IoT Systems
A new era of computing has arrived with the embedding of computational intelligence in various engineered and natural systems. Networked devices at the edge of the internet are no longer merely computers. Rather, they are diverse machines capable of sensing, learning, acting and interacting with humans and the physical world around them — at scales ranging from one person to the planetary.
At UCLA Samueli School of Engineering, the “Internet of Things” (IoT) area of study will delve into many applications such as mixed-reality spaces, connected communities, smart transportation, precision mobile health and more “smart and connected” systems at all scales in diverse spheres.
The UCLA IoT track will integrate faculty expertise from Electrical and Computer Engineering and Computer Science. The curriculum will focus on architectural abstractions, theoretical foundations, algorithmic methods, hardware/software technologies and applications relating to the design, implementation and fabrication of IoT systems.
Please note: If you’re interested in applying for the IoT concentration, please select AI concentration in the application process and mention it in the Statement of Purpose for your intent to apply for IoT concentration.
“The UCLA IoT area of study will prepare students for a digital revolution across industries, with hands-on technical knowledge to support next-generation IT innovation and applications.”
Area Director: Prof. Mani Srivastava
Sample Curriculum for Systems Issues in IoT
Fall | Winter | Spring | Summer |
EC ENGR M202A / COM SCI M213A Embedded Computing (Instructor: Prof. M. Srivastava) |
EC ENGR 209A Human-Computer Interaction (Instructor: Prof. A. Chen) |
EC ENGR 209AS IoT Security & Privacy (Instructor: Prof. N. Sehatbaksh or Prof. M. Srivastava)OR
EC ENGR 209AS |
Capstone Project |
COM SCI 215 IoT Connectivity & Sensing (Instructor: O. Abari) OR
COM SCI 211 |
Engineering Professional Development Elective | COM SCI 209AS AI on Chip (Instructor: L. He) |
Engineering Professional Development Elective |
Engineering Professional Development Elective | |||
12 Units | 8 Units | 8 Units | 8 Units |
Sample Curriculum for AI/ML Issues in IoT
Fall | Winter | Spring | Summer |
EC ENGR M202A / COM SCI M213A Embedded Computing (Instructor: Prof. M. Srivastava) |
EC ENGR 209AS AI/ML for IoT/CPS (Instructor: Prof. M. Srivastava) |
EC ENGR 209AS AI on Chip (Instructor: Prof. L. He) |
Capstone Project |
COM SCI 215 IoT Connectivity & Sensing (Instructor: O. Abari) OR
COM SCI 211 |
EC ENGR C247 Neural Networks and Deep Learning (Instructor: J. Kao) |
Engineering Professional Development Elective | Engineering Professional Development Elective |
Engineering Professional Development Elective | |||
12 Units | 8 Units | 8 Units | 8 Units |