Abstract: Apparatus and methods for thermal management of electronic user devices are disclosed herein. An example apparatus includes at least one of a user presence detection analyzer to identify a presence of a user relative to an electronic device based on first sensor data generated by a first sensor or at least one of an image data analyzer or a motion data analyzer to determine a gesture of the user relative to the device based on second sensor data generated by a second sensor; a thermal constraint selector to select a thermal constraint for a temperature of an exterior surface of the electronic device based on one or more of the presence of the user or the gesture; and a power source manager to adjust a power level for a processor of the electronic device based on the thermal constraint.

Abstract: Apparatus and methods for thermal management of electronic user devices are disclosed herein. An example apparatus includes at least one of a user presence detection analyzer to identify a presence of a user relative to an electronic device based on first sensor data generated by a first sensor or at least one of an image data analyzer or a motion data analyzer to determine a gesture of the user relative to the device based on second sensor data generated by a second sensor; a thermal constraint selector to select a thermal constraint for a temperature of an exterior surface of the electronic device based on one or more of the presence of the user or the gesture; and a power source manager to adjust a power level for a processor of the electronic device based on the thermal constraint.

Abstract: Apparatus and methods for thermal management of electronic user devices are disclosed herein. An example electronic device disclosed herein includes a housing, a fan, a first sensor, a second sensor, and a processor to at least one of analyze first sensor data generated by the first sensor to detect a presence of a subject proximate to the electronic device or analyze second sensor data generated by the second sensor to detect a gesture of the subject, and adjust one or more of an acoustic noise level generated the fan or a temperature of an exterior surface of the housing based on one or more of the presence of the subject or the gesture.

Abstract: Apparatus and methods for thermal management of electronic user devices are disclosed herein. An example electronic device disclosed herein includes a housing, a fan, a first sensor, a second sensor, and a processor to at least one of analyze first sensor data generated by the first sensor to detect a presence of a subject proximate to the electronic device or analyze second sensor data generated by the second sensor to detect a gesture of the subject, and adjust one or more of an acoustic noise level generated the fan or a temperature of an exterior surface of the housing based on one or more of the presence of the subject or the gesture.

Abstract: Various systems and methods for implementing automatic thermal policy tuning are described herein. A system for thermal policy tuning on an electronic device, comprising: a memory device configured to store instructions; and a processor subsystem, which when configured by the instructions, is operable to perform the operations comprising: accessing a thermal policy configuration comprising a plurality of parameters to control a thermal policy of the electronic device; using the thermal policy configuration as input to a machine-learning algorithm, the machine-learning algorithm using an objective function to determine a revised thermal policy configuration; and implementing the revised thermal policy configuration on the electronic device.

Abstract: Thermal management of a computing device is achieved using reward-based updating of synaptic weights of a spiking neural network. The thermal management is achieved using machine readable mediums having instructions that cause a processor to, during a first time window, generate weights to be applied to input trains of spikes from input neurons of a spiking neural network. The instructions further cause the processor to, based on a number of spikes included in an output train of spikes output by an output neuron of the spiking neural network during the first time window, adjust the workload of the processor, and, based on whether a surface temperature of an enclosure housing the processor meets a first threshold or a workload of the processor meets a second threshold, generate a penalty. The instructions also cause the processor to train the spiking neural network by updating the weights.