Just as the web browser brought us click-stream data and the mobile phone brought us geo-location data, ubiquitous low-cost sensors integrated with wearable and IoT devices will bring us a new torrent of user data to collect, analyze, and exploit. The course takes a hands-on approach to exploring the possibilities and limitations of consumer-grade sensing technologies for physiological and contextual data.
We will survey the intellectual foundations and research advances in ubiquitous computing, physiological and affective computing, with applications in health and wellness, social computing, information security, novel user interfaces, etc. We will cover temporal and spectral techniques for time-series data analysis. We will consider data stewardship issues, including data ownership, data privacy, and research ethics. The class lending library will provide access to a variety of devices that can be used for data collection and application prototyping.
Project work can be undertaken in a variety of application domains, such as affective computing, ambient assisted living, biometric authentication, privacy by design, quantified self, smart cars and homes, social robotics, and virtual and augmented reality.
Course Schedule and additional resources on bCourses
Meeting Time
Tuesdays and Thursdays 12:30pm-2pm in 210 South Hall
Instructor
Professor John Chuang
chuang@ischool
Office: 303A South Hall
Office hours: Mondays 2-3pm in 6A South Hall (beginning Sep 12)
Teaching Assistant
Max Curran
mtcurran@ischool
Office hours: Fridays 1:30-3pm in 6A South Hall (beginning Sep 9)
Registration Information
Course: INFO 290 LEC 003
CCN: 29270
Units: 3
Pre-requisite: None
Tentative Grading Criteria
Assignments: 30%
Project 1: 30%
Project 2: 30%
Participation: 10%
Academic Integrity
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