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    REFERENCE IMAGE ENROLLMENT AND EVOLUTION FOR SECURITY SYSTEMS
    1.
    发明公开
    REFERENCE IMAGE ENROLLMENT AND EVOLUTION FOR SECURITY SYSTEMS 审中-公开

    公开(公告)号：US20240184868A1

    公开(公告)日：2024-06-06

    申请号：US18427370

    申请日：2024-01-30

    Applicant: INTELLIVISION TECHNOLOGIES CORP

    Inventor： Krishna Khadloya ,  Manuel Gonzalez

    IPC: G06F21/32 ,  G06F18/22 ,  G06N3/08 ,  G06V20/56 ,  G06V40/16

    CPC classification number: G06F21/32 ,  G06F18/22 ,  G06N3/08 ,  G06V20/56 ,  G06V40/172

    Abstract: Person or object authentication can be performed using artificial intelligence-enabled systems. Reference information, such as for use in comparisons or assessments for authentication, can be updated over time to accommodate changes in an individual's appearance, voice, or behavior. In an example, reference information can be updated automatically with test data, or reference information can be updated conditionally, based on instructions from a system administrator. Various types of media can be used for authentication, including image information, audio information, or biometric information. In an example, authentication can be performed wholly or partially at an edge device such as a security panel in an installed security system.

    Enrollment system with continuous learning and confirmation
    3.
    发明授权
    Enrollment system with continuous learning and confirmation 有权

    公开(公告)号：US11921831B2

    公开(公告)日：2024-03-05

    申请号：US17200584

    申请日：2021-03-12

    Applicant: INTELLIVISION TECHNOLOGIES CORP

    Inventor： Krishna Khadloya ,  Manuel Gonzalez

    IPC: G06F21/32 ,  G06F18/22 ,  G06N3/08 ,  G06V20/56 ,  G06V40/16

    CPC classification number: G06F21/32 ,  G06F18/22 ,  G06N3/08 ,  G06V20/56 ,  G06V40/172

    Abstract: Person or object authentication can be performed using artificial intelligence-enabled systems. Reference information, such as for use in comparisons or assessments for authentication, can be updated over time to accommodate changes in an individual's appearance, voice, or behavior. In an example, reference information can be updated automatically with test data, or reference information can be updated conditionally, based on instructions from a system administrator. Various types of media can be used for authentication, including image information, audio information, or biometric information. In an example, authentication can be performed wholly or partially at an edge device such as a security panel in an installed security system.

    Human presence detection in edge devices
    4.
    发明授权
    Human presence detection in edge devices 有权

    公开(公告)号：US11295139B2

    公开(公告)日：2022-04-05

    申请号：US16279512

    申请日：2019-02-19

    Applicant: INTELLIVISION TECHNOLOGIES CORP.

    Inventor： Krishna Khadloya ,  Maxim Sokolov ,  Vaidhi Nathan ,  Chandan Gope

    IPC: G06K9/00 ,  G08B13/196 ,  G06T7/246 ,  G06T7/215

    Abstract: A system and method for detecting human presence in or absence from a field-of-view of a camera by analyzing camera data using a processor inside of or adjacent to the camera itself. In an example, the camera can be integrated with or embedded in another edge-based sensor device. In an example, a video signal processing system receives image data from one or more image sensors and uses a local processing circuit to process the image data and determine if a human being is or is not present during a particular time, interval, or sequence of frames. In an example, the human being identification technique can be used in security or surveillance applications such as for home, business, or other monitoring cameras.

    Audio type detection
    5.
    发明授权
    Audio type detection 有权

    公开(公告)号：US10978050B2

    公开(公告)日：2021-04-13

    申请号：US16280806

    申请日：2019-02-20

    Applicant: INTELLIVISION TECHNOLOGIES CORP.

    Inventor： Krishna Khadloya ,  Chandan Gope ,  Vaidhi Nathan

    IPC: G10L15/16 ,  G10L25/21 ,  G10L25/18 ,  G06N3/08 ,  G06N3/04 ,  G06F9/54 ,  G06N20/10 ,  G06N20/20

    Abstract: Artificial intelligence-based processing can be used to classify audio information received from an audio input unit. In an example, audio information can be received from a microphone configured to monitor an environment. A processor circuit can identify identifying one or more features of the audio information received from the microphone and use a first applied machine learning algorithm to analyze the one or more features and determine whether the audio information includes an indication of an abnormal event in the environment. In an example, the processor circuit can use a different second applied machine learning algorithm, such as a neural network-based deep learning algorithm, to analyze the same one or more features and classify the audio information as including an indication of a particular event type in the environment.

    System and Method for Scalable Cloud Services
    6.
    发明申请
    System and Method for Scalable Cloud Services 审中-公开

    公开(公告)号：US20170195386A1

    公开(公告)日：2017-07-06

    申请号：US15463516

    申请日：2017-03-20

    Applicant: Intellivision technologies Corp.

