The Internet of Things (IoT) is the network of physical objects—devices, vehicles, buildings and other items—embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data.
This innovative program is designed to meet high employer demand for experts that can engineer new interactive services, acquire, fuse, and process the data collected from sensors, actuators, controllers, and other devices, and develop architectures to interconnect these elements as part of larger, more diverse systems.
Potential careers in this rapidly evolving area encompass industry sectors ranging from energy, healthcare, transportation, infrastructure, to manufacturing. Students will be trained in in a wide range of IoT technologies, architectures, and solutions applicable to different domains, and will have the opportunity to develop skills and advanced knowledge in areas such as data analytics, IoT architecture, and distributed application development.
The degree is flexible enough to allow students to further focus their interest utilizing the many elective options, and culminates in a portfolio of work, that is assess and showcases the skills acquired throughout the program. Classes are modestly sized and emphasize best classroom practices while employing online resources to reinforce the classroom experience.
Students will take 10 courses for a total of 30 credits. Most students complete the program in three semesters.
For questions on the degree requirements, please contact eegradapply@buffalo.edu
We consider IoT to have mainly two parts: the Internet and the Things:
- For the Internet, students focus on courses in communications and networking.
- For the Things, students become familiar with hardware (courses in sensors, embedded systems, antennas/RF, power systems).
Core Courses:
EE 526 Wearable and Implantable Sensors
EE 534 Principles of Networking
EE 538 Principles of Modern Digital Communications
EE 541 Energy Storage
EE 701: Special Topics: Internet of Things
Elective Courses:
EE 516 Introduction to Digital Signal Processing
EE 530 Fundamentals of Solid State Devices
EE 531 Probability and Stochastic Processes for Engineering
EE539 Principles of Information Theory and Coding
EE 549 Analog Integrated Circuits Layout
EE 569 RF & Microwave Circuits
EE 574 RF & Microwave Circuits 2
EE 553 Microelectronic Fabrication Laboratory
EE 559 Big Data Analytics
EE 567 Power Electronics
EE 620 MIMO Wireless Communications
CSE 508 Programming with Python
CSE 516 Commerce Technology
CSE 524 Realtime & Embedded Systems
CSE 555 Introduction to Pattern Recognition
CSE 565 Computer Security
CSE 566 Wireless Networks Security
CSE 570 Introduction to Parallel and Distributed Processing
CSE 574 Introduction to Machine Learning
CSE 603 Parallel & Distributed Processing
CSE 626 Data Mining
CSE 642 Techniques of Artificial Intelligence
CSE 676 Deep Learning