Abstract: A method includes using a memory address map, locating a first portion of an application in a first memory and loading a second portion of the application from a second memory. The method includes executing in place from the first memory the first portion of the application, during a first period, and by completion of the loading of the second portion of the application from the second memory. The method further includes executing the second portion of the application during a second period, wherein the first period precedes the second period.

Abstract: A context-based protection system uses tiered protection structures including master protection units, shared memory protection units, a peripheral protection units to provide security to bus transfer operations between central processing units (CPUs), memory array or portions of arrays, and peripherals.

Abstract: Various aspects of techniques, systems, and use cases include robot safety. A device in a network may include processing circuitry and memory including instructions, which when executed by the processing circuitry, cause the processing circuitry to perform operations. The operations may include collecting telemetry data for a robot, the robot operating according to a path control plan generated using reinforcement learning with a safety factor as a reward function, and detecting that a safety event, involving a robot action, has occurred with the robot and an object. The operations may include simulating a recreation of the safety event to determine whether a simulated action matches the robot action.

Abstract: Various aspects of methods, systems, and use cases include techniques for training or using a model to control a robot. A method may include identifying a set of action primitives applicable to a set of robots, receiving information corresponding to a task (e.g., a collaborative task), and determining at least one action primitive based on the received information. The method may include training a model to control operations of at least one robot of the set of robots using the received information and the at least one action primitive.

Abstract: Technologies for filtering biosignals include one or more biosignal sensors coupled to a user to receive biosignals and a computing device to receive biosignals from the biosignal sensors. The biosignal sensors filter the received biosignals to identify abnormal biosignals using a plurality of domain filters including a time domain filter and a frequency domain filter. The biosignals identified as abnormal by each of the domain filters are transmitted to the computing device, while the remaining biosignals are discarded.

Abstract: A method includes using a memory address map, locating a first portion of an application in a first memory and loading a second portion of the application from a second memory. The method includes executing in place from the first memory the first portion of the application, during a first period, and by completion of the loading of the second portion of the application from the second memory. The method further includes executing the second portion of the application during a second period, wherein the first period precedes the second period.

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: A method includes using a memory address map, locating a first portion of an application in a first memory and loading a second portion of the application from a second memory. The method includes executing in place from the first memory the first portion of the application, during a first period, and by completion of the loading of the second portion of the application from the second memory. The method further includes executing the second portion of the application during a second period, wherein the first period precedes the second period.

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: 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 method includes using a memory address map, locating a first portion of an application in a first memory and loading a second portion of the application from a second memory. The method includes executing in place from the first memory the first portion of the application, during a first period, and by completion of the loading of the second portion of the application from the second memory. The method further includes executing the second portion of the application during a second period, wherein the first period precedes the second period.

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: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments for booting an application from multiple memories. An embodiment operates by executing in place from a first memory a first portion of the application, loading a second portion of the application from a second memory, and executing the second portion of the application.

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: A context-based protection system uses tiered protection structures including master protection units, shared memory protection units, a peripheral protection units to provide security to bus transfer operations between central processing units (CPUs), memory array or portions of arrays, and peripherals.

Abstract: Technologies for filtering biosignals include one or more biosignal sensors coupled to a user to receive biosignals and a computing device to receive biosignals from the biosignal sensors. The biosignal sensors filter the received biosignals to identify abnormal biosignals using a plurality of domain filters including a time domain filter and a frequency domain filter. The biosignals identified as abnormal by each of the domain filters are transmitted to the computing device, while the remaining biosignals are discarded.