Abstract: Audio sensors collaborate for geo-location and tracking of health conditions for multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of a health event of concern, in view of the estimated location, a command for an AI action, such as contacting a hospital server or adapting to monitor a suspected health condition, is received for a response to the health event at the AI clients that detected the health event, or others.

Abstract: Audio sensors collaborate for geo-location and tracking of health conditions for multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of a health event of concern, in view of the estimated location, a command for an AI action, such as contacting a hospital server or adapting to monitor a suspected health condition, is received for a response to the health event at the AI clients that detected the health event, or others.

Abstract: Audio sensors collaborate for geo-location and tracking of multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of the event in view of the estimated location, a command for an AI action, such as connecting a call between users, is received for a response to the event at the AI clients that detected the event, or others.

Abstract: Audio sensors collaborate for geo-location and tracking of multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of the event in view of the estimated location, a command for an AI action, such as connecting a call between users, is received for a response to the event at the AI clients that detected the event, or others.

Abstract: Aspects of the present disclosure relate to synchronizing presentation of content in head-worn computing systems including linking the multiple users to the same access point in the cloud, the users indicating to the cloud that they would like to participate in a synchronized experience of the content and identifying, by the cloud, how many head-worn computers will be included in the synchronized experience of the content. The method further includes downloading the content to the multiple head-worn computers from the cloud, polling the multiple head-worn computers to determine the percentage of the content that has been downloaded to each of multiple head-worn computers, and when all of the multiple head-worn computers has exceeded a predetermined percentage of content that has been downloaded, sending a start command from the cloud to each of the head-worn computers simultaneously to begin a synchronized presentation of the content to all of the multiple users.

Abstract: Audio sensors collaborate for geo-location and tracking of multiple users. Different users can be independently geo-located and tracked within the AI environment. Location is determined from two or more AI clients of known locations that detect an event such as a human voice command to connect a call with a specific user. Responsive to classification of the event in view of the estimated location, a command for an AI action, such as connecting a call between users, is received for a response to the event at the AI clients that detected the event, or others.