How many hours a day do you use a computer? The computer is no longer limited to desktop computers- your smartphone, smartwatch, earphone, and smart band- all these are computers nowadays, doing computing in some form. They can sense you, your environment, context, behavior, and many things. Have you ever wondered about their capability or how they sense such diverse environmental contexts? Such devices are pervasive, mobile, personalized, and user-friendly -- so we call them ubiquitous -- thus supporting 'computing anywhere and everywhere.' This course will help you learn how these devices use pervasive sensing technologies and intelligent computing paradigms to sense humans and their environment, context, and activities. Consequently, this course intersects many other subjects, such as physics, mathematics, signal processing, machine learning, algorithm design and optimization, and human-computer interactions.

This course will have four broad modules: (1) Location, gesture and activity sensing, (2) Interaction sensing, (3) Context sensing, and (4) Environment sensing. In addition, we'll also discuss the security, confidentiality, ethics, and trust models associated with all these sensing paradigms. We'll look into different sensors and devices, various sensing modalities ranging from locomotive sensing to wireless, acoustic, and RF sensing, how they get integrated, how we can develop low-cost, low-resource learning models to process the data collected from those sensors, how the information is interpreted, how do we infer causality, and finally, how such various methods are combined to infer the final decision.

Additionally, you'll also do some hands-on experiments to program and run models on devices like smartphones and embedded sensors to extract human behavior and contextual information from the collected data. In this process, you'll also learn how to handle real-time noisy sensor data and apply machine learning or deep learning models on top of them.