College of Information and Computer Sciences · UMass Amherst
Welcome to COMPSCI 528: Mobile and Ubiquitous Computing!
This course will introduce students to the field of mobile sensing and ubiquitous computing, an emerging CS research area that aims to design and develop disruptive technologies with hardware and software systems for real-world messy, noisy, and mobile scenarios. The students will learn how to build mobile sensing systems, implement them with ubiquitous computing tools, make sense of the sensor data, and model the target variables. Lastly, the students will learn how to think critically about problems in many application areas, including Wearable Computing, Medicine, and Sustainability, and subsequently practice to find appropriate Mobile solutions. The student is expected to work on different hands-on assignments, critique writing, and a final project. This course counts as an Elective toward the CS Major.
This course aims to introduce students to state-of-the-art cyber-physical systems in healthcare applications. Every topic begins from first principles and gradually ramps up to the system design and application, helping students to understand the state-of-the-art developments in this area and initiate research. Students are expected to perform various projects, including signal processing algorithm implementation and embedded system implementation, to obtain hands-on knowledge.
Students will gain practical, hands-on experience by completing assignments and projects utilizing ESP32-S3 hardware. Tutorials will be provided in two class meetings.
There is no required textbook for this course.
Additional office hours are available on request.
The schedule below is the plan of record and may shift slightly; changes are announced in class and on Canvas.
| Week | Topics | Note |
|---|---|---|
| Week 1 | Overview of course and logistics Working principles of sensors and DSP basics | |
| Week 2 | Working principles of sensors and DSP basics | |
| Week 3 | Mathematical foundations for signal analysis | |
| Week 4 | Time and frequency analysis: FFT and STFT | |
| Week 5 | Outdoor and indoor localization | |
| Week 6 | Activity and gesture monitoring | |
| Week 7 | Scheduling — Midterm | |
| Week 8 | Activity and gesture monitoring | |
| Week 9 | Human vital signal sensing: breathing monitoring | |
| Week 10 | Human physiological signal sensing: SpO2 & blood pressure sensing | |
| Week 11 | Human physiological signal sensing: non-invasive SpO2 & blood pressure sensing | |
| Week 12 | Human physiological signal sensing: EEG, EMG, EOG, EDA sensing | |
| Week 13 | Wireless Networks | |
| Week 14 | Security Analysis | |
| Week 15 | Project presentation and demo |
Course grades are a weighted average of the grades earned on all graded material. The final grade is Min(100, actual grade). The weights for the different categories are:
| Component | Weight |
|---|---|
| Assignments | 40% |
| Participation (in class and online discussion) | 5% |
| Midterm (in class) | 30% |
| Final project — proposal (10%), progress report (5%), in-class presentation (5%), final report (15%); done in groups | 25% |
A: 94% · A−: 90% · B+: 87% · B: 84% · B−: 80% · C+: 77% · C: 74% · C−: 70% · D+: 67% · D: 64% · D−: 60% · F: below 60%
The Programming Assignments will be in C, C++, Java, Python, or combined depending on the project you select. The grading of the Programming Assignments is a combination of completeness (all specifications are covered), correctness of results, and style. All programming assignments are due at the beginning of class on the due date. Submissions will be made via Canvas.
Exams are closed book. One two-sided cheat sheet of hand-writing is allowed. Makeup exams are not normally given; in special circumstances, arrangements should be made prior to the exam date if at all possible.
Grades are recorded in Canvas. You can check Canvas for all of your current grades.
Attendance is required for this course. As with all science courses, you will have an easier time learning the material if you attend the lectures and participate in class.
All programming assignments are due at the beginning of class on the due date. Submissions will be made via Canvas. Late work is not accepted unless there is prior written approval by the instructor based on special circumstances. Makeup exams and quizzes are not normally given; in special circumstances, arrangements should be made prior to the exam date if at all possible.
The current university policy concerning incomplete grades will be followed in this course. Incomplete grades are given only in situations where unexpected emergencies prevent a student from completing the course and the remaining work can be completed the next semester. The instructor is the final authority on whether you qualify for an incomplete. Incomplete work must be finished by the end of the subsequent semester or the “I” will automatically be recorded as an “F” on your transcript.
The University of Massachusetts Amherst is committed to providing an equal educational opportunity for all students. If you have a documented physical, psychological, or learning disability on file with Disability Services (DS), you may be eligible for reasonable academic accommodations to help you succeed in this course. Please notify the instructor within the first two weeks of the semester so that appropriate arrangements can be made.