Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

Abstract: In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images.

Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory stores visual data captured by one or more sensors. The processor detects one or more first objects in the visual data based on a machine learning model and one or more first reference templates. The processor further determines, based on an object ontology, that the visual data is expected to contain a second object, wherein the object ontology indicates that the second object is related to the one or more first objects. The processor further detects the second object in the visual data based on the machine learning model and a second reference template. The processor further determines, based on an inference rule, that the visual data is expected to contain a third object. The processor further detects the third object in the visual data based on the machine learning model and a third reference template.

Abstract: Multiple devices are detected in an environment and a user input is received to define a relationship between two or more devices in the plurality of devices. A system can determine that a first of the two or more devices includes a sensor resource and a second of the two or more devices includes an actuator resource. Data is identified describing outputs of the first device corresponding to the sensor resource and inputs of the second device corresponding to the actuator resource. A model is generated modeling interoperation of the sensor resource and actuator resource based at least in part on the data.

Abstract: A registrar device is delegated enrollment authority for a group by a group authority. The registrar device identifies a particular asset device in association with a reconfiguration of a machine-to-machine (M2M) system that includes the group. The registrar device identifies an enrollment request for enrollment of the particular asset device within the group of devices in association with the reconfiguration of the M2M system and communicates with the particular device to initiate enrollment of the particular device within the group of devices, where enrollment of the particular device includes provisioning the particular device with a group access credential.

Abstract: An embodiment includes at least one computer readable storage medium comprising instructions that when executed enable a system to: receive (a)(i) first radio signal location data for a first object from a radio sensor; and (a)(ii) first visual signal location data for the first object from a camera sensor; perform feature extraction on (b)(i) the first radio signal location data to determine first extracted radio signal features; and (b)(ii) the first visual signal location data to determine first extracted visual signal features; solve a first association problem between the first extracted radio signal features and the first extracted visual signal features to determine first fused location data; and store the first fused location data in the at least one computer readable storage medium. Other embodiments are described herein.

Abstract: A user input including an identification of a set of job abstractions is received, where each job abstraction in the set of job abstractions includes a respective one of a plurality of defined job abstractions and each of the plurality of defined job abstractions are mapped to two or more asset capability abstractions in a plurality of defined asset capability abstractions. The user input is processed to generate program data, based on the set of job abstractions. The resulting program data is executable by a processor device to: identify a set of asset capability abstractions in the plurality of asset capability abstractions corresponding to the set of job abstractions; determine that a set of devices in an environment possess capabilities corresponding to the set of asset capability abstractions; and launch a system including the set of devices to implement jobs corresponding to the set of job abstractions.

Abstract: Availability of computing resources is detected on a particular device in a network and a runtime core is caused to be loaded on the particular device based on the availability. The runtime core is configured to support hot-plugging of code embodying any one of a plurality of job and first code comprising a placeholder job is caused to be run on the runtime core to reserve at least a portion of the computing resources of the particular device. A particular one of the plurality of jobs to be run on the particular device is identified and the first code is replaced with second code corresponding to the particular job to replace the placeholder job on the runtime core.

Abstract: A gateway is provided with configuration management logic to identify a set of configurations corresponding to a deployment of a particular application, and automatically send corresponding configuration data to a set of devices in range of the gateway. Service management logic of the gateway determines that assets on the set of devices correspond to one or more asset abstractions defined for the particular application, where the configuration data is sent to the set of devices based on the assets corresponding to the asset abstractions. Sensor data is received during the deployment as generated by a sensor asset of one of the devices, the sensor data is processed according to service logic of the particular application to generate a result, and actuating data is generated and sent during the deployment to an actuator asset on the set of devices based on the result.

Abstract: In one embodiment, an apparatus comprises a communication interface to communicate over a network, and a processor. The processor is to: receive a workload provisioning request from a user, wherein the workload provisioning request comprises information associated with a workload, a network topology, and a plurality of potential hardware choices for deploying the workload over the network topology; receive hardware performance information for the plurality of potential hardware choices from one or more hardware providers; generate a task dependency graph associated with the workload; generate a device connectivity graph associated with the network topology; select, based on the task dependency graph and the device connectivity graph, one or more hardware choices from the plurality of potential hardware choices; and provision a plurality of resources for deploying the workload over the network topology, wherein the plurality of resources are provisioned based on the one or more hardware choices.

