Award Abstract # 1639266
I-Corps: Conceptualizing and Validating an Occupant-aware Predictive Control System

NSF Org: TI
Translational Impacts
Recipient: VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY
Initial Amendment Date: April 28, 2016
Latest Amendment Date: April 28, 2016
Award Number: 1639266
Award Instrument: Standard Grant
Program Manager: Steven Konsek
TI
 Translational Impacts
TIP
 Directorate for Technology, Innovation, and Partnerships
Start Date: May 1, 2016
End Date: May 31, 2017 (Estimated)
Total Intended Award Amount: $50,000.00
Total Awarded Amount to Date: $50,000.00
Funds Obligated to Date: FY 2016 = $50,000.00
History of Investigator:
  • John Taylor (Principal Investigator)
    jet@gatech.edu
Recipient Sponsored Research Office: Virginia Polytechnic Institute and State University
300 TURNER ST NW
BLACKSBURG
VA  US  24060-3359
(540)231-5281
Sponsor Congressional District: 09
Primary Place of Performance: Virginia Polytechnic Institute and State University
750 Drillfield Drive
Blacksburg
VA  US  24061-0001
Primary Place of Performance
Congressional District:
09
Unique Entity Identifier (UEI): QDE5UHE5XD16
Parent UEI: X6KEFGLHSJX7
NSF Program(s): I-Corps
Primary Program Source: 01001617DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 802300
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.084

ABSTRACT

Building ventilation systems are not responsive to occupants, operating according to predetermined schedules to satisfy the maximum number of people that could be in a space. It's comparable to a car that only runs in the highest gear: ineffective, inflexible, and inefficient. Vast amounts of energy are wasted while making people too cold or hot in their offices. Based on a study conducted by Pacific Northwest National Labs there is a potential for 16% energy savings through incorporation of high resolution real-time occupancy data in building automation systems that control heating, ventilation and air conditioning (HVAC) equating to roughly $2.7 billion annually. A survey conducted by Center for Built Environment at UC Berkeley showed that merely 11% of buildings fulfill standards for thermal comfort, and 26% meet air quality requirements, severely impairing occupant satisfaction and productivity. The small array of occupancy sensing products currently on the market are cumbersome, too costly, and tend to focus on narrow aspects of building operation. As a result they've achieved adoption of less than 1% of the total nonresidential real estate market. This I-Corps team is working on a passive sensing system to address this industry-wide blind spot with a cost-effective and easy to deploy system in order to increase building energy efficiency and improve occupant comfort.

This team is working on a distributed sensing solution that will enable building HVAC control systems to respond to and anticipate building occupancy. The complete initial version of the system will include machine learning and computer vision algorithms embedded in the small fully wireless sensors processing data from a low-cost RGB camera and passive infrared sensor that will be able to detect both stationary and moving people across a coverage area of approximately 600 square feet in an open space. By the end of the program the team intends to have completed a software prototype for the image processing portion capable of delivering real-time occupancy counting and prediction using sample building image streams. More importantly, the team plans to have validated the demand in the market for the proposed product through the interviews, investigated the potential privacy concerns from prospective clients, explored value propositions outside of energy efficiency and comfort from advanced occupancy data, and identified the types of real estate clients that we should focus on. The proposed product has the potential to greatly reduce building energy consumption and improve occupant comfort throughout the US, and more broadly make the built environment far more responsive and data-driven. The team's interviews over the course of I-Corps program will be vital in shaping the business model to bring this application of computer vision and machine learning research and development to market.

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Buildings are not responsive to occupants’ behavior, which leads to energy waste and uncomfortable indoor spaces. Based on a study conducted by Pacific Northwest National Labs there is a potential for 16% energy savings through incorporation of high resolution real-time occupancy data in building automation systems. Further, according to a survey conducted by the Center for Built Environment at the University of California at Berkeley, merely 11% of buildings fulfill ASHRAE requirements for thermal comfort, and 26% fulfill the requirements for air quality.

We began this research project to develop a camera sensor based solution that enables building heating, ventilation and air conditioning (HVAC) control systems to anticipate occupant needs based on detected behavior.  We believed this would be a technological solution that would offer financially attractive returns for commercial buildings based on energy cost savings, while also improving tenant satisfaction.  However, the I-CORPS process requires researchers to complete a comprehensive customer discovery phase during which over 200 interviews were conducted.  Along the way it was determined that our initial approach lacked a robust business model.  We pivoted away from this idea and, in the process, created two new technological solutions that are operating as new startups.

In the first of these startups, we retained the camera based sensor concept from our initial technological solution but pivoted to a different market where our designed solution would address a more substantial problem.  OnSiteIQ, formed by the research team’s entrepreneurial lead, focuses on safety analytics through camera sensor based analytics in the construction industry. As part of the customer discovery and prototype development, construction jobsite safety was identified as a key challenge faced in the construction industry. Furthermore, the cost of the safety inspection services and the labor-intensiveness of the process were recognized as root causes of the problem. These challenges are part of OnSiteIQ’s services to provide more affordable and frequent safety inspections to construction projects to improve safety in this industry.

In the second of these startups, we retained the application--improving HVAC system efficiency in buildings--but, we pivoted away from the camera based solution.  Envairo, formed by the research team’s industry mentor, helps offices maximize employee productivity while minimizing real estate operating costs. The company leverages HVAC sensors to determine the number of people in each room, enabling companies to plan and design their office spaces according to actual needs. Beyond monitoring, Envairo optimizes air conditioning and ventilation to ensure high thermal comfort and air quality while reducing energy consumption.

From an intellectual merit standpoint, this project has both expanded the cutting edge of research on HVAC system operation and the use of camera-based sensors to improve construction safety, as well as evolved technologies developed in university laboratories toward commercially viable solutions. Both startup companies have received investment from private sources.  This has created broader impacts for industry and society in several ways.  First, this project resulted in the creation of two startup business which are impacting the careers of the researchers from this project and other individuals they now employ in these ventures.  Second, each of these startups is addressing a broad societal problem.  About three workers per day die on construction sites, OnSiteIQ is working to improve the safety of workers on construction sites.  Commercial office buildings need to deliver for the needs of the people inside, but they do not need to waste resources to do so.  Overventilation when occupancy is low accounts for excess energy use of 16% or $6.4 billion per year in the USA. Envairo is addressing this problem by providing visibility into how spaces are being used and how air conditioning systems are performing.

 


Last Modified: 10/04/2017
Modified by: John E Taylor

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