested in IoT.
IoT and edge computing are significant areas in the field of cyber-physical systems (CPS), in which networking, computation, and physical components are seamlessly integrated together. In CPS, software and physical components are deeply intertwined and interact with each other in ways that change with context. CPS helps improve efficiency, performance, reliability, and security of business and technology infrastructure. The growing demand for state-of-the-art CPS infrastructure is driving the urgent need of new methodologies, algorithms, and tools for the modeling, simulation, synthesis, and verification of such systems.
In this track, you will be introduced to a broad foundation and deep domain knowledge in IoT, edge computing and CPS to take full advantage of this explosive growth opportunity. You will learn how to build intelligent ecosystems that will allow devices to collect and analyze data at scale, by focusing on four key areas of CPS: hardware, software, networks, and critical infrastructure.
Recommended Courses
Core Courses
Select at least six courses from the following list:
- CE 303 Advanced Digital Design
- CE 329 The Art of Multicore Concurrent Programming
- CE 346 Microprocessor System Design
- CE 355 ASIC and FPGA Design
- CE 364, 464 Cyber-Physical Systems Design and Application
- CE 365, 465 Internet-of-Things Sensors, Systems, and Applications
- CE 366, 466 Embedded Systems
- CE 395, 495 Advanced Digital System Design with FPGAS
- CS 339 Introduction to Database Systems
- CS 340 Introduction to Computer Networking
- EE 326 Electronic System Design I
- EE 327 Electronic System Design II
- EE 359 Digital Signal Processing
- EE 363 Digital Filtering
- EE 375, 475 Machine Learning: Foundations, Applications, and Algorithms
Elective Courses
Select up to six courses from the following list:
- BME 353 Bioelectronics
- BME 495 Wearable Devices: From Sensing to Biomedical Inference
- CE 347-1 Microprocessor Systems Project I
- CE 347-2 Microprocessor Systems Project II
- CE 361 Computer Architecture I
- CE 362 Computer Architecture Project
- CE 392 VLSI Systems Design Projects
- CE 393, 493 Advanced Low Power Digital and Mixed-signal Integrated Circuit Design
- CE 452 Advanced Computer Architecture I
- CE 456 Modern Topics in Computer Architecture
- CS 343 Operating Systems
- CS 345 Distributed Systems
- CS 397, 497 Wireless and Mobile Health (mHealth)
- CS 397, 497 Wireless Protocols for the Internet of Things
- EE 307 Communications Systems
- EE 328, 428 Information Theory and Learning
- EE 332 Introduction to Computer Vision
- EE 374 Intro to Digital Control
- EE 378 Digital Communications
- EE 380 Wireless Communications
- EE 395 Adaptive Signal Processing and Learning
- EE 395, 495 Introduction to Smart Grid Systems
- EE 395, 495 Machine Learning for Medical Images and Signals
- EE 395, 495 Cardiovascular Instrumentation
- EE 418 Advanced Digital Signal Processing
- EE 435 Deep Learning Foundations from Scratch
- ENTREP 474 NUvention: Energy
- ENTREP 475 NUvention: AI
- ME 395 Industry 4.0 Manufacturing
