GrayUR Undergraduate Research for Credit - Machine Learning for Residential HVAC
Machine Intelligence for the NEST Thermostat
Project Overview
The Nest thermostat is an intuitive thermostat that learns temperature settings through user input. This thermostat was designed to optimize the temperature control and make homes more efficient. However, we asked, what if we could make the Nest more intuitive? How could we expand the current capabilities of the Nest? The Nest is a smart device that solely uses user input to predict and set the temperature for the house at a certain time. It does not account for heat loss which occurs in any location with this thermostat, nor does it account for changes in temperature as the year passes on. So, the goal of this project is to create a system that can account for heat loss and provide the Nest with the ideal temperature needed to achieve optimal user comfort.
Objectives
- Collect adequate data for model training
- Demonstrate refined classification model
- Demonstrate classification accuracy
- Develop alpha version predictive model
Major Tasks
The major tasks of the project are outlined below. These are nominal and are likely to change somewhat throughout the course of the year. These are meant to illustrate the general nature of the work that the position entails.
- Refine data collection hardware
- Deploy additional sensor nodes
- Revise data cleaning algorithms
- Develop and demonstrate system to validate model classification
- Complete next generation classification model training
- Implement voting algorithms for data disagreement
- Implement alpha version predictive model
- Develop predictive data collection systems
General Responsibilities of the Group
Students participating in the GrayUR undergraduate research group will register for an ENGE 2994 or ENGE 4994 undergraduate research course. Typically, students enroll for a 1 credit-hour course load. Under certain circumstances, we can look at extending this up to as many as 3 credits per semester and can sometimes explore technical elective credit within your major. Though not required, the expectation is that you will continue on with the team for two semesters, though we will examine the relationship at the end of the fall semester.
In addition to the major technical tasks listed above, all members of the GrayUR undergraduate research team should expect
- To devote ~3 hours/week to research for each credit hour
- To attend a biweekly team meeting with Dr. Gray
- To attend a monthly all-hands meeting with Dr. Gray
- To participate in periodic reporting (symposia, research poster sessions, etc.)
Major Deliverables
All student teams will have the following deliverables
- One progress presentation to the entire GrayUR group each semester
- Final project reporting
- Final report
- Final slides
- Final personal reflection
Open Positions
Specific Role(s)
- Thermal data collection researcher.
- Duties associated with hardware and software development for data collection, data preprocessing, data validation hardware and procedures.
Preferred Majors
- ME
- CpE
- EE
- CS
- CEE
- Phys
Preferred Academic Years
Looking for Sophomore/Junior level students
Preferred Skills and Interests
- heat flow
- residential HVAC
- mechanical design and assembly
- electrical design and assembly
- arduino/PI coding
- sensor deployment
- data collection
- data modeling
How to Apply
Applications will be reviewed by Dr. Gray and by continuing researchers on the team. After a review of the application, our team will contact candidates to schedule an interview (likely to be conducted via zoom). Review for the positions will begin on Bastille Day, 2022, and will continue until all positions are filled. Please send an email to Dr. David Gray (dagray3@vt.edu) with the following deliverables;
- A brief (~1 page) essay or cover letter explaining which of the projects you are interested in, and why you think you might be a good fit for that project (or those projects). If you are applying for multiple projects, extend your essay a little and describe your interest and qualifications for each position. Be sure to let us know your major and where you are in your academic career (sophomore, junior, etc.)
- A resume outlining your work experience and education
Please reach out if you have any questions or concerns.
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