Reference number : GC-2017-Q2-04347, amendment number : , agreement type : G, recipient legal name : England, Andrea (Sheridan Institute of Technology and Advanced Learning), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for Colleges, program name french : Subventions d'engagement partenarial pour les collèges, program purpose english : Mobile apps enable companies to place maintenance/repair service requests instantly from anywhere and track_x000D_
their progress with real-time updates. However, real-time automatic identification of equipment that is_x000D_
experiencing a technical issue would be even more valuable information for both service providers and facility_x000D_
managers._x000D_
GetResQ Ltd., the industry partner for this research collaboration with Sheridan College, currently has a mobile_x000D_
app that offers a variety of innovative solutions for restaurant maintenance needs. Through this proposed_x000D_
Engage grant, GetResQ aims to add a new service to the mobile app to identify specific equipment in a facility_x000D_
based on a digital image of the equipment. The Sheridan research team proposes to design, implement and test_x000D_
an algorithm to enable this service. The proposed algorithm is based on a combination of template matching_x000D_
and machine learning algorithms using feature-based techniques such as Edge. For example, when a facility_x000D_
manager notices an equipment issue, he could simply take a photo of the equipment and the mobile app would_x000D_
automatically identify the equipment and notify the appropriate technical team. The algorithm aims to target_x000D_
dense environments that contain adjacent similar equipment where automatic identification of specific_x000D_
equipment is complex. The applied research to be undertaken during this project will add useful features to_x000D_
GetResQ's current mobile app, thereby attracting new customers. In addition, it will engage students in_x000D_
addressing real-world problems, which will increase their potential for contributing to future innovation., program purpose french : Mobile apps enable companies to place maintenance/repair service requests instantly from anywhere and track_x000D_
their progress with real-time updates. However, real-time automatic identification of equipment that is_x000D_
experiencing a technical issue would be even more valuable information for both service providers and facility_x000D_
managers._x000D_
GetResQ Ltd., the industry partner for this research collaboration with Sheridan College, currently has a mobile_x000D_
app that offers a variety of innovative solutions for restaurant maintenance needs. Through this proposed_x000D_
Engage grant, GetResQ aims to add a new service to the mobile app to identify specific equipment in a facility_x000D_
based on a digital image of the equipment. The Sheridan research team proposes to design, implement and test_x000D_
an algorithm to enable this service. The proposed algorithm is based on a combination of template matching_x000D_
and machine learning algorithms using feature-based techniques such as Edge. For example, when a facility_x000D_
manager notices an equipment issue, he could simply take a photo of the equipment and the mobile app would_x000D_
automatically identify the equipment and notify the appropriate technical team. The algorithm aims to target_x000D_
dense environments that contain adjacent similar equipment where automatic identification of specific_x000D_
equipment is complex. The applied research to be undertaken during this project will add useful features to_x000D_
GetResQ's current mobile app, thereby attracting new customers. In addition, it will engage students in_x000D_
addressing real-world problems, which will increase their potential for contributing to future innovation., agreement title english : Smart Equipment Detector, agreement title french : Smart Equipment Detector, agreement number : CARD1, agreement value : 25000.0, agreement start date : 2017-09-20, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada