公开(公告)号：US11960540B2

公开(公告)日：2024-04-16

申请号：US17800006

申请日：2020-06-19

申请人： MOTOROLA SOLUTIONS, INC.

发明人： Pawel Wilkosz ,  Lukasz Osuch ,  Krzysztof Jasinski ,  Marcin Lukasik

IPC分类号： G06F16/78 ,  G06F16/58 ,  G06F16/953 ,  G16Y20/10 ,  G16Y30/00 ,  G16Y40/10

CPC分类号： G06F16/7867 ,  G06F16/5866 ,  G06F16/953 ,  G16Y20/10 ,  G16Y30/00 ,  G16Y40/10

摘要： 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.

公开(公告)号：US12100214B2

公开(公告)日：2024-09-24

申请号：US17661919

申请日：2022-05-04

申请人： MOTOROLA SOLUTIONS, INC.

发明人： Janusz Szuba ,  Krzysztof Jasinski ,  Piotr Matejanka ,  Pawel Wilkosz

IPC分类号： G06V20/52 ,  G06V10/774

CPC分类号： G06V20/52 ,  G06V10/7747

摘要： 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.