Fortem Technologies, Inc.

Other

David Preece

Matthew Elliott Argyle

Adam Eugene Robertson

Bryan Alan Davis

James David Mackie

Mikko Valimaki

Matthew Robertson Morin

Brandon Robert Hicks

Marcus Isaac Daley

David A Boyle

Darek Easterly

Leslie J Silver

David Thimm

Bruce Alexander Carpenter

Jennifer Ada Real

Eric Richard Grover

Mitchell Kay Oldroyd

A method and system device provides a unique object identification process by obtaining information from one or more of radar signals, infrared signals, optical signals, audio signals, and other signals. The method includes continuously receiving object data at the device, applying by a machine learning system, a set of parameters to process the object identification and confidence level, and outputting or updating the object identification, confidence level, and actionable recommendations. The radar data includes a Doppler signature having a wrapped signal due to a sampling rate of the radar system. The Doppler signature is used to train the machine learning system to identify drone types.

System and method for drone and object classification

Systems, methods, and computer-readable media are described using radar systems to avoid vehicle collisions. An example radar system can include antennas mounted on an aircraft, where each antenna has a different orientation facing a different direction away from the aircraft. The radar system can include one or more processing devices and a computer-readable storage medium storing instructions which, when executed by the one or more processing devices, cause the radar system to coordinate digital beam steering and digital beam forming with the antennas to produce a radar coverage area that includes a portion of an airspace around the aircraft; detect, based a signal transmitted by the antennas using the digital beam steering and digital beam forming, an object within the radar coverage area; and generate collision avoidance information including an indication of the object detected within the radar coverage area and/or an instruction for avoiding a collision with the object.

Using radar sensors for collision avoidance

In one embodiment, a visual reporting system generates a 3-dimensional (3D) interactive vehicle inspection report comprising 3D model data and inspection data for a particular vehicle. The inspection data, such as recommended repair items, are associated with graphical vehicle sections in the 3D model. Further, additional inspection data, such as instructional videos or inspection photographs, can be provided to a user desiring additional detail. By providing an interactive visual representation of inspection data, the 3D inspection report provides a report that can be customized to provide different levels of detail to different users. In addition, the 3D model can provide a visually compact summary of the inspection data by marking on the 3D model the repair items for the vehicle. Use of the 3D inspection report can raise the likelihood that the vehicle owner understands the need for repair, leading to more repair orders for repair facilities.

Inspection reporting including a 3D vehicle model

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Elk Ridge, UT, United States of America

David Preece