Master of Computer Engineering in Internet of Things

The objective of IoT is to enhance both device-to-device interactions, as well as device-to-human interactions via the Internet. IoT systems facilitate controlling and monitoring devices from anywhere by integrating sensors, actuators, local processing and storage devices, wireless networks, Internet, and cloud computing. IoT engineers also need to understand the Cyber Security and Big Data challenges for IoT applications. Learning every major aspect of these technologies is necessary to be a successful engineer in the field of Internet of Things. Students will be trained to master several key topics in the field of computer networking, embedded systems, system architectural design issues, communication and information systems, smart grids and cybersecurity.

Minimum Credits Required 30
Maximum 400-Level Credit 12
Minimum 500-Level+ Credit 18
Maximum 700-Level Credit 4
Maximum Transfer Credit 9
Core Courses (18-24)
Select a minimum of 6 courses from the following:18-24
Intro to Computer Ntwks3
AI and Edge Computing3
5G Wireless Network3
Wireless Comm Systm Design3
IoT and Cyber Physical Systems3
Computer Cyber Security3
Application Software Design3
Computer Network Security3
Modern Internet Tech3
Special Problems (Internet of Things)3
Network Engineering Elective (3-6)
Select minimum 1 course from the following:3-6
5G Wireless Network3
Wireless Ntwrk Protocols/Stand3
Coding Reliable Communications3
Info Theory and Applications3
Comm Netwrks Performance Analy3
Dsgn Optmztn Compt Ntwrks3
Wireless and Mobile Networks3
Wireless Network Security3
Computer Engineering Elective (3-6)
Select minimum 1 course from the following:3-6
Smart & Connected Embedded Sys4
Computer Org and Design3
Hardwr Security & Adv Comp Arc3
Hardware Software Codesign3
Object-Oriented Program & ML3
Signal and Image Processing Elective (3-6)
Select minimum 1 course from the following:3-6
Digital Signal Processing I3
Image Processing3
Video Processing & Comm3
Analysis Random Signals3
Compt Vision Image Processing3
Machine and Deep Learning3
Statistical Signal Processing3
Digital Signal Processing II3
Power Engineering Elective Courses (0-3)
Select 0-1 course from the following:0-3
Applied Optimization Engrgs3
Hybrid Electric Vehicle Drives3
Discrete Time Systems3
Next Generation Smart Grid3
Energy Harvesting3
Motion Control Syst Dynamics3
Power Elect Dynmcs Control3
Power System Planning3
AI in Smart Grid3
Elements of Smart Grid3
Microgrid Design and Operation3