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公开(公告)号:US12284463B2
公开(公告)日:2025-04-22
申请号:US18203173
申请日:2023-05-30
Applicant: Cisco Technology, Inc.
Inventor: Jay Kemper Johnston , David C. White, Jr. , Magnus Mortensen
IPC: H04N7/15 , G06F3/0484 , G08B25/00 , H04L65/403
Abstract: This disclosure describes techniques for providing notifications about events that occur during an online meeting. For instance, a system may establish an online meeting, such as a video conferencing meeting, for users. While in the meeting, a first user may view video of a second user and determine that the second user is experiencing an emergency event. As such, a user device of the first user may receive an input indicating that the emergency event is occurring with the second user. The system may receive the indication from the user device and verify that the emergency event is occurring. Additionally, the system may then send a notification to emergency personnel that indicates at least that the emergency event is occurring and a location of the second user. Furthermore, the system may send notification(s) to contact(s) associated with the second user that indicate at least that the emergency event is occurring.
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公开(公告)号:US12212451B2
公开(公告)日:2025-01-28
申请号:US18241682
申请日:2023-09-01
Applicant: Cisco Technology, Inc.
Inventor: Magnus Mortensen , Jay Kemper Johnston , David C. White, Jr.
IPC: H04L41/0631 , G06N3/08 , H04L41/0654
Abstract: In one embodiment, an issue analysis service obtains telemetry data from a plurality of devices in a network across a plurality of time intervals. The service detects a failure event in which a device in the network is in a failure state. The service clusters the telemetry data obtained prior to the failure event into rounds according to time intervals in which the telemetry data was collected. Each round corresponds to a particular time interval. The service applies a machine learning-based classifier to each one of the rounds of clustered telemetry data to identify one or more common traits appearing in the telemetry data for each round. The service generates a trait change report indicating a change in the one or more common traits appearing in the telemetry data across the rounds leading up to the failure event.
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公开(公告)号:US20240394721A1
公开(公告)日:2024-11-28
申请号:US18790270
申请日:2024-07-31
Applicant: Cisco Technology, Inc.
Inventor: David C. White, JR. , Jay K. Johnston , Magnus Mortensen , Christopher Shaun Roberts , Felipe De Mello
IPC: G06Q30/016 , G06N3/008 , G06N20/00
Abstract: A computer executed process for mimicking human dialog, referred to herein as a “humanoid” or “humanoid system,” can be configured to provision itself to provide automated customer support. The humanoid can be trained for a customer support campaign. The training can include the humanoid observing communications between a human operator and at least one customer regarding at least one customer support case in the customer support campaign. The humanoid can assess at least one confidence level of the humanoid for the customer support campaign to determine whether the humanoid is adequately trained to handle future customer support cases for the customer support campaign. The humanoid can provision itself to handle at least one future customer support case in the customer support campaign in response to determining that it is adequately trained for the customer support campaign.
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公开(公告)号:US12118568B2
公开(公告)日:2024-10-15
申请号:US17159886
申请日:2021-01-27
Applicant: Cisco Technology, Inc.
Inventor: David C. White, Jr. , Jay K. Johnston , Magnus Mortensen , Christopher Shaun Roberts , Felipe De Mello
IPC: G06Q30/016 , G06N3/008 , G06N20/00
CPC classification number: G06Q30/016 , G06N3/008 , G06N20/00
Abstract: A computer executed process for mimicking human dialog, referred to herein as a “humanoid” or “humanoid system,” can be configured to provision itself to provide automated customer support. The humanoid can be trained for a customer support campaign. The training can include the humanoid observing communications between a human operator and at least one customer regarding at least one customer support case in the customer support campaign. The humanoid can assess at least one confidence level of the humanoid for the customer support campaign to determine whether the humanoid is adequately trained to handle future customer support cases for the customer support campaign. The humanoid can provision itself to handle at least one future customer support case in the customer support campaign in response to determining that it is adequately trained for the customer support campaign.
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公开(公告)号:US20240144918A1
公开(公告)日:2024-05-02
申请号:US17977353
申请日:2022-10-31
Applicant: Cisco Technology, Inc.
Inventor: David C. White, JR. , Jay K. Johnston , Magnus Mortensen
Abstract: A method, computer system, and computer program product are provided for improving user speech. A data sample of a user speaking one or more words is received, wherein the data sample includes video data and audio data of the user speaking. The data sample is analyzed to determine a correct articulation of a mouth when speaking the one or more words. A synthetic video of the user performing the correct articulation is generated. The synthetic video of the user is presented to the user. A live video of the user is presented to the user while the synthetic video is presented.
