IS 596 - Social Sensing and Human-Cyber-Physical Systems - Fall 2021



Instructor

  • Prof. Dong Wang
    Email: dwang24 at illinois dot edu
    Office Hours: By Appointment (Office Hour Zoom)
  • TA: Lanyu Shang
    Email: lshang3 at illinois dot edu
    Office Hours: Monday 10am - Noon or By Appointment (Office Hour Zoom)
  • Lecture Time and Zoom Link

    Monday 3:00- 4:55 pm

    Lecture Zoom Link

    Course Overview

    Online social media (e.g., Twitter, Facebook), smartphones, and ubiquitous internet connectivity have greatly facilitated data sharing at scale, allowing for a firehose of human and sensor observations to pour in about the physical world in real-time. This opens up unprecedented challenges and opportunities in the field of social sensing and human-centric cyber-physical systems (H-CPS) where an important goal is to efficiently organize the real-time data feeds and accurately reconstruct the "states of the world", both physical and social. This course offers students the opportunity to learn the theoretical foundations, state-of-the-art techniques, and hands-on experience in this exciting area. The topic of this class is timely due to the increasing interest in online social networks, big data, and human-in-the-loop systems, as well as the proliferation of computing artifacts that interact with or monitor the physical world.

    The class contains four main components: (i) the introduction to social sensing and cyber-physical systems; (ii) key technical challenges (e.g., big data analytics, system reliability, user mobility, energy, privacy, etc.); (iii) state-of-the-art techniques and systems (e.g., MapReduce/Hadoop, fact-finding, etc); (iv) emerging applications (smartphone-based crowdsensing, online social media sensing, participatory/opportunistic sensing, intelligent transportation, smart buildings, body area networks etc). The students will have the opportunities to work with real world social sensing and cyber-physical system problems.

    Getting Help

  • Canvas Page - General announcement and Q&A after class
  • Office Hours - Please refer to the above schedule.
  • Email - Contact Prof. Wang for questions about grades, course policies, etc.
  • Grades are available on Canvas.
  • Course Documents

  • Lecture Zoom Link
  • Syllabus
  • Course Project (Group Signup Form)
  • Assignment 1: Twitter Data Crawler
  • Assignment 2: Tweet Sentiment Analysis
  • Assignment 3: Tweets Clustering

  • Project Meeting Links

  • Project Kick-off Meetings
  • Project Mid-term Meetings
  • Project Pre-Final Meetings
  • Grading

  • 10% of the grade will be assigned on individuals' class participation and proactive discussion of lecture topics and project presentations. (Individual based)

  • 10% of the grade will be assigned on an in-class paper presentation on the selected topic by each group. (Group based)

  • 30% of the grade will be assigned on individuals' homework assignments. (Individual based)

  • 50% of the grade will be determined by a group course project. This grade includes project proposal, mid-term report, mid-term project presentation, a final project presentation, a final project paper, and project updates and demonstrations (to the instructor). The project will implement some innovative social sensing model, service, system, or computing environment. Students will be allowed to work in groups of 1 or 2 on the project. The project will proceed through the landmarks stated below. (Group based)

  • 5%: Project discussion and updates

  • 5%: Project proposal

  • 5%: Mid-term project presentation

  • 10%: Mid-term project report

  • 10%: Final project presentation

  • 15%: Final project paper

  • Note: For individual based work, each student will receive the credit based on her/his own work. For the group based work, every student in the group will receive the same credit based on the group's work.
  • The iSchool has the responsibility for maintaining academic integrity so as to protect the quality of education and research in our school and to protect those who depend on our integrity. Consequences of academic integrity infractions may be serious, ranging from a written warning to a failing grade for the course or dismissal from the University. See the student code for academic integrity requirements: http://studentcode.illinois.edu/article1/part4/1-401/

    Course Project

  • The project will be chosen by each group within the first couple of weeks of class. Here are some ideas to help you get started. Groups are encouraged to come up with their own ideas. If you have some really cool idea that does not satisfy such restriction, please schedule a meeting to discuss it with the instructor. Project title, abstract, and member list are due on Noon, Sep. 3.

