Abstract: For example, an apparatus may include a radar, the radar may include a reconfigurable radio configured, based on a plurality of reconfigurable radio parameters, to transmit a plurality of Transmit (Tx) radar signals via a plurality of Tx antennas, to receive via a plurality of Receive (Rx) antennas a plurality of Rx radar signals based on the plurality of Tx radar signals, and to provide digital radar samples based on the Rx radar signals; a radar perception processor configured to generate radar perception data based on the digital radar samples, the radar perception data representing semantic information of an environment of the radar; and a feedback controller to configure the plurality of reconfigurable radio parameters based on the radar perception data, and to feedback the reconfigurable radio parameters to the reconfigurable radio.

Abstract: According to various embodiments, a radar device is described comprising a processor configured to generate a scene comprising an object based on a plurality of receive wireless signals, generate a ground truth object parameter of the object and generate a dataset representative of the scene and a radar detector configured to determine an object parameter of the object using a machine learning algorithm and the dataset, determine an error value of the machine learning algorithm using a cost function, the object parameter, and the ground truth object parameter and adjust the machine learning algorithm values to reduce the error value.

Abstract: Embodiments herein relate to gas identification with a gas identification apparatus having a plurality of metal oxide semiconductor (MOS) sensors. In various embodiments, a gas identification apparatus may include a set of heterogeneous MOS sensors to provide different response patterns for the presence of different gases and an identification engine coupled with the sensors, and having a plurality of regression models and one or more artificial neural networks, to analyze a response pattern to identify presence of a gas, based at least in part on a plurality of property measurements of the MOS sensors when exhibiting the response pattern, and using one or more of the plurality of regression models and the one or more artificial neural networks. Other embodiments may be described and/or claimed.

Abstract: For example, an apparatus may include a radar, the radar may include a reconfigurable radio configured, based on a plurality of reconfigurable radio parameters, to transmit a plurality of Transmit (Tx) radar signals via a plurality of Tx antennas, to receive via a plurality of Receive (Rx) antennas a plurality of Rx radar signals based on the plurality of Tx radar signals, and to provide digital radar samples based on the Rx radar signals; a radar perception processor configured to generate radar perception data based on the digital radar samples, the radar perception data representing semantic information of an environment of the radar; and a feedback controller to configure the plurality of reconfigurable radio parameters based on the radar perception data, and to feedback the reconfigurable radio parameters to the reconfigurable radio.

Abstract: Embodiments herein relate to gas identification with a gas identification apparatus having a plurality of metal oxide semiconductor (MOS) sensors. In various embodiments, a gas identification apparatus may include a set of heterogeneous MOS sensors to provide different response patterns for the presence of different gases and an identification engine coupled with the sensors, and having a plurality of regression models and one or more artificial neural networks, to analyze a response pattern to identify presence of a gas, based at least in part on a plurality of property measurements of the MOS sensors when exhibiting the response pattern, and using one or more of the plurality of regression models and the one or more artificial neural networks. Other embodiments may be described and/or claimed.