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公开(公告)号:US20240135388A1
公开(公告)日:2024-04-25
申请号:US18497103
申请日:2023-10-29
Applicant: Cisco Technology, Inc.
Inventor: David C. White, JR. , Jay K. Johnston , Magnus Mortensen , Christopher Shaun Roberts , Kevin D. McCabe
IPC: G06Q30/016 , G06Q10/0639 , H04L51/02
CPC classification number: G06Q30/016 , G06Q10/06395 , H04L51/02 , G06Q10/103
Abstract: A computer executed process for mimicking human dialog, referred to herein as a “humanoid” or “humanoid system,” can be configured to provide automated customer support. The humanoid can identify a support issue for a customer, as well as a customer support campaign corresponding to the support issue. The humanoid can identify at least one machine learning model associated with the customer support campaign and can communicate with the customer using the at least one machine learning model. The humanoid can execute a support action to resolve the support issue.
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公开(公告)号:US20230412451A1
公开(公告)日:2023-12-21
申请号:US18241682
申请日:2023-09-01
Applicant: Cisco Technology, Inc.
Inventor: Magnus Mortensen , Jay Kemper Johnston , David C. White, JR.
IPC: H04L41/0631 , H04L41/0654 , G06N3/08
CPC classification number: H04L41/0636 , H04L41/0654 , G06N3/08
Abstract: In one embodiment, an issue analysis service obtains telemetry data from a plurality of devices in a network across a plurality of time intervals. The service detects a failure event in which a device in the network is in a failure state. The service clusters the telemetry data obtained prior to the failure event into rounds according to time intervals in which the telemetry data was collected. Each round corresponds to a particular time interval. The service applies a machine learning-based classifier to each one of the rounds of clustered telemetry data to identify one or more common traits appearing in the telemetry data for each round. The service generates a trait change report indicating a change in the one or more common traits appearing in the telemetry data across the rounds leading up to the failure event.
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公开(公告)号:US11287829B2
公开(公告)日:2022-03-29
申请号:US16446804
申请日:2019-06-20
Applicant: Cisco Technology, Inc.
Inventor: Jay Kemper Johnston , Magnus Mortensen , Kevin Klous , David C. White, Jr.
Abstract: In one embodiment, a supervisory service of a parking area may send a light fidelity (Li-Fi) based advertisement indicative of an offer to send video streams of the parking area to an autonomous vehicle. The supervisory service may receive an acceptance of the offer by the autonomous vehicle that includes an identifier for the autonomous vehicle. The supervisory service may identify one or more video streams of the parking area as associated with the autonomous vehicle based in part on a location of the autonomous vehicle in the parking area. The supervisory service may annotate the one or more identified video streams with metadata regarding a feature of the parking area. The supervisory service may send the annotated one or more video streams to the autonomous vehicle, wherein the autonomous vehicle uses the metadata of the annotated one or more video streams to avoid the feature of the parking area.
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公开(公告)号:US11196614B2
公开(公告)日:2021-12-07
申请号:US16523463
申请日:2019-07-26
Applicant: Cisco Technology, Inc.
Inventor: Magnus Mortensen , Jay Kemper Johnston , David C. White, Jr.
Abstract: In one embodiment, an issue analysis service determines that an issue exists with a device in a network. The service searches a decision tree for a solution to the issue, wherein branch nodes of the decision tree comprise diagnostic checks. The service clusters, based on a determination that a solution to the issue does not exist in the decision tree, telemetry for the device with telemetry for one or more other devices that also experienced the issue. The service uses a neural network to identify a difference between the clustered telemetry and telemetry from one or more devices for which the issue was resolved. The service adds a leaf node to the decision tree with the identified difference as a solution to the issue.
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公开(公告)号:US11121941B1
公开(公告)日:2021-09-14
申请号:US16817577
申请日:2020-03-12
Applicant: Cisco Technology, Inc.
Inventor: Jay Kemper Johnston , Magnus Mortensen , David C. White, Jr.
Abstract: This disclosure describes techniques for monitoring communications in an application cloud infrastructure. The techniques may include determining whether a performance issue associated with the communications is related to an application server for a hosted application, or to a computing network that transmits the communications across the application cloud infrastructure. The techniques may also further include testing to define a performance issue, and/or taking action in response to a performance issue, including potentially mitigating the performance issue. As such, monitoring communications may help improve network performance by efficiently identifying and isolating instances of potential performance degradation.
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