  • Each group will schedule a regular meeting (during project meeting slots and office hours) to meet with the instructor and discuss the progress and problems encountered on their projects.

  • Each group will prepare and submit a two page project proposal. The proposal should include an overview of the project (preferably with a diagram), a brief review of state-of-the-arts in related fields, the proposed method/solution, a credible set of initial project results if available, a list of further proposed milestones, and a plan of action for the rest of the semester. The proposal is due on Noon, Oct. 1.

  • Each group is responsible for a Mid-term Project Presentation in class starting from Oct. 18. The presentation will allow the instructor and classmates to comment on the initial results and current state of the project and also give constructive feedback to the group members.

  • Each group will prepare and submit a four page mid-term project report. The mid-term report should include a reasonable amount of preliminary results, a description of finished milestones, a discussion of encountered problems and relevant solutions, and any modifications to the plan (if there are) to finish the remaining tasks. The mid-term report is due on Noon, Oct. 22.

  • Final project presentations will be conducted by each group in the week of Dec. 6.

  • Each group will prepare and submit a final project paper. The final project paper is a comprehensive summary of the whole project and should follow a technical paper writing style. The expected number of pages for the final paper is 8-10 pages (including references). Final project paper is due on Noon, Dec. 13.

  • The proposal, mid-term report and final project paper should all follow a standard technical paper format . Here is the template: IEEE Latex or Word Template .

  • A successful project could result in a conference or journal quality paper.

  • Note : For more information about the project (e.g., possible ideas and milestones), please visit Course Project Page

    You are encouraged to seek out and exploit external manuals, books, websites, and other documentation that can help you to complete your project, provided that you indicate what sources you have used. However, all software development, experimental work, and writing of the proposal, report and paper must be done solely by you and your project partner(s).

    Project Documents Submission Instruction: To submit the project related documents (i.e., abstract, proposal, midterm/final presentation slides and reports), please (1) email the document (i.e., pdf for text documents and pptx/pdf for slides) directly to Prof. Wang before the deadline; (2) upload a copy of the submission to Canvas as a backup. One submission per group is sufficient.

    Assignments

    Assignments are normally due at the beginning of class on the date due . This might change due to the break (e.g., Fall Break). Please double check with the assignment description and the course website for the actual due date. Late assignments will receive no credit. This includes assignments submitted after class has begun.

    Programming assignments will be turned in electronically by uploading all required files to Canvas. You are free to turn in assignments multiple times before the deadline expires. It would be a good habit to turn in an incomplete but working assignment on a daily basis. Thus, there is no excuse for failing to turn in an assignment: everyone should turn in something long before the deadline. Exceptions will be made only in grave circumstances.

  • Assignment 1: Twitter Data Crawler
  • Assignment 2: Tweet Sentiment Analysis
  • Assignment 3: Tweets Clustering

  • In-class Paper Presentation

  • Each group will do an in-class paper presentation to present a selected technical paper in the second half of the semester.

  • The in-class paper presentation will provide good opportunities for you to exercise your scientific presentation ability, practice critical thinking, understand how to judge and challenge other's work in a professional way, and learn how to organize and lead an active scientific/technical discussion session.

