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: Example task assignment methods disclosed herein for video analytics processing in a cloud computing environment include determining a graph, such as a directed acyclic graph, including nodes and edges to represent a plurality of video sources, a cloud computing platform, and a plurality of intermediate network devices in the cloud computing environment. Disclosed example task assignment methods also include specifying task orderings for respective sequences of video analytics processing tasks to be executed in the cloud computing environment on respective video source data generated by respective ones of the video sources.

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: 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 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: Data is received describing a local model of a first device generated by the first device based on sensor readings at the first device and a global model is updated that is hosted remote from the first device based on the local model and modeling devices in a plurality of different asset taxonomies. A particular operating state affecting one or more of a set of devices deployed in particular machine-to-machine network is detected and the particular machine-to-machine network is automatically reconfigured based on the global model.

Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a network interface, a video stream comprising a plurality of video frames; identify a plurality of dependencies among the plurality of video frames; identify, based on the plurality of dependencies, a first subset of video frames to be transmitted using a first transmission method and a second subset of video frames to be transmitted using a second transmission method, wherein the first subset of video frames and the second subset of video frames are identified from the plurality of video frames, and wherein the first transmission method provides a higher quality of service than the second transmission method; transmit, via the network interface, the first subset of video frames to a corresponding destination using the first transmission method; and transmit, via the network interface, the second subset of video frames to the corresponding destination using the second transmission method.

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 processing circuitry to: receive, via a communication interface, a compressed video stream captured by a camera, wherein the compressed video stream comprises: a first compressed frame; and a second compressed frame, wherein the second compressed frame is compressed based at least in part on the first compressed frame, and wherein the second compressed frame comprises a plurality of motion vectors; decompress the first compressed frame into a first decompressed frame; perform pixel-domain object detection to detect an object at a first position in the first decompressed frame; and perform compressed-domain object detection to detect the object at a second position in the second compressed frame, wherein the object is detected at the second position in the second compressed frame based on: the first position of the object in the first decompressed frame; and the plurality of motion vectors from the second compressed frame.

Abstract: Example task assignment methods disclosed herein for video analytics processing in a cloud computing environment include determining a graph, such as a directed acyclic graph, including nodes and edges to represent a plurality of video sources, a cloud computing platform, and a plurality of intermediate network devices in the cloud computing environment. Disclosed example task assignment methods also include specifying task orderings for respective sequences of video analytics processing tasks to be executed in the cloud computing environment on respective video source data generated by respective ones of the video sources.

Abstract: A delivery confirmation of a package at a delivery location may be determined based on a communication protocol between a user device and a package device associated with the package. A user can order an item and anticipate a delivery of the item to a delivery location associated with the user. A delivery device can determine that it has entered a geographic region associated with the delivery location. The delivery device and/or a user device associated with the delivery location can determine, using the communication protocol, that the delivery device is within a range of the user device. Then, the user device can receive a package device identifier associated with the package device, determine that the package device is within the range of the user device, and determine a delivery confirmation of the package.

Abstract: A weighting value is determined for each of a plurality of decision trees in a random forest model hosted on a particular device, where the weighting is based on entropy of the respective decision tree. A new decision tree is received at the particular device and a weighting value is determined for the new decision tree based on entropy of the new decision tree. Based on the determined weighting value, it is determined whether to add the new the decision tree to the random forest model. A classification for data generated at the particular device is predicted using the random forest model.

Abstract: Disclosed are various embodiments for estimating missing wireless attributes of a wireless fingerprint generated for a given location and confirming that the given location is a correct location. A collection of wireless fingerprint samples for the given location can be used to train an attribute prediction model that can estimate missing attributes in wireless fingerprints. For example, a wireless fingerprint may be incomplete as the fingerprint may fail to include attribute data for some AP devices associated with the given location. The attribute prediction model can be used to reconstruct wireless fingerprints to include the missing attributes. The reconstructed wireless fingerprints can then be used to train a location confirmation model which can be used for accurate location confirmation.

Abstract: In one embodiment, an apparatus comprises a display interface to communicate with a display device and a processor. The processor is to: identify a mobile transaction associated with a user, wherein the mobile transaction comprises a potential transaction to be completed using a mobile device of the user; access transaction data associated with the mobile transaction; encrypt the transaction data based on an encryption key associated with the user; generate a visual code associated with the encrypted transaction data, wherein the visual code comprises visually encoded data, and wherein the visual code is generated within a protected execution environment of the processor; establish a protected datapath between the processor and the display device via the display interface; and transmit the visual code to the display device via the protected datapath, wherein the visual code is to be displayed on the display device.

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 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: Data is received describing a local model of a first device generated by the first device based on sensor readings at the first device and a global model is updated that is hosted remote from the first device based on the local model and modeling devices in a plurality of different asset taxonomies. A particular operating state affecting one or more of a set of devices deployed in a particular machine-to-machine network is detected and the particular machine-to-machine network is automatically reconfigured based on the global model.

Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a communication interface, a compressed video stream captured by a camera, wherein the compressed video stream comprises: a first compressed frame; and a second compressed frame, wherein the second compressed frame is compressed based at least in part on the first compressed frame, and wherein the second compressed frame comprises a plurality of motion vectors; decompress the first compressed frame into a first decompressed frame; perform pixel-domain object detection to detect an object at a first position in the first decompressed frame; and perform compressed-domain object detection to detect the object at a second position in the second compressed frame, wherein the object is detected at the second position in the second compressed frame based on: the first position of the object in the first decompressed frame; and the plurality of motion vectors from the second compressed frame.

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: In one embodiment, an apparatus comprises a communication interface and a processor. The communication interface is to communicate with a visual computing device over a network. The processor is to: access visual data captured by a camera; detect a particular feature in the visual data, wherein the particular feature comprises a visual indication of privacy-sensitive information; sanitize the visual data to mask the privacy-sensitive information associated with the particular feature, wherein sanitizing the visual data causes sanitized visual data to be produced; and transmit, via the communication interface, the sanitized visual data to the visual computing device over the network, wherein the visual computing device is to use the sanitized visual data to process a visual query associated with the visual data.