Abstract: Generally discussed herein are systems, devices, and methods for data management in a reverse content data network (rCDN). A component of the rCDN may include a memory to hold content received from a first sensor device of a plurality of sensor devices of the rCDN and first attributes that describe properties of the content. The component may include processing circuitry to receive second content from a second sensor device of the plurality of sensor devices, the second content including a plurality of second attributes that describe properties of the second content, and forward, in response to a determination, based on the first and second attributes, that there is insufficient space to store the second content on the memory, the second content to a node of the rCDN that is fewer hops away from a backend cloud than the component.

Abstract: Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

Abstract: A wireless access device is provided that includes at least one processor, an antennae, and a localization engine. The localization engine is executable by the at least one processor to determine a location of the access device, receive a wireless signal from a particular device that includes presence information corresponding to the particular device that lacks self-localization functionality, and determine a location of the particular device based on the location of the access device and the presence information.

Abstract: A system and method for vehicle communication, including a computing device communicatively coupled with a roadside computing device disposed along a road, wherein the computing device is disposed remote from the road. The roadside computing device to communicate with a vehicle computing system of a vehicle on the road.

Abstract: System and techniques for radio link quality prediction are described herein. A mobile device may receive a device registration. Motion data for the mobile device may then be obtained. A predicted path for the mobile device may be derived from the motion data. A set of predicted radio metrics for the mobile device along the predicted path mat be produced via a dynamic coverage map. The set of predicted radio metrics may then be transmitted.

Abstract: System and techniques for network flow-based hardware allocation are described herein. A workload for is obtained for execution. Here, the workload includes a flow that has a processing component and a network component. Then, during execution of the workload, the flow is repeatedly profiled and assigned a network service and a processing service during a next execution based on a network metric and a processing metric obtained from the profiling.

Abstract: System and techniques for enhanced electronic navigation maps for a vehicle are described herein. A set of map tiles may be received at a vehicle component from a remote entity. Sensor derived data that has a locality corresponding to a map tile in the set of map tiles may be obtained. A field-programmable gate array of the vehicle may then be invoked to combine the sensor derived data and the map tile to create a modified map tile. The modified map tile may be communicated to a control system of the vehicle.

Abstract: A robot may include a processor, configured to operate according to a first operational mode or a second operational mode, wherein the first operational mode comprises performing an environmental perception operation using first sensor data, wherein the first sensor data comprise no camera data, and wherein the second operational mode comprises performing the environmental perception operation using second sensor data, wherein the second sensor data comprise camera data; while operating according to the first operational mode, determine a confidence factor representing a confidence of the environmental perception operation; determine whether or not the confidence factor is outside of a range; and if the confidence factor is outside of the range, operate according the second operational mode.

Abstract: Disclosed herein are embodiments of systems and methods for diversified imitation learning for automated machines. In an embodiment, a process-profiling system obtains sensor data captured by a plurality of sensors that are arranged to observe one or more human subjects performing one or more processes to accomplish one or more tasks. The process-profiling system clusters the sensor data based on a set of one or more process-performance criteria. The process-profiling system also performs, based on the clustered sensor data, one or both of generating and updating one or more process profiles in a plurality of process profiles. The process-profiling system selects, for one or more corresponding automated machines, one or more process profiles from among the plurality of process profiles, and the process-profiling system configures the one or more corresponding automated machines to operate according to the selected one or more process profiles.

Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store sensor data captured by one or more sensors associated with a first device. Further, the processor comprises circuitry to: access the sensor data captured by the one or more sensors associated with the first device; determine that an incident occurred within a vicinity of the first device; identify a first collection of sensor data associated with the incident, wherein the first collection of sensor data is identified from the sensor data captured by the one or more sensors; preserve, on the memory, the first collection of sensor data associated with the incident; and notify one or more second devices of the incident, wherein the one or more second devices are located within the vicinity of the first device.

Abstract: This disclosure is directed to a universal interface for sensor devices. Applications executed in a device may interact with sensor devices via a universal interface. For example, the device may act as a gateway allowing Internet of Things (IoT) devices to interact with at least one resource external to the environment in which the IoT devices operate. The device may comprise at least memory circuitry to store at least a virtual file system and at least one application. The virtual file system may provide a programmatic interface through which at least one sensor device may be accessible to the at least one application. Processing circuitry in the device may execute an application from those stored within the memory circuitry. The application, when executed, may cause interconnect circuitry also in the device to at least one of transmit instructions to, or receive data from, a sensor device utilizing the virtual file system.