    Inventor： Vaidhi Nathan ,  Krishna Khadloya ,  Albert Kay ,  Prakash Narayan

    IPC: H04L29/06 ,  G08B13/196 ,  H04L29/08

    CPC classification number: H04L65/4084 ,  G08B13/19613 ,  H04L63/029 ,  H04L63/08 ,  H04L65/608 ,  H04L67/02 ,  H04L67/025 ,  H04L67/04 ,  H04L67/10 ,  H04L67/104 ,  H04L67/1097 ,  H04L67/12 ,  H04L67/20 ,  H04L67/28 ,  H04L67/42 ,  H04L69/40 ,  H04N5/23206 ,  H04N5/23225 ,  H04N7/181

    Abstract: The invention is based, in part, on a system for allowing at least one client to real-time monitor and, or playback at least one real-world recognized event via at least one processor-controlled video camera, said system comprising: a processor; a non-transitory storage medium coupled to the processor; encoded instructions stored in the non-transitory storage medium, which when executed by the processor, cause the processor to: detect a threshold-grade event from audio-video data of a real-world environment captured from a processor-controlled video camera by an event detection module within an event management system applying event detection parameters; analyze the threshold-grade event for categorization into any one of a recognized event by an event recognition module within the event management system applying event recognition parameters; transmit at least any one of a single stream of the recognized event and, or a single stream of a audio-video sequence succeeding and, or preceding the recognized event to a client device; and facilitate at least any one of a user defined playback of the single stream of the recognized event, user defined monitoring of the audio-video sequence preceding and, or succeeding the recognized event, and, or remote provisioning of the processor-controlled video camera, whereby the playback and, or provisioning is facilitated via a client device user interface.

    MULTIPLE-FACTOR RECOGNITION AND VALIDATION FOR SECURITY SYSTEMS
    7.
    发明申请
    MULTIPLE-FACTOR RECOGNITION AND VALIDATION FOR SECURITY SYSTEMS 有权

    公开(公告)号：US20250014409A1

    公开(公告)日：2025-01-09

    申请号：US18735963

    申请日：2024-06-06

    Applicant: INTELLIVISION TECHNOLOGIES CORP

    Inventor： Krishna Khadloya ,  Manuel Gonzalez

    IPC: G07C9/37 ,  G06N3/063 ,  G06N3/08 ,  G06V40/16 ,  G06V40/20 ,  G08B21/22 ,  G08B27/00

    Abstract: A security system can conditionally grant or deny access to a protected area using an artificial intelligence system to analyze images. In an example, an access control method can include receiving candidate information about a face and gesture from a first individual and receiving other image information from or about a second individual. The candidate information can be analyzed using a neural network-based recognition processor that can provide a first recognition result indicating whether the first individual corresponds to a first enrollee of the security system, and can provide a second recognition result indicating whether the second individual corresponds to a second enrollee of the security system. The example method can include receiving a passcode, such as from the first individual. Access can be conditionally granted or denied based on the passcode and the recognition results.

    MULTIPLE-FACTOR RECOGNITION AND VALIDATION FOR SECURITY SYSTEMS
    8.
    发明公开
    MULTIPLE-FACTOR RECOGNITION AND VALIDATION FOR SECURITY SYSTEMS 审中-公开

    公开(公告)号：US20230351831A1

    公开(公告)日：2023-11-02

    申请号：US18197562

    申请日：2023-05-15

    Applicant: INTELLIVISION TECHNOLOGIES CORP

    Inventor： Krishna Khadloya ,  Manuel Gonzalez

    IPC: G07C9/37 ,  G06V40/16 ,  G06V40/20 ,  G06N3/063 ,  G06N3/08 ,  G08B21/22 ,  G08B27/00

    CPC classification number: G07C9/37 ,  G06V40/172 ,  G06V40/20 ,  G06N3/063 ,  G06N3/08 ,  G08B21/22 ,  G08B27/005

    Abstract: A security system can conditionally grant or deny access to a protected area using an artificial intelligence system to analyze images. In an example, an access control method can include receiving candidate information about a face and gesture from a first individual and receiving other image information from or about a second individual. The candidate information can be analyzed using a neural network-based recognition processor that can provide a first recognition result indicating whether the first individual corresponds to a first enrollee of the security system, and can provide a second recognition result indicating whether the second individual corresponds to a second enrollee of the security system. The example method can include receiving a passcode, such as from the first individual. Access can be conditionally granted or denied based on the passcode and the recognition results.

    AUDIO TYPE DETECTION
    9.
    发明申请
    AUDIO TYPE DETECTION 有权

    公开(公告)号：US20210210074A1

    公开(公告)日：2021-07-08

    申请号：US17203269

    申请日：2021-03-16

    Applicant: INTELLIVISION TECHNOLOGIES CORP.

    Inventor： Krishna Khadloya ,  Chandan Gope ,  Vaidhi Nathan

    IPC: G10L15/16 ,  G06N3/08 ,  G06N3/04 ,  G06F9/54 ,  G06N20/10 ,  G10L25/21 ,  G10L25/18 ,  G06N20/20

    Abstract: Artificial intelligence-based processing can be used to classify audio information received from an audio input unit. In an example, audio information can be received from a microphone configured to monitor an environment. A processor circuit can identify identifying one or more features of the audio information received from the microphone and use a first applied machine learning algorithm to analyze the one or more features and determine whether the audio information includes an indication of an abnormal event in the environment. In an example, the processor circuit can use a different second applied machine learning algorithm, such as a neural network-based deep learning algorithm, to analyze the same one or more features and classify the audio information as including an indication of a particular event type in the environment.

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