Key information

Instructor
Omid Ardakanian
ardakanian@ualberta.[NULL]ca
http://webdocs.cs.ualberta.ca/~oardakan

Lectures
Tue/Thu 2:00-3:20PM, CSC B-43

Office Hours
Tue 3:30-4:30PM or by appointment, ATH 3-21

eClass
https://eclass.srv.ualberta.ca/course/view.php?id=46434

Prequisites
There are no formal prerequisites for this course

Grading
30% Paper Presentations, 15% Paper Reviews, 5% Class Participation, 10% Project Proposal, 40% Final Project

News

  • 03/09/2018 — First lecture: 2:00-3:20PM, Tuesday, Sept. 4

Overview

This course covers ways to leverage sensing, networking, analytics, and control to make key physical infrastructure of our society, i.e., buildings, transportation systems, and power grids, smarter and more energy efficient. It aims to provide a high-level perspective on the design and analysis of cyber-physical systems, and introduce various topics including systems for data acquisition, storage, and processing, algorithms for resource allocation, scheduling, and control federation, and different types of analytics.

Course Objectives

This course will introduce students to the new areas of Cyber-Physical Systems and the Internet of Things, enabling them to develop the diverse range of skills required to perform research in these areas. In particular, they will learn how to use Computer Science techniques to design, analyze, and improve complex cyber-physical systems, collect and analyze massive amounts of data, and build end-to-end systems that people want to use. Students will complete a group project applying computational techniques, such as machine learning, optimization, control, and simulation to real-world problems.

Organization

This course is a graduate-level seminar that will consist primarily of reading, reviewing, and presenting research papers in the field of Cyber-Physical Systems. Two papers will be assigned to each class. All students must read both papers before the class and submit a short review (critical analysis) for one of the two papers (of their choice) by 1:00PM on the day of the lecture (refer to this article for advice on how to evaluate a paper and write a report). Reviews must be submitted through eClass. Each paper will be presented to the class by one student in a 25-minute conference style presentation, followed by a 15-minute discussion of the paper which will be led by the presenter. All students should also submit presentation feedback for each paper discussed in the class by noon of the day following the lecture. The feedback forms will be anonymized and made available to the presenter in the next class.

Students will work in pairs on an original research project on a topic related to Cyber-Physical Systems. Students are given the opportunity to choose their groupmate, but anyone who does not have a group by October 9th will be assigned to a groupmate at random. The instructor will propose several projects. Each group may decide to work on a proposed project or define a new project. Either way, they must submit a proposal which will be evaluated by the instructor. Each group should write a workshop-quality paper, 8-10 pages in length, describing the research they have done, and present their work to the class in a 25-minute conference-style presentation near the end of the term.

Project Proposal

The proposal must be in pdf format and submitted through eClass by October 18th. The proposal must be 2 pages (double-column in ACM SIG format with 10pt font), answering the following questions:

  1. What is the research problem you want to investigate and why is it important?
  2. What are the existing solutions and why are they insufficient?
  3. What is your methodology?
  4. What resources or data sets do you need?
  5. How tasks are delineated and responsibilities are assigned to the partners?

Final Report

The final report should be a 8-10 page, workshop-quality paper (double-column in ACM SIG format with 10pt font). It must be submitted through eClass by December 14th.

Grading System

During the term, your marks will be accumulated out of 100%, but you will be assigned a letter grade at the end of the term. Marks (out of 100%) are translated to letter grades based on instructor's interpretation of the university grading system (as defined in Section 23.4 of the Academic Regulations). There is no a priori distribution or formula. See the Grading policy.

Schedule

This schedule is tentative and subject to change. Paper titles and presenters will be added later. You can find the papers assigned to each class here.

Date Topic Lecture Assignment
4/9 Course Logistics slides
6/9 Introduction slides
Module 1: Smart Buildings & Smart Homes
11/9 Platforms for Smart Homes and Buildings — Part 1 slides Paper review
13/9 Platforms for Smart Homes and Buildings — Part 2 Paper review
18/9 Metadata and Semantic Modeling of Buildings Paper review
20/9 Monitoring Occupant Presence and Actions — Part 1 slides Paper review
25/9 Monitoring Occupant Presence and Actions — Part 2 Paper review
27/9 Monitoring Occupant Presence and Actions — Part 3 Paper review
2/10 Monitoring Energy and Water Use Paper review
4/10 Intelligent Building Control Paper review
9/10 Energy Disaggregation Project group signup & paper review
11/10 Blockchain and Smart Contracts slides
Module 2: Smart Grid
16/10 Data Acquisition and Storage slides Paper review
18/10 Data Analytics slides Project proposal & paper review
23/10 Load Scheduling, Demand Response, and Incentive Design — Part 1 Paper review
25/10 Load Scheduling, Demand Response, and Incentive Design — Part 2 Paper review
30/10 No Class — Students must work on their project
1/11 Optimal Control of Distributed Energy Resources — Part 1 Paper review
6/11 Optimal Control of Distributed Energy Resources — Part 2 Paper review
8/11 Cyber Security and Privacy Paper review
13/11 No Class — Fall term reading week
15/11 No Class — Fall term reading week
Module 3: Smart Cities & Intelligent Transportation Systems
20/11 Mobility Modeling Paper review
22/11 Urban Computing & Planning — Part 1 Paper review
27/11 Urban Computing & Planning — Part 2 Paper review
29/11 Project Presentation
4/12 Project Presentation
6/12 Project Presentation
14/12 Project report