Abstract: Techniques are provided for optimizing the operations of an ICN, particularly for an ICN with clustered nodes. A cluster head node may function as an orchestrator and a coordinator for efficient caching, routing, and computing and for co-existence of ICN and IP nodes in the network. A content store of an ICN router may include an indication of the time after which data expires and the new data is to be swapped in place of the expired data after that point in time. Digital rights management (DRM) enforcement is provided by managing access to a DRM engine in at least one of the ICN nodes in a cluster. Congestion control is provided by minimizing the number of ICN scoped interest requests and thereby minimizing the potentially high volume of data responses. These techniques optimize interest packet forwarding and processing through collaboration with neighboring ICN nodes.

Abstract: Systems, methods, and computer-readable media are provided for managing mutual and transitive trust relationships between resources, such as Fog/Edge nodes, autonomous devices (e.g., IoT devices), and/or analog/biological resources to provide collaborative, trusted communication over a network for service delivery. Disclosed embodiments include a subject resource configured to assign an observed resource to a trust zone based on situational and contextual information. The situational information may indicate a vector of the observed resource with respect to the subject resource. The contextual information may be based in part on whether a relationship exists between the subject resource and the observed resource. The subject resource is configured to determine a trust level of the observed resource based on the determined trust zone. Other embodiments are disclosed and/or claimed.

Abstract: Automated methods and apparatuses for charging or fueling a vehicle include provision of a plurality of tags and a controller to a vehicle. The plurality of tags are respectively installed at a plurality of positions on a top face of a roof of the vehicle. The controller is configured to cause information about a charging or fueling port of the vehicle to be transmitted to a charging or fueling system of a charging or fueling station. The charging or fueling system, provided with a charging connector or fueling nozzle, and an imaging device, uses at least the information about the charging or fueling port and the plurality of positions of the plurality tags to determine a location of the charging or fueling port of the vehicle, to charge or fuel the vehicle.

Abstract: Various systems and methods for customizing training data for an artificial intelligence (AI) or machine-learning (ML) model are disclosed. A set of data is identified from a plurality of sets of data used to train the AI or ML model. The set of data is identified based on a set of metadata associated with the set of data indicating an association between the set of data and a jurisdiction of a digital services tax (DST). Based on the identifying, the plurality of sets of data is modified by removing or reducing reliance upon the set of data. The AI or ML model is retrained based on the modified plurality of sets of data. The retrained AI or ML model is provided for deployment in an individual autonomous agent.

Abstract: A device for a vehicle may include a first wireline interface configured to receive a first data stream from a first sensor having a first sensor type for perceiving a surrounding of the vehicle, the first data stream including raw sensor data detected by the first sensor; a second wireline interface configured to receive a second data stream from a second sensor having a second sensor type for perceiving the surrounding of the vehicle, the second data stream including raw sensor data detected by the second sensor; one or more processors configured to generate a coded packet including the received first data stream and the received second data stream by employing vector packet coding on the first data stream and the second data stream; and an output wireline interface configured to transmit the generated coded packet to one or more target units of the vehicle.

Abstract: Generally discussed herein are systems, devices, and methods for data management in a reverse content data network (rCDN). A component of the rCDN may include a memory to hold content received from a first sensor device of a plurality of sensor devices of the rCDN and first attributes that describe properties of the content. The component may include processing circuitry to receive second content from a second sensor device of the plurality of sensor devices, the second content including a plurality of second attributes that describe properties of the second content, and forward, in response to a determination, based on the first and second attributes, that there is insufficient space to store the second content on the memory, the second content to a node of the rCDN that is fewer hops away from a backend cloud than the component.

Abstract: Generally discussed herein are systems, devices, and methods for populating a cache in an information-centric network. A device of an ICN can include a content store including published content and attributes of the published content stored thereon, the attributes including at least two of a device from which the content originated attribute, a lineage attribute, and a service level agreement attribute, and content processing circuitry coupled to the content store, the content processing circuitry configured to manage the published content based on the attributes.

Abstract: A vehicle recognition system includes a sound analysis circuit to analyze captured sounds using an audio machine learning technique to identify a sound event. The system includes an image analysis circuit to analyze captured images using an image machine learning technique to identify an image event, and a vehicle identification circuit to identify a type of vehicle based on the image event and the sound event. The vehicle identification circuit may further use V2V or V2I alerts to identify the type of vehicle and communicate a V2X or V2I alert message based on the vehicle type. In some aspects, the type of vehicle is further identified based on a light event associated with light signals detected by the vehicle recognition system.

Abstract: A system and method for vehicle communication, including a computing device communicatively coupled with a roadside computing device disposed along a road, wherein the computing device is disposed remote from the road. The roadside computing device to communicate with a vehicle computing system of a vehicle on the road.