About the Course

Do you want to learn about cool emerging technologies like using smartphones to diagnose diseases and health disorders? Do you want to explore novel interfaces that will redefine the future of virtual reality systems? Everyday, we are awash in wireless signals that are used for communication, but did you know that we can also leverage these signals for many other applications. Our smartphones today are full of highly capable sensors that we can use to do everything from healthcare monitoring to motion tracking. Our class explores the unconventional approaches that allow ubiquitous sensors and signals to solve real world problems. You will gain hands on experience applying signal processing and machine learning algorithms to tackle issues that affect millions of people. Students from all areas of computer science and engineering are welcome, there are no prerequisites.


Important Dates

Date Deliverable Due
Oct 3 Assignment 0 out
Oct 12 Assignment 0 due
Oct 17 Assignment 1 out
Oct 31 Assignment 1 due
Nov 2 Assignment 2 out
Nov 9 Project proposal
Nov 16 Assignment 2 due
Dec 11 Project presentation + report

Schedule

Disclaimer: Paper assignements are preliminary, please do not read ahead until they are finalized.
Date Material
Sept 26 Introduction and History of Mobile Systems
The Computer for the 21st Century
What next, Ubicomp? Celebrating an intellectual disappearing act
Charting Past, Present, and Future Research in Ubiquitous Computing
Sept 28 Interaction 1
ViBand: High-Fidelity Bio-Acoustic Sensing Using Commodity Smartwatch Accelerometers
Abracadabra: Wireless, High-Precision, and Unpowered Finger Input for Very Small Mobile Devices
Oct 3 Interaction 2 Whole-home gesture recognition using wireless signals
FingerIO : Using Sonar for Fine-Grained Finger Tracking
Soli: ubiquitous gesture sensing with millimeter wave radar
Oct 5 Through-body interaction
Enabling On-Body Transmissions with Commodity Devices
Touch Recognition Of Uninstrumented Electrical And Electromechanical Objects
Oct 10 Localization 1
SurroundSense: mobile phone localization via ambience fingerprinting
Zee: Zero-Effort Crowdsourcing for Indoor Localization
Oct 12 Localization 2
RADAR: An In-Building RF-based User Location and Tracking System
The Cricket location-support system
Oct 17 Localization 3
ArrayTrack: A Fine-Grained Indoor Location System
Decimeter-Level Localization with a Single WiFi Access Point
Oct 19 TBD
Oct 24 Mobile health 1
ApneaApp: Sleep Apnea Detection on Smartphones
Vital-Radio: Smart Homes that Monitor Breathing and Heart Rate
Oct 26 Mobile health 2
Oct 31 Mobile health 3
Guest lecture: Alex Mariakakis
BiliCam: Using Mobile Phones to Monitor Newborn Jaundice
PupilScreen: Using Smartphones to Assess Traumatic Brain Injury
Nov 2 Physical computing
Nov 7 Low-power systems
Guest lecture: Vamsi Talla
Ambient Backscatter: Wireless Communication Out of Thin Air
Wi-Fi Backscatter: Internet Connectivity for RF-Powered Devices
Nov 9 Smart homes 1
Surface MIMO: Using Conductive Surfaces For MIMO Between Small Devices
Wall++: Room-Scale Interactive and Context-Aware Sensing
Nov 14 Smart homes 2
Nov 16 Fabrication
3D Printing Wireless Connected Objects
Nov 21 Drones
Nov 23 No class. University holiday.
Nov 28
Nov 30 Deep learning
Dec 5 Bio computing
Liftoff of a 190 mg Laser-Powered Aerial Vehicle: The Lightest Wireless Robot to Fly
Dec 7 Security and privacy
DolphinAtack: Inaudible Voice Commands
Gyrophone: Recognizing Speech from Gyroscope Signals

Grading and Evaluation

Your grade will be based on 3 homework assignments, summaries of class readings and a final project.

Homework

COLLABORATION POLICY: Homework must be done individually: each student must hand in their own answers. In addition, each student must write and submit their own code in the programming part of the assignment (we may run your code). It is acceptable, however, for students to collaborate in figuring out answers and helping each other solve the problems. You must also indicate on each homework with whom you collaborated.

RE-GRADING POLICY: All grading related requests must be submitted to the TA via email only. Office hours and in person discussions are limited solely to asking knowledge related questions, not grade related questions. If you feel that we have made an error in grading your homework, please let us know with a written explanation, and we will consider the request. Please note that regrading of a homework may cause your grade to go up or down on the entire homework set.

LATE POLICY: Homeworks must be submitted by the posted due date. There is no credit for late work. The homework scoring system of above is an attempt to minimize the harshness of this policy.

NO EXCEPTIONS WILL BE GIVEN TO THE GRADING POLICIES (unless based on university policies, e.g. medical reasons). IF YOU ARE NOT ABLE TO COMPLY WITH THE LATE HOMEWORK POLICY, DUE TO TRAVEL, CONFERENCES, OTHER DEADLINES, OR ANY OTHER REASON, DO NOT ENROLL IN THE COURSE.

HONOR CODE: As we sometimes reuse problem set questions from previous years, covered by papers and webpages, we expect the students not to copy, refer to, or look at the solutions in preparing their answers (referring to unauthorized material is considered a violation of the honor code). Similarly, we expect students not to google directly for answers. The homework is to help you think about the material, and we expect you to make an honest effort to solve the problems. If you do happen to use other material, it must be acknowledged clearly with a citation on the submitted solution. For more information, please see the CSE Academic Misconduct policy that this course adheres to.

Project

You will work independently or with a partner on a mobile systems project spanning most of the quarter ending with a poster presentation and written report. The project should address a novel question. The components of the project are