Abstract: In one example an input/output interface to receive motion tracking data from at least one remote motion sensing device and a controller coupled to the input/output interface and comprising logic, at least partially including hardware logic, to receive the motion tracking data, generate estimated position data using the motion tracking data; and present the estimated position data on a display device coupled to the electronic device. Other examples may be described.

Abstract: Systems and methods may be used to map and collect data from a mesh network at a gateway device connecting a plurality of devices (e.g., edge devices, IoT devices, sensors, or the like) to a network. A method may include determining a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map may define the mesh network for the plurality of devices connected to the gateway. The method may include sampling data throughout the mesh network based on a compressive sensing (CS) sampling schedule. The sampled data may be output, such as to a remote device via the network. The sampled data may be saved at the gateway.

Abstract: Described is an apparatus and method for data compression using compressive sensing in a wearable device. Described is also a machine-readable storage media having instruction stored thereon, that when executed, cause one or more processors to perform an operation comprising: receive an input signal from a sensor; convert the input signal to a digital stream; and symmetrically pad on either ends of the digital stream with a portion of the digital stream to form a padded digital stream.

Abstract: A photoplethysmogram (PPG) measurement includes the use of compressive sensing based on samples generated in accordance with a fixed pattern. A pulse oximeter circuit can drive an LED according to the fixed pattern to create a compressive sensing sample matrix of sparse measurements. The fixed pattern can be a binary progression. The PPG signal reconstruction can include zero padding the sample matrix.

Abstract: Techniques disclosed for accurately predicting the occurrence of anomalous sensor readings within a sensor network and advantageously using these predictions to limit the amount of power used by relay nodes within the sensor network. Some examples analyze spatial and temporal characteristics of anomalous sensor readings to predict future occurrences. In these examples, the relay nodes operate in a reduced power mode for periods of time in which anomalous sensor readings are not predicted to occur. Also, in these examples, only relay nodes in a path between a sensor predicting an anomalous reading and a gateway of the sensor network operate in full power mode. This feature allows other relay nodes to remain in the reduced power mode even when an anomalous sensor reading is predicted elsewhere in the sensor network.

Abstract: Described is an apparatus and method for data compression using compressive sensing in a wearable device. Described is also a machine-readable storage media having instruction stored thereon, that when executed, cause one or more processors to perform an operation comprising: receive an input signal from a sensor; convert the input signal to a digital stream; and symmetrically pad on either ends of the digital stream with a portion of the digital stream to form a padded digital stream.

Abstract: Systems and methods may be used to map and collect data from a mesh network at a gateway device connecting a plurality of devices (e.g., edge devices, IoT devices, sensors, or the like) to a network. A method may include determining a shortest path tree (SPT) map of the plurality of devices, the shortest path tree map may define the mesh network for the plurality of devices connected to the gateway. The method may include sampling data throughout the mesh network based on a compressive sensing (CS) sampling schedule. The sampled data may be output, such as to a remote device via the network. The sampled data may be saved at the gateway.

Abstract: Techniques disclosed for accurately predicting the occurrence of anomalous sensor readings within a sensor network and advantageously using these predictions to limit the amount of power used by relay nodes within the sensor network. Some examples analyze spatial and temporal characteristics of anomalous sensor readings to predict future occurrences. In these examples, the relay nodes operate in a reduced power mode for periods of time in which anomalous sensor readings are not predicted to occur. Also, in these examples, only relay nodes in a path between a sensor predicting an anomalous reading and a gateway of the sensor network operate in full power mode. This feature allows other relay nodes to remain in the reduced power mode even when an anomalous sensor reading is predicted elsewhere in the sensor network.

Abstract: Techniques are provided for compressive sensing (CS) in a sensor network, for improved power efficiency. A methodology implementing the techniques according to an embodiment includes determining a state of a sensor network, based on a calculated statistic of sampled data values generated by one or more sensors in the network, and on anomaly indications generated by the one or more sensors. The method further includes calculating a CS sampling schedule based on the determined state and further based on a sparse signal recovery algorithm. The method further includes broadcasting the CS schedule to the one or more sensors. The CS schedule includes a sensor identification, sampling frequency, and sampling time offset for each sensor to be sampled. The method further includes updating the state of the sensor network and the CS schedule, based on updated data values generated by the one or more sensors in accordance with the sampling schedule.

