Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$50,000.00
Jul 1, 2022
For-profit organization
ICAP 2022 – International Co-Innovation Action Plan
994643
This International Co-Innovation Action Program (ICAP) project will prepare the firm to enter into future international co-innovation work.
$180,000.00
Jun 1, 2022
For-profit organization
Enhanced Organic Recognition and Segmentation
991973
The goal of this project is to expand the product offering from heat loss into building cooling and commercial and industrial applications. The project will improve existing machine learning and computer vision techniques on airborne thermal data to detect and segment the components within a thermal scene. This includes buildings, vegetation, walkways, driveways, roads, water bodies, and composite objects such as vegetation over a rooftop.
$37,500.00
Apr 1, 2022
For-profit organization
MyHEAT Inc.-2022-2023-991874
991874
The purpose of this CanExport SMEs agreement is to support small- and medium-sized enterprises (SMEs) for activities related to export market development that are part of an export business case for a specific target market, particularly where activities are targeting departmental priority markets and sectors.
$50,000.00
Nov 1, 2021
For-profit organization
COOL Maps - Machine Learning and Thermal Maps To Detect Inefficient Building Cooling
981783
The goal of the COOL Maps Pilot is to determine if machine learning techniques on airborne acquired thermal data can be used to model building air conditioning efficiency.
$900,655.00
Aug 16, 2021
For-profit organization
000021800
000021800
Increase operational efficiency of thermal mapping platform and increase export sales
$1,650,655.00
Aug 16, 2021
For-profit organization
000021800
000021800
Increase operational efficiency of thermal mapping platform and increase export sales
$900,655.00
Aug 16, 2021
For-profit organization
000021800
000021800
Increase operational efficiency of thermal mapping platform and increase export sales
$1,650,655.00
Aug 16, 2021
For-profit organization
000021800
000021800
Increase operational efficiency of thermal mapping platform and increase export sales
$37,125.00
May 1, 2020
For-profit organization
MyHEAT US & European Expansion
949315
MyHEAT's Engagement Platform is an excellent example of the latest technology that can enhance US & European Energy Efficiency programs. In person meetings with prospects will bring credibility to our exciting product.
$150,000.00
Jun 1, 2019
For-profit organization
Utilizing Machine Learning and Computer Vision To Improve HEAT Ratings
929231
MyHEAT boosts the performance of energy efficiency programs for utilities, governments, and retail partners by utilizing machine learning and large-scale aerial thermal data collection and processing to reveal invisible energy escaping from every residential, commercial and industrial building in a city. This project will test different types of machine learning on our aerial thermal data sets to improve the correlation of our HEAT Rating with consumption and energy efficiency.