Abstract: Systems, apparatuses and methods may provide for origination camera technology that generates a cell representation of a local space associated with an origination camera in a multicast domain, predicts that an object in the local space will exit the local space and enter one or more adjacent spaces associated with additional cameras in the multicast domain, and sends the cell representation and a trajectory of the object to the additional cameras before the object exits the local space. Additionally, transition camera technology may generate a leader election message based on a multicasted trajectory of an object and a predicted trajectory of the object, send the leader election message from a transition camera to one or more additional cameras in a multicast domain, and track the object in the local space in response to a leader notification message.

Abstract: Systems, apparatuses and methods may provide for technology that detects an unidentified individual at a first location along a trajectory in a scene based on a video feed of the scene, wherein the video feed is to be associated with a stationary camera, and selects a non-stationary camera from a plurality of non-stationary cameras based on the trajectory and one or more settings of the selected non-stationary camera. The technology may also automatically instruct the selected non-stationary camera to adjust at least one of the one or more settings, capture a face of the individual at a second location along the trajectory, and identify the unidentified individual based on the captured face of the unidentified individual.

Abstract: Systems, apparatuses and methods may provide for technology that identifies a sequence of events associated with a computer architecture, categorizes, with a natural language processing system, the sequence of events into a sequence of words, identifying an anomaly based on the sequence of words and triggering an automatic remediation process in response to an identification of the anomaly.

Abstract: Systems, apparatuses and methods may provide for technology that identifies a sequence of events associated with a computer architecture, categorizes, with a natural language processing system, the sequence of events into a sequence of words, identifying an anomaly based on the sequence of words and triggering an automatic remediation process in response to an identification of the anomaly.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that extracts data from multimodal sensor signals associated with a scene and generates a five-dimensional (5D) representation of the scene, wherein the 5D representation includes a three-dimensional (3D) visual representation, a one-dimensional (1D) temporal representation, and a 1D branch representation. The technology may also store the 5D representation as a set of abstract descriptors.

Abstract: Techniques are disclosed to address issues related to the use of personalized training data to supplement machine learning trained models for Driver Monitoring System (DMS), and the accompanying mechanisms to maintain confidentiality of this personalized training data. The techniques disclosed herein also address issues related to maintaining transparency with respect to collected sensor data used in a DMS. Additionally, the techniques disclosed herein facilitate the generation of a digital representation of a driver for use as supplemental training data for the DMS machine learning trained models, which allow for DMS algorithms to be tailored to individual users.

Abstract: Systems, apparatuses and methods may provide for technology that identifies a sequence of events associated with a computer architecture, categorizes, with a natural language processing system, the sequence of events into a sequence of words, identifying an anomaly based on the sequence of words and triggering an automatic remediation process in response to an identification of the anomaly.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that generates a cell representation of a local space associated with an origination camera in a multicast domain, predicts that an object in the local space will exit the local space and enter one or more adjacent spaces associated with additional cameras in the multicast domain, and sends the cell representation and a trajectory of the object to the additional cameras before the object exits the local space. Additionally, transition camera technology may generate a leader election message based on a multicasted trajectory of an object and a predicted trajectory of the object, send the leader election message from a transition camera to one or more additional cameras in a multicast domain, and track the object in the local space in response to a leader notification message.

Abstract: Systems, apparatuses and methods may provide for origination camera technology that extracts data from multimodal sensor signals associated with a scene and generates a five-dimensional (5D) representation of the scene, wherein the 5D representation includes a three-dimensional (3D) visual representation, a one-dimensional (1D) temporal representation, and a 1D branch representation. The technology may also store the 5D representation as a set of abstract descriptors.

Abstract: Systems, apparatuses and methods may provide for technology that detects an unidentified individual at a first location along a trajectory in a scene based on a video feed of the scene, wherein the video feed is to be associated with a stationary camera, and selects a non-stationary camera from a plurality of non-stationary cameras based on the trajectory and one or more settings of the selected non-stationary camera. The technology may also automatically instruct the selected non-stationary camera to adjust at least one of the one or more settings, capture a face of the individual at a second location along the trajectory, and identify the unidentified individual based on the captured face of the unidentified individual.

Abstract: Apparatus, systems, methods, and articles of manufacture for automated quality assurance and software improvement are disclosed. An example apparatus includes a data processor to process data corresponding to events occurring with respect to a software application in i) a development and/or a testing environment and ii) a production environment. The example apparatus includes a model tool to: generate a first model of expected software usage based on the data corresponding to events occurring in the development and/or the testing environment; and generate a second model of actual software usage based on the data corresponding to events occurring in the production environment. The example apparatus includes a model comparator to compare the first model to the second model. The example apparatus includes a correction generator to generate an actionable recommendation to adjust the development and/or the testing environment to reduce a difference between the first model and the second model.

Abstract: An apparatus includes a feature extractor to extract features from input data, the features including descriptive information corresponding to a function of the input data, an inference generator to classify the features into a group indicative of a semantic property, a programming pattern, or a compliance type of the function of the input data, assign a cluster identifier to the features based on a prediction that the features are classified into the group, and retrieve solutions from a database that correspond to the cluster identifier, and a suggestion determiner to generate a suggestion list by building a pool of suggestions to present to a user.