Abstract: Techniques are provided for compressive sensing (CS) in a sensor network, for improved power efficiency. A methodology implementing the techniques according to an embodiment includes determining a state of a sensor network, based on a calculated statistic of sampled data values generated by one or more sensors in the network, and on anomaly indications generated by the one or more sensors. The method further includes calculating a CS sampling schedule based on the determined state and further based on a sparse signal recovery algorithm. The method further includes broadcasting the CS schedule to the one or more sensors. The CS schedule includes a sensor identification, sampling frequency, and sampling time offset for each sensor to be sampled. The method further includes updating the state of the sensor network and the CS schedule, based on updated data values generated by the one or more sensors in accordance with the sampling schedule.

Abstract: In one example an input/output interface to receive motion tracking data from at least one remote motion sensing device and a controller coupled to the input/output interface and comprising logic, at least partially including hardware logic, to receive the motion tracking data, generate estimated position data using the motion tracking data; and present the estimated position data on a display device coupled to the electronic device. Other examples may be described.

Abstract: Discussed generally herein are methods and devices including or providing a patch system that can help in diagnosing a medical condition and/or provide therapy to a user. A body-area network can include a plurality of communicatively coupled patches that communicate with an intermediate device. The intermediate device can provide data representative of a biological parameter monitored by the patches to proper personnel, such as for diagnosis and/or response.

Abstract: Discussed generally herein are methods and devices including or providing a patch system that can help in diagnosing a medical condition and/or provide therapy to a user. A body-area network can include a plurality of communicatively coupled patches that communicate with an intermediate device. The intermediate device can provide data representative of a biological parameter monitored by the patches to proper personnel, such as for diagnosis and/or response.

Abstract: A photoplethysmogram (PPG) measurement includes the use of compressive sensing based on samples generated in accordance with a fixed pattern. A pulse oximeter circuit can drive an LED according to the fixed pattern to create a compressive sensing sample matrix of sparse measurements. The fixed pattern can be a binary progression. The PPG signal reconstruction can include zero padding the sample matrix.

Abstract: Discussed generally herein are methods and devices including or providing a patch system that can help in diagnosing a medical condition and/or provide therapy to a user. A body-area network can include a plurality of communicatively coupled patches that communicate with an intermediate device. The intermediate device can provide data representative of a biological parameter monitored by the patches to proper personnel, such as for diagnosis and/or response.

Abstract: A cable assembly includes a conductor and a self-cleaning layer that surrounds the conductor and includes one or more of a photocatalyst and an electrocatalyst. Overhead high voltage electricity transmission lines are formed from these cable assemblies. Methods of reducing surface buildup on a cable are also provided.

Abstract: Embodiments of the present disclosure provide techniques and configurations for a wearable sensor apparatus. In one instance, the apparatus may comprise a first flexible substrate, including a first plurality of sensors disposed on a first side of the first flexible substrate to be in direct contact with a user's body, and a first set of conductive connectors disposed on a second side of the first flexible substrate; and a second flexible substrate that includes a second set of conductive connectors disposed on a first side of the second flexible substrate compatibly to the first set of conductive connectors to mechanically and electrically couple the second flexible substrate with the first flexible substrate, and circuitry disposed on a second side of the second flexible substrate to receive and process readings provided by the sensors via the first and second sets of conductive connectors. Other embodiments may be described and/or claimed.

Abstract: In one embodiment a secure controller comprises a memory module, and logic to receive one or more information components pertaining to a transaction initiated by a user on a controller separate from the secure controller, present, on a display device, a Turing test in combination with one or more information components associated with the transaction, receive a user input in response to the Turing test, authenticate the transaction when the user input corresponds to the answer to the Turing test and the personal identifier matches a personal identifier associated with the user. Other embodiments may be described.

Abstract: A method, apparatus, and system are provided for extending a trusted computing base (TCB). According to one embodiment, a first level trusted computing base (TCB) is generated having hardware components including a trusted platform module (TPM), and an extended TCB is formed by adding a second level software-based TCB to the first level TCB, and properties associated with the first level TCB are transferred to the second level TCB.

Abstract: Disclosed is a virtual machine monitor (VMM) that controls access to a page table hierarchy by a guest operating system (OS). For example, the guest operating system may operate as part of a virtual machine. Particularly, the virtual machine monitor obtains control of memory access transactions responsive to the guest operating system attempting to access the page table hierarchy. More particularly, when the guest operating system attempts to access a page table, control of memory access transactions is trapped to the virtual machine monitor.