Machine learning-based device placement and configuration service

A method, a device, and a non-transitory storage medium are described in which a machine learning-based device placement and configuration service is provided. The machine learning-based device placement and configuration system uses regression models calculated from installation and performance dat...

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Bibliographic Details
Main Authors Herson, Andrew W, Kennedy, Christopher, Huszar, Domonkos, Horvath, Istvan S, Rekeczky, Csaba
Format Patent
LanguageEnglish
Published 02.03.2021
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PHYSICS
PICTORIAL COMMUNICATION, e.g. TELEVISION
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Summary:A method, a device, and a non-transitory storage medium are described in which a machine learning-based device placement and configuration service is provided. The machine learning-based device placement and configuration system uses regression models calculated from installation and performance data. The regression model includes data associated with sites at which video cameras were previously installed and tested for detection accuracy levels possibly associated with a service area. With these generated models, information about the physical space, and desired performance criteria, designers optimize camera number, camera placement, and geo-location camera parameters. The device placement and configuration service may find an optimal camera placement and geo-location camera parameter set which satisfy certain criteria. The geo-location parameters include position, height, heading, pitch, and roll. Subsequent to the installation of the video cameras using the calculated geo-location parameters, the system may verify accuracy of detection of the service area, and update the regression model.
Bibliography:Application Number: US202016896366