Machine Intelligence for the NEST Thermostat (MINT) 

Project Overview 

The NESTAI project aims to significantly enhance the artificial intelligence capabilities of the Google Nest Thermostat, moving beyond basic schedule memorization. The project will develop an intelligent temperature management system that dynamically maintains user comfort by factoring in external weather fluctuations, individual activity levels, sleep schedules, and HVAC heat loads. Initially, the team will create a pre-training dataset informed by fundamental heat transfer principles to establish baseline comfort parameters. Subsequently, personal preference data will be collected, allowing the AI to continually adapt and retrain itself, fine-tuning its temperature control responses to the specific lifestyle and comfort needs of individual users.

Objectives 

  1. To develop a baseline comfort model using fundamental heat transfer principles. 
  2. To establish a robust data collection system for capturing user-specific comfort preferences. 
  3. To create an adaptive AI capable of refining temperature management based on ongoing personal and environmental data.

Major Tasks 

he 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. 

  • Research and analyze heat transfer principles related to human thermal comfort.  
  • Develop initial baseline comfort prediction models.  
  • Design and implement methods for collecting personalized comfort data.  
  • Conduct field data collection from diverse user groups.  
  • Train and retrain AI models based on collected user preference data.  
  • Test and validate AI model predictions and user comfort adaptations.  
  • Document system capabilities and outcomes in a final comprehensive report. 

Preferred Skills and Interests 

  • Interest in artificial intelligence and machine learning  
  • Knowledge or interest in thermodynamics and heat transfer principles  
  • Comfort with data collection methodologies and user studies  
  • Programming skills (Python preferred)  
  • Enthusiasm for interdisciplinary collaboration (engineering, building construction, hospitality management, etc.)  
  • Strong problem-solving skills and adaptability 

How to Apply 

Applications will be reviewed by Dr. Gray and by continuing/former researchers from the team.  After a review of the application, our team will contact candidates to schedule a zoom screening interview.  Review for positions will be conducted either during Summer (for Fall on-boarding) or Winter (for Spring on-boarding). Please complete the MS Form, uploading 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 to Dr. Gray (dagray3@vt.edu) if you have any questions or concerns. 

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