Abstract: A plurality of devices are detected within range of a particular device, and capabilities of each of the plurality of devices are determined, as well as a respective taxonomy to be associated with each device based on the device's capabilities. A set of asset abstractions are identified, referenced by a particular software application configured to manage a particular machine-to-machine network. Each asset abstraction can correspond to a respective one of the set of taxonomies, and the particular machine-to-machine network can be built from an instance of each one of the set of asset abstractions. A subset of the plurality of devices can be selected for deployment in the particular machine-to-machine network based on the associated taxonomies, the subset of devices representing an instance of each one of the set of asset abstractions. The subset of devices are then automatically deployed to implement the instance of the particular machine-to-machine network.

Abstract: A mechanism is described for facilitating portable, reusable, and shareable Internet of Things-based services and resources according to one embodiment. A method of embodiments, as described herein, includes wherein receiving a recipe request for selecting a recipe relating to Internet of Things (IoT) services, where selecting includes at least one of searching the recipe and modifying the recipe. The method may further include selecting the recipe, where the recipe includes a set of resource requirements and business logic. The method may further include modifying the set of resource requirements, where the modified set of resource requirements is associated with the business logic to modify the recipe, and deploying the modified recipe at one or more computing devices, where the modified recipe to facilitate management for one or more IoT devices at one or more locations.

Abstract: A set of samples are returned by radio frequency identifier (RFID) reader corresponding to the readings of signals emitted from a particular RFID tag, each sample including a respective set of features identifying values of the attributes of the signals as detected. At least some of the features are provided as inputs to a random forest of decision trees, each providing a prediction that the particular RFID tag is located in one of a plurality of defined zones in a particular environment. From outputs of the plurality of decision trees based on the set of samples, it can be determined that the particular RFID tag is located in a particular one of the plurality of zones at a first instance in time.

Abstract: Systems, apparatuses and methods may identify a capability abstraction in a request to configure a first Internet of Things (IOT) application in a physical environment including a plurality of IOT devices and select a resource abstraction from a plurality of resource abstractions based on the capability abstraction. The selected resource abstraction may correspond to a first IOT device in the plurality of IOT devices. Additionally, the first IOT application may be bound with the first IOT device. In one example, first data originating from the first IOT device is received, a first runtime abstraction is selected from a plurality of runtime abstractions, wherein the first runtime abstraction corresponds to the first IOT application, and the first data is sent to the first IOT application via the first runtime abstraction.

Abstract: A particular device is provided with a communications module to receive signals of a plurality of devices within range of the particular device and further provisioned with grouping logic. The grouping logic is executable by one or more processors to determine from each of the signals a respective identifier for each of the plurality of devices, determine, based at least in part on the identifiers, that a particular subset of the plurality of devices are also included with the particular device in a particular one of a plurality of defined groups, and converge data received from the particular subset of devices based on the particular group.

Abstract: In one embodiment, an apparatus comprises a processor to: identify a workload comprising a plurality of tasks; generate a workload graph based on the workload, wherein the workload graph comprises information associated with the plurality of tasks; identify a device connectivity graph, wherein the device connectivity graph comprises device connectivity information associated with a plurality of processing devices; identify a privacy policy associated with the workload; identify privacy level information associated with the plurality of processing devices; identify a privacy constraint based on the privacy policy and the privacy level information; and determine a workload schedule, wherein the workload schedule comprises a mapping of the workload onto the plurality of processing devices, and wherein the workload schedule is determined based on the privacy constraint, the workload graph, and the device connectivity graph.

Abstract: Techniques related to applying computer vision to decompressed video are discussed. Such techniques may include generating a region of interest in an individual video frame by translating spatial indicators of a first detected computer vision result from a reference video frame to the individual video frame and applying a greater threshold within the region of interest than outside of the region of interest for computer vision evaluation in the individual frame.

Abstract: Systems and methods for automated generation and presentation of thematic content objects to consumers in a retail environment are provided. A portable device may include a transmitter or transceiver that emits, produces or otherwise transmits a signal that includes information and/or data representative of an identifier that uniquely identifies the portable device. Upon entering an establishment thematic content delivery circuitry detects the presence of the portable device and obtains the identifier included in the signal emitted by the portable device. Using the identifier, the thematic content delivery circuitry determines a theme logically associated with the identifier. The thematic content delivery circuitry generates thematic content output that is logically associated with the theme and communicates the thematic content output to an output device. The thematic content output may include display output, audio output, tactile output, hardcopy output, or combinations thereof.

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: A set of data is identified that includes a plurality of observed values generated by a plurality of sensor devices located in a plurality of different locations. For each of the plurality of observed values, a modality of the value, a spatial location of the value, and a timestamp of the value is determined. Values for one or more missing values in the set of data are determined from the modalities, spatial locations, and timestamps of the plurality of observed values.