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 mechanisms that may be used to route notifications in an Internet of Things (IoT) environment according to user activity and/or proximity detection. More particularly, in various embodiments, an entity that manages the IoT environment may receive one or more messages, actions, or responses that indicate detected activity or detected proximity associated with one or more users from one or more IoT devices in the IoT environment. The management entity may then establish an activity and proximity trail from the one or more messages, actions, or responses that indicate the detected activity or the detected proximity, whereby in response to an IoT device reporting one or more notifications, an IoT device in proximity to at least one of the one or more users may be identified and the one or more notifications may be routed to the identified IoT device.
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:
Systems, methods, apparatuses, and non-transitory computer-readable media for micro and macro activity detection and monitoring are disclosed. One example method includes receiving a profile from a health care provider, the profile comprising a physiological threshold; iteratively during a first time interval: receiving first sensor signals from a first sensor, the first sensor disposed within a first device worn by an individual, receiving second sensor signals from a second sensor, the second sensor disposed within a second device, and determining, using a trained machine learning technique for the individual, and accumulating a macro activity and a micro activity based on the first and second sensor signals, using the accumulated macro and micro activities, determining an aggregate macro activity and an aggregate micro activity for the first time interval; and responsive to determining, using the aggregate macro activity and the aggregate micro activity, that the physiological threshold has been reached, outputting a notification indicating the physiological threshold.
Abstract:
Methods and apparatuses for implementing an emergency instruction based on an emergency message from a trusted authority source. The method includes receiving, at an Internet of Things (IoT) device, an emergency secret key from a trusted authority source The method receives, at an IoT device, an emergency message from the trusted authority source; decoding, at an IoT device, the emergency message from the trusted authority source using the emergency secret key to determine a value within the emergency message. The method calculates, at an IoT device, a result based on the determined value. The method implements, at an IoT device, an emergency instruction if the result is above a predetermined threshold.
Abstract:
The disclosure is related to determining an association among Internet of Things (IoT) devices. A first IoT device receives an identifier of a second IoT device, obtains a schema of the second IoT device based on the identifier of the second IoT device, and determines whether or not there is an association between the first IoT device and the second IoT device based on a schema of the first IoT device and the schema of the second IoT device, where the schema of the first IoT device comprises schema elements and corresponding values of the first IoT device and the schema of the second IoT device comprises schema elements and corresponding values of the second IoT device.
Abstract:
Methods, systems, computer-readable media, and apparatuses for remote patient monitoring and event detection are presented. For example, one method includes receiving, by a computing device via wireless communication, one or more sensor signals from a sensor associated with a patient; obtaining a patient condition based on the one or more sensor signals using a trained machine-learning (“ML”) model; and responsive to detecting an emergency condition based on the patient condition, providing an indication of the emergency condition.
Abstract:
The disclosure relates to adaptive advertisements that embedded devices may discover and use to connect to host devices. In particular, host devices may generally transmit multiple advertisements to signal a willingness to host one or more embedded devices, which may selectively process the advertisements to adaptively attach to a particular host device according to properties associated with the host device and/or requirements associated with the embedded devices. Furthermore, the host devices may have overload thresholds that control whether the host devices should be “discoverable” such that the advertisements may be dynamically adjusted (or suspended) according to current load status and connected embedded devices may be redirected to another target host device to shed load when the current load status exceeds the overload threshold.
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:
Example systems, methods, computer-readable media, and apparatuses for dynamic provisioning of wireless devices with health gateways are disclosed. One example method includes detecting, by a wireless device, a signal from a health gateway, the signal including connection information and service information; determining whether the health gateway is a suitable based on the connection information and the service information; and in response to determining that the health gateway is suitable, establishing a communications connection with the health gateway.