Abstract:
The disclosure generally relates to Internet of Things (IoT) device social networking, and in particular to an IoT device publish-subscribe messaging model and automatic IoT device social network expansion. For example, IoT devices from different networks may publish status data that relates to certain topics, wherein the published status updates may be managed in a distributed manner at each IoT network. Furthermore, IoT devices interested in published data can subscribe to data relating to certain topics, which may be used to dynamically adjust actions that the subscribing IoT devices may take. Furthermore, IoT devices can employ common social networking capabilities (e.g., refer, follow, like, publish, subscribe, etc.) to interact with other IoT devices and find relevant information from other IoT devices that can be used to improve performance and effectiveness.
Abstract:
The disclosure relates to collaborative intelligence and decision-making in an Internet of Things (IoT) device group. In particular, various IoT devices in the group may be interdependent, whereby a decision that one IoT device plans may impact other IoT devices in the group. Accordingly, in response to an IoT device planning a certain decision (e.g., to transition state or initiate another action), the IoT devices in the group may collaborate using distributed intelligence prior to taking action on the planned decision. For example, a recommendation request may be sent to other IoT devices in the group, which may then analyze relationships within the group to assess potential impacts associated with the planned decision and respond to approve or disapprove the planned decision. Based on the responses received from the other IoT devices, the IoT device may then determine whether to take action on the planned decision.
Abstract:
Methods and apparatuses for optimizing performance using data from an Internet of Things (IoT) device with analytics engines. The method receives, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices. The method retrieves, from memory of an analytics engine, at least the portion of the received data. The method calculates, in a calculator of the analytics engine, the trend data based on at least the portion of the received data. The method transmits, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.
Abstract:
An aspect enables context aware actions among heterogeneous Internet of Things (IoT) devices. An IoT device receives data representing a context of each of a first set of IoT devices, receives data representing a current state of each of a second set of IoT devices, and determines an action to perform at a target IoT based on the received data. An aspect verifies an implied relationship between a first user and a second user by detecting an interaction between a first user device belonging to the first user and a second user device belonging to the second user, storing information related to the interaction in a first interaction table associated with the first user device, assigning a relationship identifier to the second user based, at least in part, on the information related to the interaction, and determining whether or not the assigned relationship identifier is correct.
Abstract:
Hosting a group call at a wireless user device (500B; 600B; 700A). An embodiment receives (520; 810), by the wireless user device, registration information for a plurality of client devices (500A; 500B; 500C; 600A; 600B; 600C; 600D), receives (610; 830), by the wireless user device, a call request for a call among two or more of the plurality of client devices, sets up (620; 710; 840), by the wireless user device, the call among the two or more of the plurality of client devices, receives (670; 850), by the wireless user device, a media stream, and transmits (680; 750; 860), by the wireless user device, the media stream to at least one of the two or more of the plurality of client devices.
Abstract:
An aspect enables context aware actions among heterogeneous Internet of Things (IoT) devices. An IoT device receives data representing a context of each of a first set of IoT devices, receives data representing a current state of each of a second set of IoT devices, and determines an action to perform at a target IoT based on the received data. An aspect verifies an implied relationship between a first user and a second user by detecting an interaction between a first user device belonging to the first user and a second user device belonging to the second user, storing information related to the interaction in a first interaction table associated with the first user device, assigning a relationship identifier to the second user based, at least in part, on the information related to the interaction, and determining whether or not the assigned relationship identifier is correct.
Abstract:
Methods and apparatuses for optimizing performance using data from an Internet of Things (IoT) device with analytics engines. The method receives, from a requesting Internet of Things (IoT) device, a request for trend data of physical resource consumption based at least in part on a portion of received data from at least one of a plurality of IoT devices. The method retrieves, from memory of an analytics engine, at least the portion of the received data. The method calculates, in a calculator of the analytics engine, the trend data based on at least the portion of the received data. The method transmits, to the requesting IoT device, the calculated trend data, wherein the requesting IoT device adjusts parameters in an IoT device using the calculated trend data.
Abstract:
The disclosure relates to collaborative intelligence and decision-making in an Internet of Things (IoT) device group. In particular, various IoT devices in the group may be interdependent, whereby a decision that one IoT device plans may impact other IoT devices in the group. Accordingly, in response to an IoT device planning a certain decision (e.g., to transition state or initiate another action), the IoT devices in the group may collaborate using distributed intelligence prior to taking action on the planned decision. For example, a recommendation request may be sent to other IoT devices in the group, which may then analyze relationships within the group to assess potential impacts associated with the planned decision and respond to approve or disapprove the planned decision. Based on the responses received from the other IoT devices, the IoT device may then determine whether to take action on the planned decision.
Abstract:
The disclosure generally relates to Internet of Things (IoT) device social networking, and in particular to an IoT device publish-subscribe messaging model and automatic IoT device social network expansion. For example, IoT devices from different networks may publish status data that relates to certain topics, wherein the published status updates may be managed in a distributed manner at each IoT network. Furthermore, IoT devices interested in published data can subscribe to data relating to certain topics, which may be used to dynamically adjust actions that the subscribing IoT devices may take. Furthermore, IoT devices can employ common social networking capabilities (e.g., refer, follow, like, publish, subscribe, etc.) to interact with other IoT devices and find relevant information from other IoT devices that can be used to improve performance and effectiveness.