Abstract:
Systems and methods are disclosed for determining a context-dependent virtual distance based on stigmergic interference. The method may include obtaining environmental status information relating to an environment in proximity to a client device, calculating, based on the obtained environmental status information, the context-dependent virtual distance between the client device and a user of the client device, and controlling a user signaling pattern of the client device based on the calculated context-dependent virtual distance.
Abstract:
Systems and methods for generating a grammar describing activities of a user are disclosed. An aspect receives log data for the user, clusters the log data around a plurality of cluster centroids, assigns one or more semantic labels to each of the plurality of cluster centroids based on determining that a threshold number of log data points have been assigned to each of the plurality of cluster centroids, determines a sequence in which the log data points were clustered around the plurality of cluster centroids, generates one or more grammars representing a sequence of possible activities of the user based on the sequence in which the log data points were clustered around the plurality of cluster centroids and the one or more semantic labels of each of the plurality of cluster centroids, and filters the assigned one or more semantic labels for each of the plurality of cluster centroids.
Abstract:
In an embodiment, an apparatus receives report(s) of raw motion data detected in IoT environment, and also receives report(s) indicating user-initiated event(s) detected by a set of IoT devices within the IoT environment. The apparatus scans the raw motion data within a threshold period of time preceding particular detected user-initiated events to identify motion sequence(s) within the IoT environment that occurred during the threshold period of time. Certain motion sequence(s) are correlated with user-initiated event(s) based on a confidence level that the user-initiated event(s) will follow the motion sequence(s). Upon detection of the motion sequence(s) at some later point in time, the correlated event(s) is preemptively triggered without user interaction.
Abstract:
The disclosure is directed to clustering a stream of data points. An aspect receives the stream of data points, determines a plurality of cluster centroids, divides the plurality of cluster centroids among a plurality of threads and/or processors, assigns a portion of the stream of data points to each of the plurality of threads and/or processors, and combines a plurality of clusters generated by the plurality of threads and/or processors to generate a global universe of clusters. An aspect assigns a portion of the stream of data points to each of a plurality of threads and/or processors, wherein each of the plurality of threads and/or processors determines one or more cluster centroids and generates one or more clusters around the one or more cluster centroids, and combines the one or more clusters from each of the plurality of threads and/or processors to generate a global universe of clusters.
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:
The disclosure generally relates to various methods to discover, configure, and leverage relationships in Internet of Things (IoT) networks. More particularly, the methods disclosed herein may support automated processes to create configurable sub-divisions and access controls in an IoT network based on usage associated with objects that are registered in the IoT network and interactions among the registered objects. Furthermore, in one embodiment, relationships between IoT devices that belong to different users may be implicitly discovered and/or ranked based on meetings (e.g., interactions) between the IoT devices, and relationships between the different users may likewise be implicitly discovered and/or ranked. Moreover, locations and interactions associated with IoT devices may be tracked over time to further discover user-specific and potentially asymmetric relationships among the IoT devices and/or the users associated therewith (e.g., where one user considers another user a close friend and the other user considers the first user an acquaintance).
Abstract:
The disclosure generally relates to various methods to discover, configure, and leverage relationships in Internet of Things (IoT) networks. More particularly, the methods disclosed herein may support automated processes to create configurable sub-divisions and access controls in an IoT network based on usage associated with objects that are registered in the IoT network and interactions among the registered objects. Furthermore, in one embodiment, relationships between IoT devices that belong to different users may be implicitly discovered and/or ranked based on meetings (e.g., interactions) between the IoT devices, and relationships between the different users may likewise be implicitly discovered and/or ranked. Moreover, locations and interactions associated with IoT devices may be tracked over time to further discover user-specific and potentially asymmetric relationships among the IoT devices and/or the users associated therewith (e.g., where one user considers another user a close friend and the other user considers the first user an acquaintance).