Characterizing proximity risks within a radio mesh
AssigneeIntel Corporation
InventorsGlen J. Anderson, Willem M. Beltman, Giuseppe Raffa
Life of this patent
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Abstract
Methods and apparatus relating to characterizing proximity risks within a radio mesh are described. In an embodiment, collection logic receives risk data from one or more source devices and memory stores the risk data. Pattern logic analyzes the stored risk data to determine existence of one or more risks. The risk data includes results of two-way ping signals communicated between the one or more source devices and a target device. Other embodiments are also disclosed and claimed.
Claims25
An apparatus comprising:
- collection logic to receive risk data from one or more source devices;
- and
- memory, coupled to the collection logic, to store the risk data,
- wherein pattern logic is to analyze the stored risk data to determine existence of one or more risks, wherein the risk data includes results of two-way ping signals communicated between the one or more source devices and a target device, wherein the one or more source devices comprise one or more communication devices, wherein the one or more communication devices communicate in accordance with millimeter Wave (mmWave) signals, wherein tracking logic is to track movement of the target device or presence of an obstacle based at least in part on machine learning or deep learning applied to the mmWave signals.
One or more computer-readable medium comprising one or more instructions that when executed on at least one processor configure the at least one processor to perform one or more operations to cause:
- collection logic to receive risk data from one or more source devices;
- and
- memory to store the risk data,
- wherein pattern logic is to analyze the stored risk data to determine existence of one or more risks, wherein the risk data includes results of two-way ping signals communicated between the one or more source devices and a target device, wherein the one or more source devices comprise one or more communication devices, wherein the one or more communication devices communicate in accordance with millimeter Wave (mmWave) signals, wherein tracking logic is to track movement of the target device or presence of an obstacle based at least in part on machine learning or deep learning applied to the mmWave signals.
A computing system comprising:
- a processor having one or more processor cores;
- memory, coupled to the processor, to store one or more bits of data;
- and
- collection logic to receive risk data from one or more source devices;
- wherein the memory is to store the risk data,
- wherein pattern logic is to analyze the stored risk data to determine existence of one or more risks, wherein the risk data includes results of two-way ping signals communicated between the one or more source devices and a target device, wherein the one or more source devices comprise one or more communication devices, wherein the one or more communication devices communicate in accordance with millimeter Wave (mmWave) signals, wherein tracking logic is to track movement of the target device or presence of an obstacle based at least in part on machine learning or deep learning applied to the mmWave signals.
Dependencies are inferred from the claim text.