  • Detailed instructions are available here
  • Tentative Schedule

    Note: Lecture notes are avaliable on Canvas.
    Week Lecture Materials
    Aug. 23 Social Sensing and Cyber-Physical Systems Landscape Reading:
    Introduction to Social Sensing
    Cyber-Physical Systems: The Next Computing Revolution
    Project Title, Abstract and Member List Due Friday, Sep. 3. (Group Signup Form)
    Aug. 30 Project Idea Brainstorm and Tutorial for Assignment 1 Assignment 1 is out, due: Sep. 13
    Sep. 6 Labor Day
    Sep. 13 Data Reliability and Information Overload Reading:
    Truth Discovery in Social Sensing
    Quantifying the Quality of Information
    Using Humans as Sensors
    Please sign up your meeting slot on Doodle by end of September 15.
    Assignment 2 is out, due: Sept. 27
    Sep. 20 Project Kick-off Meetings
    Sep. 27 Data Reliability and Information Overload Cont. Reading:
    Exploitation of Physical Constraints
    Handling Conflicting Claims
    Provenance-Assisted Social Signal Classification
    Project Proposal Due Friday, Noon, Oct. 1.
    Oct. 4 Online Social Media Sensing Reading:
    Earthquake Shakes Twitter Users
    From Tweets to Polls
    You Are Where You Tweet
    Groundhog Day: Near-Duplicate Detection on Twitter
    Please sign up your meeting slot on Doodle by end of October 6.
    Assignment 3 is out, due: Nov. 1
    Oct. 11 Project Mid-term Meetings
    Oct. 18 Mid-term Project Presentations Mid-term Project Presentation Mid-term Project Presentation
    Project Mid-term Report Due Friday, Noon, Oct. 22
    Oct. 25 Big Data Issues Reading:
    Big Table Paper
    Map-Reduce Paper
    Data Cube Paper
    Nov. 1 Crowdsensing and Mobile Sensing Reading:
    A Survey of Mobile Sensing
    How Long to Wait: Bus Arrival Time Prediction
    Automatically Characterizing Places
    Nov. 8 Automotive Sensing and Intelligent Transportation
    Reading:
    GreenGPS: A Participatory Sensing Fuel-Efficient Maps Application
    SignalGuru: A Collaborative Traffic Signal Schedule Advisory Service
    CarSpeak: A Content-Centric Network for Autonomous Driving
    Nov. 15 Medical Sensing, Privacy or Open Issues
    (Students In-class Presentation)
    In-class Paper Presentation
    Reading:
    Medical Sensing:
    Detecting Cocaine Use with Wearable Electrocardiogram Sensors
    Sensor Selection for Energy-Efficient Ambulatory Medical Monitoring
    Real-time Clinical Monitoring and Deterioration Warning
    Context-Aware Assisted-Living and Residential Monitoring
    Cyber-Physical Modeling of Implantable Cardiac Medical Devices
    BiliCam: Using Mobile Phones to Monitor Newborn Jaundice
    Contactless Sleep Apnea Detection on Smartphones
    MyHealthAssistant: An Event-driven Middleware for Multiple Medical Applications on a Smartphone-Mediated Body Sensor Network
    SADHealth: A Personal Mobile Sensing System for Seasonal Health Monitoring
    Recognizing Academic Performance, Sleep Quality, Stress Level, and Mental Health using Personality Traits, Wearable Sensors and Mobile Phones
    Privacy:
    ProtectMyPrivacy: Detecting and Mitigating Privacy Leaks on iOS Devices
    Cloud-Enabled Privacy-Preserving Collaborative Learning for Mobile Sensing
    Understanding Users' Mental Models of Mobile App Privacy through Crowdsourcing
    Privacy Manipulation and Acclimation in a Location Sharing Application
    Privacy-aware Regression Modeling of Participatory Sensing Data
    Privacy.Tag: Privacy Concern Expressed and Respected
    Privacy-Preserving Compressive Sensing for Crowdsensing based Trajectory Recovery
    A Privacy-Preserving Vehicular Crowdsensing-Based Road Surface Condition Monitoring System Using Fog Computing
    Location Privacy-Preserving Task Allocation for Mobile Crowdsensing with Differential Geo-Obfuscation
    AnonySense: Privacy-Aware People-Centric Sensing
    Is This Thing On?
    Nov. 22 Fall Break
    Nov. 29 Project Final Meetings Please sign up your meeting slot on Doodle by end of November 18.
    Dec. 6 Final Project Presentation Final Project Presentation
    Dec. 13 Final Project Report Final Project Report Due Monday, Noon, Dec. 13