2 Syllabus
This syllabus will be continuously updated throughout the course.
2.1 Course Description
We spend a significant portion of our lives inside buildings: working, sleeping, and on leisure activities. Unsurprisingly, buildings are responsible for over 40% of our annual greenhouse gas emissions. The history of buildings goes hand in hand with the history of energy efficiency, as we have moved from non-renewable/inefficient fuel sources and technologies (e.g., firewood, cookstoves) to more renewable/efficient ones (e.g., solar energy, heat pumps). Increasing efficiency has also resulted in tighter integration between buildings, their systems, and the supporting services. All of these trends have led to an explosion in the number of instrumentation systems (for monitoring and/or controlling) installed in buildings, and an associated increase in the number and complexity of the decisions that are being (and can be) made in light of these new instruments. Autonomous technologies (which make decisions on our behalf in order to achieve pre-established goals) are well suited to address the challenges that these information-rich and highly-interconnected buildings pose.
With a focus on real-world deployments, case studies and group projects, this course will cover the theory and emerging practice of retrofitting existing buildings with hardware and software to significantly increase their autonomy and overall sustainability. The focus will be primarily on the operational stage of the life-cycle of buildings, and particularly on HVAC, electrical and water systems within them. In particular, this course will expose the students to recent advances in the quest to endow buildings with the ability to operate autonomously (i.e., with minimal human assistance), in order to provide the services they were designed for, while maintaining quality of service and upholding human values such as privacy, equity and environmental sustainability. The course will be based on lectures, assignments and a final project where the students will have the opportunity to design and implement an autonomous technology and evaluate it through a hardware-in-the-loop experiment in the lab. This course builds upon machine learning, statistics, data acquisition and instrumentation, linear systems and control theory.
It is intended to be a upper-graduate level course (i.e., for Ph.D. students or senior M.S. students) interested in gaining practical exposure to the state-of-the-art in data science for building systems. As such, the format of the course is tailored to that experience and will include reading and critiquing recent publications in the field, learning to implement data analysis techniques described in them, and producing novel results using these newly acquired skills.
The course assumes students are familiar with concepts in instrumentation, linear algebra, probability, statistics and programming, though this is not a strict requirement if the student has previously discussed with the instructor and has received approval.
2.2 Grading:
Here is how performance in the course will be evaluated:
| Task | Percentage |
|---|---|
| Assignments | 40% |
| Interim Project Progress Update | 20% |
| Final Project Report and Demo | 40% |
2.2.1 Assignments
A total of four assignments will be given out. The topics covered in each assignment will closely follow the ones listed in the schedule of classes.
All assignments are to be solved individually. Discussions and conversations with other students regarding the problem sets are encouraged. However, the final solutions along with the reasoning behind them need to come from you and be clearly explained in the submitted documents.
Each assignment will be worth 10% and is due at the beginning of class on the date that is indicated in each assignment. Assignments that are submitted before this deadline can receive 100% of the available credit. There is a 3 day grace period for late submissions, with the following available credit in each of those five days: 1 Day Late: 90%, 2 Days late: 70%, 3 Days late: 40%. After this time, assignments will not be graded. Of course, if you anticipate not being able to meet this schedule due to a major problem, please talk to the instructor as soon as possible.
2.2.2 Project Updates
Another small portion (20%) of the grade for the course will be based on a progress update that will take place during the last period of the course. This update will consist of: (1) a written 2-page report, authored by all team members; and (2) a 10 minute individual meeting with the instructor to discuss the project, its goals and the plan forward. The written progress report will confer 10% of the final grade, while the individual meeting discussion will be used to provide the remaining 5%.
The final project report and demonstration are worth almost half of the total grade and, in some ways, are the most important assignment. The written report is worth 30% and the demonstration 10% of the total grade. For the written report, we are asking that you submit it using the ACM BuildSys Template (either LaTeX or MS Word). You should use your own words when writing it and avoid plagiarism of any kind. In it you will describe, in simple terms, the motivation and specific objectives of your project, the design choices made for the hardware and or software prototype that you put together, the experiments you performed to validate whether or not your solution satisfies the objective, and a discussion about the results and limitations. You should make all code and datasets available as part of your submission.
The rubric that will be used for grading the written report is as follows:
- Formatting and organization (15%)
- Grammar, clarity and accuracy of ideas (15%)
- Display of mastery of concepts covered in class (35%)
- Creativity expressed in the solution (10%)
- Depth of discussion related to the pros/cons of the implemented solution (15%)
- Overall assessment of the project’s idea nd execution (10%)
2.3 Course Policies
Though there are definitely reasons to like anarchism, I still prefer the democratic system, so here are the rules of the game as they are now (and subject to change if enough of you request that I do).
2.3.1 Collaboration
Collaboration is expected within the limits of discussing concepts and problems. However, each student must produce his/her own solution to the problems. Copying from another student’s assignment is clearly plagiarism. Using information directly from websites, books, papers and other literary sources without appropriate attribution is also plagiarism. Assignments submitted for this class will be reviewed by the instructor and TA and may be scanned through web-based academic integrity software. Occurrences of cheating or plagiarism will be handled according to the university policy on Academic Integrity, https://www.cmu.edu/policies/documents/Academic%20Integrity.htm. Students are expected to have read this policy and conform to the highest standards of academic integrity. For incidents of academic misconduct, the University Academic Disciplinary Actions Policy, found at https://www.cmu.edu/student-affairs/theword/acad_standards/creative/disciplinary.html, will be followed.
2.3.2 Class Participation
Students are expected to be in class on time and participate in class discussions. If you cannot make class, please inform your instructors and group members ahead of time. In class, students are expected to be courteous and respectful of the views and needs of other students and instructors.
2.3.3 Student with Disabilities
If you have a disability and have an accommodations letter from the Disability Resources office, I encourage you to discuss your accommodations and needs with me as early in the semester as possible. I will work with you to ensure that accommodations are provided as appropriate. If you suspect that you may have a disability and would benefit from accommodations but are not yet registered with the Office of Disability Resources, I encourage you to contact them at access@andrew.cmu.edu.
2.3.4 Posting of course materials
All the material used in the course (syllabus, readings, problem sets, reports) is intended for use in the class only. No unauthorized posting, publication or redistribution is expected. Uploading course materials to Course Hero or other web sites is not an authorized use of the course material.