EE290Q / CSE283 – Fall 2008
We are witnessing a growing interest in a new generation of intelligent systems, called embedded intelligent systems, including wireless sensor networks, smart camera networks, and mobile sensor networks, to name a few. The most compelling motivation for this new generation of intelligent systems is that these systems can dramatically extend our abilities in perception and control over our environment and if we are successful, they will be embedded into our daily lives, providing convenience, safety, and sustainability.
Research in embedded intelligent systems is at the intersection of inference, networking, and control, based on advances in hardware and software. This course takes a system-level perspective and discusses recent advances in theory, algorithms, and systems for embedded intelligent systems.
Course Information | Schedule | References
Time: 3:30-6:30PM Thursday
Location: 290 HMMB (UC Berkeley), COB112
COB209 (UC Merced)
Instructors: Shankar Sastry (UC Berkeley), Songhwai Oh (UC Merced)
Topics
o Routing and networking
o Synchronization, calibration, localization, and target tracking
o Distributed algorithms and inference
o Heterogeneous sensor networks
o Mobile sensor networks
o Consensus
o Networked control systems
o Security and privacy
Prerequisites: Linear algebra, probability, analysis
Project: A significant part of this class is an individual or a group project, which includes project proposals, presentations, and a project report. The choice of a project topic (with instructor approval) is up to students; however, the project must exhibit the interplay of at least two of the main themes (inference, networking, and control).
Grading: Based on reading and homework assignments, and project
|
|
Date |
Lectures |
Readings (References) |
Assignments |
|
Week 1 |
8/28 |
Lecture 1: Overview Lecture 2: Applications and overview of topics |
o Overview: [Estrin02] [Chong03] o Applications: [Szewczyk04] [Oh07] o Hardware: [CITRIC] |
|
|
Week 2 |
9/4 |
Lecture 3: WSN Technology Lecture 4: Routing |
o Standards: [IEEE802.15.4] [ZigBee] o Routing: [Mauve01] o [Zuniga04] |
|
|
Week 3 |
9/11 |
Lecture 5: Routing Lecture 6: Synchronization, Calibration |
o Routing: [KWZZ03] [Cagalj02] o Synch/Calib: [RBS02] [ETA06] [Balzano07] [Whitehouse02] |
|
|
Week 4 |
9/18 |
Lecture 7: Localization Lecture 8: Bayesian networks and inference |
||
|
Week 5 |
9/25 |
Lecture 9: Distributed inference in SN Lecture 10: Belief propagation in SN |
Initial project proposal (1 page) |
|
|
Week 6 |
10/2 |
Lecture 11: Gaussian processes Lecture 12: Sensor placement/selection |
||
|
Week 7 |
10/9 |
Lecture 13: Target tracking in SN Lecture 14: Heterogeneous sensor networks |
Project proposal (4 pages) |
|
|
Week 8 |
10/16 |
Lecture 15: Heterogeneous sensor networks Lecture 16: Mobile sensor networks |
||
|
Week 9 |
10/23 |
Lecture 17: Consensus (theory) Lecture 18: Consensus (applications) |
|
|
|
Week 10 |
10/30 |
Guest lecture o Judy Estrin, CEO of JLABS, LLC. o 4PM, Sibley Auditorium (UCB) o VIEW FROM THE TOP Lecture Series |
||
|
Week 11 |
11/6 |
Midterm Project Presentation |
|
|
|
Week 12 |
11/13 |
Lecture 19: Networked control systems Lecture 20: Networked control systems |
||
|
Week 13 |
11/20 |
Lecture 21: Network capacity Lecture 22: Security and privacy |
|
|
|
Week 14 |
12/4 |
Lecture 23: Game theory Lecture 24: Research topics in EIS |
|
|
|
Final |
12/11 |
Final Project Presentations |
|
Project report (upto 8 pages) |