Live Case – Project

Select Machine Learning Framework for Analyzing Data in order to Optimize HVAC Systems

A Collaboration Between

Engagement Synopsis

Interns will have an opportunity to work on adding ML capabilities to our Industrial Internet of Things (IIOT) platform, and related toolsets and technology related to HVAC systems. Throughout the project, students will work with faculty mentors and Eco-Enterprise leadership to analyze data and further exploration of data analysis techniques for use in a machine learning application.
Students will be responsible for getting up-to-speed on outcomes derived from the previous project completed over the summer. Next, students will be responsible for reviewing and cleaning data to better understand what is feasible to use within a machine learning framework. Lastly, students will be working on researching machine learning techniques that can apply to the data set in order to accomplish outcomes that align with the project goal.
The ultimate goal is to help Eco-Enterprise develop machine learning technology that can optimize efficiency within HVAC systems, which are expensive and resource intensive to run.

Company Information

CompanyEco-Enterprise
HQNew Jersey
RevenueN/A
Employees1-5
StageSmall Business
Hiring PotentialFollow-on Projects, Formal Internship, Entry Level Full-Time, Upper Level Full-Time
Websitehttp://Eco-Enterprise.com

Company Overview

eco-enterprise helps businesses to become more Efficient, Economic and Environmentally responsible via unique financial solutions and energy-saving technologies.

Course Info & Engagement Details

SchoolA&S Experiential Hiring Programs
Engagement FormatLive Case - Class Collaboration or Case Competition - This learning format allows educators to deliver experiential learning to students at scale. Students are often split into groups to work on a live case (or a series of cases) from a real host company that directly relates to key learning objectives.
CourseFacilities Management RFP
Level
  • All Undergraduate
Students Enrolled8
Meeting Day & TimeMonday, Wednesday, Friday: 11:00 AM MT - 11:50 AM MT
Student Time Commitment1-3 Hours Per Week
Company Time Commitment1 Hour
Duration51.57 Weeks

Project Topics

Students

There are currently no students assigned.

Collaboration Timeline

Touchpoints & Assignments Due Date Type
Deadline for Students to Register

Deadline for Students to Register

Students register to the course by this date.
January 13th, 2021 Event na
Students Review Onboarding Materials

Students Review Onboarding Materials

January 22nd, 2021 Event na
Official Project Launch

Official Project Launch

11:00 AM MT: We’ll web conference via Zoom you into our class to kickoff the project. https://umontana.zoom.us/j/95405051063?pwd=Ulo1ek1UaWgrRjAweks1aWZEaWUzZz09
January 25th, 2021 Event na
Kickoff Evaluation Due

Kickoff Evaluation Due

February 5th, 2021 Event na
Milestone Deliverable #1 Due Milestone Deliverable #1 Due
Please upload your deliverable for milestone #1
February 27th, 2021 Submission Required submission-required
Temperature Check Survey Due

Temperature Check Survey Due

March 5th, 2021 Event na
FINAL PRESENTATIONS

FINAL PRESENTATIONS

We’ll find a time on this day to web conference via Zoom to close the project. https://umontana.zoom.us/j/95405051063?pwd=Ulo1ek1UaWgrRjAweks1aWZEaWUzZz09
April 23rd, 2021 Event na
Milestone Deliverable #2 Due Milestone Deliverable #2 Due
Please upload your final presentation for Milestone #2
April 23rd, 2021 Submission Required submission-required
End of Term SELF Evaluation

End of Term SELF Evaluation

April 30th, 2021 Event na
End of Term PEER Evaluation

End of Term PEER Evaluation

April 30th, 2021 Event na

Key Milestones & Project Process

  • February 15, 2022 - Get up-to-speed on Company Background & Outcomes Derived from Summer

    • Background of Eco-Enterprise business model and offering
    • Deep dive into HVAC use-case
    • Read final reports developed by students from Summer term
    • Learn about the different algorithms that have been packaged
    • Review process of cleaning data to prepare it to run through algorithms

    Suggested Deliverable:

    • Background presentation on Eco-Enterprise summer 2021 performance and jobs to done for Fall 2021 project, including a timeline and high-level detail of action items
  • February 22, 2022 - Review Data, Scrubbing Process, & Machine Learning Strategy to Understand Algorithm Use-Case

    • What Algorithm packages are currently being used? How? What outcomes does this develop?
    • How far along has the team gotten on choosing the machine learning framework for this intended outcome?
    • What is the ultimate goal of the machine learning Algorithm?
    • How does the data need to be organized in order for the Algorithm to work?
    • Can you help prepare the data
    • What other machine learning tools and Algorithms might work for this data set? Are they worth testing, why or why not?

    Suggested Deliverable:

    • Present progress on data pipeline and Machine Learning Strategy you will be using for the remainder of the project
  • March 7, 2022 - Present Machine Learning Strategy & Sample Outcomes from the Model

    • Description of process including data cleaning and use of machine learning tool
    • Training materials and instructions for running through the process including preparing the data, how to execute, how to use/maintain
    • Sample detailed outcomes from testing process with explainer content
    • Advantages and disadvantages of moving forward with this model
    • Detail any error analysis

    Suggested Deliverable:

    Present Machine Learning Strategy & Sample Outcomes from the Model

Project Resources

There are no resources currently available

Company Supervising Team

There are currently no supervisors assigned.

School Supervisors

There are currently no supervisors assigned.