Motorola Solutions, Inc.

Krzysztof Jasinski

Pawel Wilkosz

Piotr Matejanka

Lukasz Osuch

Janusz Szuba

Marcin Lukasik

Mariusz Jochymczyk

A device, system, and method for implementing role-based machine learning models is provided. A implements a supervisory machine learning model that detects a first role associated with a first object in images received from a camera. The device, from machine learning models, selects and implements a first machine learning model associated with the first role to perform analysis on the images, that is reported to one or more communication devices. After implementing the first machine learning model, the device uses the supervisory machine learning model to determine a second role associated with a second object in the images that is different from the first role, and selects, from the machine learning models, a second machine learning model associated with the second role. The device implements the second machine learning model to perform analysis on the images to change the analysis reported to the one or more communication device.

Device, system, and method for implementing role-based machine learning models

A method and system for improving prediction of an incident affecting public safety is described. At a machine learning analytics system, the method includes obtaining a real-time video for a location of a public safety emergency call and predicting a public safety incident therefrom. At a learning processor, the method includes: receiving information related to the public safety emergency call; identifying a public safety incident type based thereon; receiving the prediction of the public safety incident; using a first public safety incident machine learning model based on the identified public safety incident type and comparing the public safety incident prediction with the information related to the public safety emergency call and identifying an incident prediction mismatch therefrom. The learning processor identifies an artifact in the real-time video that is a contributing factor for the incident prediction mismatch; and implements a model improvement action associated with the artifact.

Video-based public safety incident prediction system and method therefor

A process for tagging incident data captured by non-public-safety agency controlled cameras. In operation, an electronic computing device detects an occurrence of an incident and obtains an incident identifier associated with the incident. The electronic computing device determines that a non-public-safety agency controlled camera is available for capturing incident data corresponding to the incident. The electronic computing device then controls a public-safety agency controlled internet-of-things (IoT) infrastructure deployed at an incident location to emit a signal including one of an audible signal, visible signal, or a combination of audible and visible signals to enable the non-public-safety agency controlled camera to tag incident data using the emitted signal. The electronic computing device links a unique tag representing the emitted signal to the incident identifier. The electronic computing device then searches the incident data captured by the non-public-safety agency controlled camera using the unique tag representing the emitted signal.

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Cracow, Poland

Krzysztof Jasinski