Internet of Things

Various industry forecasts project that, by 2020, there will be around 50 billion smart devices connected to the Internet of Things (IoT), helping to engineer new solutions to societal-scale problems such as healthcare, energy conservation, transportation, etc. These smart devices (networked embedded systems) exist everywhere around us - in everything from small devices such as biomedical implants, networked sensors, and smart cards, to larger devices such as personal computing devices and home electronics/appliances, and even in very large systems such as automobiles, aircraft avionics, and missile flight control systems. Designing and deploying an IoT-based solution requires deep technical competence and expertise in hardware design (at the printed circuit board level as well as at the chip level), embedded software, wireless networking, mobile computing, and cloud computing. Students focusing on this topic area will develop such expertise that will make them highly sought-after by companies building IoT solutions in a variety of application domains.

Potential employers for students focusing on this topic include not only the traditional semiconductor and hardware companies, such as Intel, ARM, Cisco, Qualcomm, Broadcom, TI, NVIDIA, NXP, AMD, etc., but also vertically-integrated system design houses (Apple, Google, Amazon, Samsung, IBM) and a range of startups.

Along with faculty advisors, each student will design his or her Plan of Study. Students are encouraged to pick courses that give them an overall view of considerations involved in architecting end-to-end IoT solutions (e.g., hardware design, embedded software, computer networking, cloud computing). In addition, students should ensure that their course selection includes courses that strengthen their hands-on hardware and software implementation skills. Students can obtain breadth by taking courses that give them an improved understanding of VLSI circuits and semiconductor devices as well as courses that focus on emerging application domains such as machine learning, video processing, etc.

Relevant Courses

Each student will consult with faculty advisors and develop a Plan of Study tailored for their goals and background.  Some relevant courses for this technical topic are listed below.

Technical Concentration (12 credits)

ECE 69500 System-on-Chip Design (3 credits)
ECE 55900 MOS VLSI Design (3 credits)
ECE 56800 Embedded Systems (3 credits)
ECE 43700 Computer Design and Prototyping (4 credits)
ECE 69500 Mobile Computing Systems (3 credits)
ECE 59500 Introduction to Operating Systems (3 credits)
ECE 59500 Computer Network Systems (3 credits)

Technical Breadth (6 credits)

ECE 59500 Primer on Semiconductor Fundamentals (1 credit)
ECE 59500 Essentials of MOSFETs (1 credit)
ECE 59500 Primer on Analysis of Experimental Data & Design of Experiments (1 credit)
ECE 59500 Applied Algorithms (3 credits)
ECE 60800 Computational Models and Methods (3 credits)
ECE 59500 Machine Learning - I (3 credits)
ECE 59500 Microfabrication Fundamentals (1 credit)
ECE 59500 Primer on RF Design (1 credit)
ECE 30862 Object-Oriented Programming in C++ and Java (3 credits)
ECE 56300 Programming Parallel Machines (3 credits)

Mathematics (3 credits)

MA 51100 Linear Algebra
MA 52700 Advanced Mathematics for Engineers and Physicists - I

Ideas to Innovation Project and Skills Development (9 credits)

Several of the project ideas listed are relevant to this technical focus.

30 credits total