Computer Laboratory

Course pages 2017–18

Advanced topics in mobile and sensor systems and data modelling

Principal lecturer: Prof Cecilia Mascolo
Taken by: MPhil ACS, Part III
Code: R249
Hours: 16 (8 2-hours sessions)
Class limit: 18 students

Aims

This module aims to introduce the latest research advancements in mobile and sensor systems and data analytics, spanning a range of domains including systems, data gathering, analytics and applications such as health, transportation, behavior monitoring, cyber-physical systems, autonomous vehicles, drones. The course will cover current and seminal research papers in the area of research.

Syllabus

The course will consist of eight two-hour lectures covering a variety of topics roughly including the following material (some variation in the topic might happen from year to year):

  1. Mobile Operating Systems, Resource and Energy Usage
  2. Mobile Sensing, Behaviour Modelling and Machine Learning on Mobiles
  3. Mobile Health
  4. Drones and Autonomous Control
  5. Cellular Detail Record Analytics
  6. Mobility Modelling
  7. Geo-Social Media Sensing and Urban Data Analytics
  8. Human Sensing and Crowdsourcing

Each week, three class participants will be assigned to introduce assigned three papers via 20-minute presentations, conference-style and highlighting critically its features. Each presentation will be followed by 10 minutes of questions. This will be followed by 10 minutes of general discussion. Slides will be used for presentation.

Students will give one or more presentations each term. Each student will submit a paper review each week for one of the three papers presented except for the week they will be presenting slides. Each review will follow a template and be up to 1,000 words. Each review will receive a maximum of 10 points. As a result, each student will produce 6-7 reviews and at least one presentation, probably two. All participants are expected to attend and participate in every class; the instructor must be notified of any absences in advance.

Objectives

On completion of this module students should have an understanding of the recent key research in mobile and sensor systems and mobile analytics as well as an improved critical thinking over research papers.

Assessment

  • 70%: Aggregate mark for reviews over 6-7 reviews
  • 30%: Presentations and participation in the discussion

Recommended reading

Readings from the most recent conferences such as ACM KDD, ACM MobiCom, ACM MobiSys, ACM SenSys, ACM UbiComp and WWW pertinent to mobile systems and data.