Resources

Students can use the following data sets, models, and tools in their projects:

  • Minutely and hourly solar irradiation data from several measurement sites in the United States [Link]
  • One-second measurements of real and reactive power consumption of 30 homes in Austria [Link]
  • One-minute electricity, gas, and water use data from hundreds of customers [Link]
  • A tool that generates household electricity, gas, hot water, and cold water data [Link]
  • micro-PMU data from LBL locations [Link]
  • A collection of Python libraries for simulating the irradiation of any point on earth [Link]
  • A public data set for energy disaggregation (REDD) [Link]
  • Smart* home and microgrid data sets [Link]
  • A data set that contains electricity, water, and natural gas measurements at one minute intervals (AMPds) [Link]
  • An online tool for obtaining a solar estimate for the area, based on the amount of usable sunlight and roof space [Link]
  • A toolkit for evaluating the accuracy of Non-Intrusive Load Monitoring (NILM) algorithms [Link]
  • System Advisor Model (SAM) for renewable energy projects [Link]
  • Lab of Things platform for IoT research [Link]
  • 'Dark Sky' weather forecast API [Link]
  • GridPV toolbox to model and simulate the integration of distributed generation into the electric power system [Link]
  • UK domestic appliance-level electricity dataset [Link]
  • Markov models for residential electricity consumption [Link]
  • A dataset of high resolution electric power and voltage profiles of Austrian households [Link]
  • Measurements of Volatile Organic Compounds from a movie theater over a month in intervals of thirty seconds [Link]
  • Smart Grid Store for smart meter data storage and analytics [Link]
  • EnergyPlus™ whole building energy simulator and DOE reference building models [Link and Link]
  • A dataset consisting of metadata of 180,000 points across 55 campus buildings [Link]
  • New York City Taxi and Uber data [Link]
  • Roadsindb provides a representation of road networks, and a dataset of parking spots, resturants, and taxi mobility traces in San Francisco [Link]
  • PJM data sets (generation, load, load forecast, energy market, etc.) [Link]

Apart from these resources, students are encouraged to use other publicly available data sets or collect data using the sensors that they deploy.

Evaluation

Students will be graded as follows:

  • 5% Class Participation,
  • 30% Paper Presentations,
  • 15% Paper Reviews (due 1:00PM on the day of the lecture),
  • 10% Project Proposal (due 11:59PM, October 18th),
  • 40% Final Project (due 11:59PM, December 14th).

Students are expected to attend the lectures, take an active part in the discussions, and ask questions. Participation marks will be given by the instructor based on in-class discussion of papers.

Marks are translated into letter grades based on your rank in the class. The instructor reserves the right to adjust final grades up or down in light of the overall distribution of marks.

Policies

Academic integrity

The University of Alberta is committed to the highest standards of academic integrity and honesty. Students are expected to be familiar with these standards regarding academic honesty and to uphold the policies of the University in this respect. Students are particularly urged to familiarize themselves with the provisions of the Code of Student Behaviour (online at www.governance.ualberta.ca) and avoid any behaviour which could potentially result in suspicions of cheating, plagiarism, misrepresentation of facts and/or participation in an offence. Academic dishonesty is a serious offence and can result in suspension or expulsion from the University.

For more information about academic integrity consult the Truth in Education website (http://www.tie.ualberta.ca)

Note about recording and/or distribution of course materials

Audio or video recording of lectures, labs, seminars or any other teaching environment by students is allowed only with the prior written consent of the instructor or as a part of an approved accommodation plan. Student or instructor content, digital or otherwise, created and/or used within the context of the course is to be used solely for personal study, and is not to be used or distributed for any other purpose without prior written consent from the content author(s).

Student accessibility services

Eligible students have both rights and responsibilities with regard to accessibility-related accommodations. Consequently, scheduling ​exam accommodations in accordance with SAS deadlines and procedures is essential. Please note adherence ​to procedures and deadlines​ is required for U of A to provide accommodations. Contact SAS (http://www.ssds.ualberta.ca/) for further information.

Student success centre

Students who require additional help in developing strategies for better time management, study skills or examination skills should contact the Student Success Centre (2-300 Students’ Union Building). For assistance with writing, contact the Centre for Writers (1-42 and 1-23 Assiniboia Hall).

Course outline

Policy about course outlines can be found in Section 23.4(2) of the University Calendar. The University Calendar is available online at http://www.registrar.ualberta.ca/calendar

Disclaimer

The course outline is subject to change. All changes will be announced in class.