Abstract: Devices, systems and processes for the detection of unsafe cabin conditions that provides a safer passenger experience in autonomous vehicles are described. One example method for enhancing passenger safety includes capturing at least a set of images of one or more passengers in the vehicle, determining, based on the set of images, the occurrence of an unsafe activity in an interior of the vehicle, performing, using a neural network, a classification of the unsafe activity, and performing, based on the classification, one or more responsive actions.

Abstract: Method and devices for testing a headphone with increased sensation are provided. The headphone can filter and amplify low frequency audio signals, which are then sent to a haptic device in the headphone. The haptic device can cause bass sensations at the top of the skull and at both ear cups. The testing system can evaluate the haptic and acoustic sensations produced by the headphone to evaluate if they have been properly assembled and calibrate the headphones if necessary.

Abstract: Devices, systems and processes for an integrated internal and external camera system that enhances the passenger experience in vehicles are described. One example method for enhancing a passenger experiences includes capturing a first set of images of an area around the vehicle using an external camera system, capturing a second set of images of one or more passengers inside the vehicle using an internal camera system, recognizing at least one gesture made by the one or more passengers based on the second set of images, identifying an object or a location external to the vehicle based on the first set of images and the at least one gesture, and displaying information related to the object or the location to the one or more passengers.

Abstract: Disclosed herein are systems, devices, and processes for gesture detection. A method includes capturing a series of images. The method includes generating motion isolation information based on the series of images. The method includes generating a composite image based on the motion isolation information. The method includes determining a gesture based on the composite image. The processes described herein may include the use of convolutional neural networks on a series of time-related images to perform gesture detection on embedded systems or devices.

Abstract: Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.

Abstract: Disclosed herein are systems, devices, and processes that use millimeter wave radar or other remote sensing to enhance mobility applications. Obstacles may be detected using remote sensing. Acceleration of a mobility apparatus may be controlled based on detection of the obstacle. The controlling may be performed based on characteristics of the obstacle, including location, type of obstacle, and/or trajectory of the obstacle.

Abstract: Method and devices for processing audio signals based on sound profiles are provided. A sound profile can include data related to haptic movement of the audio data which is specific to a left ear or a right ear, demographic information, ethnicity information, age information, location information, social media information, intensity score of the audio data, previous usage information, or device information. A sound profile can be customized for individual user to include the inaudible frequency range at high frequency end and low frequency end. Audio data within the inaudible frequency range can be compensated by haptic movement corresponding to the inaudible frequency range. A sound profile can further include an audio frequency range and its lowest audible volume for a user. A sound profile can be provided to a user without any action from the user's part.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.

Abstract: Devices, systems and processes for the detection of unsafe cabin conditions that provides a safer passenger experience in autonomous vehicles are described. One example method for enhancing passenger safety includes capturing at least a set of images of one or more passengers in the vehicle, determining, based on the set of images, the occurrence of an unsafe activity in an interior of the vehicle, performing, using a neural network, a classification of the unsafe activity, and performing, based on the classification, one or more responsive actions.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device.

Abstract: Method and devices for testing a headphone with increased sensation are provided. The headphone can filter and amplify low frequency audio signals, which are then sent to a haptic device in the headphone. The haptic device can cause bass sensations at the top of the skull and at both ear cups. The testing system can evaluate the haptic and acoustic sensations produced by the headphone to evaluate if they have been properly assembled and calibrate the headphones if necessary.

Abstract: Disclosed herein are systems, devices, and processes for gesture detection. A method includes capturing a series of images. The method includes generating motion isolation information based on the series of images. The method includes generating a composite image based on the motion isolation information. The method includes determining a gesture based on the composite image. The processes described herein may include the use of convolutional neural networks on a series of time-related images to perform gesture detection on embedded systems or devices.

Abstract: Method and devices for processing audio signals based on sound profiles are provided. A sound profile can include data related to haptic movement of the audio data which is specific to a left ear or a right ear, demographic information, ethnicity information, age information, location information, social media information, intensity score of the audio data, previous usage information, or device information. A sound profile can be customized for individual user to include the inaudible frequency range at high frequency end and low frequency end. Audio data within the inaudible frequency range can be compensated by haptic movement corresponding to the inaudible frequency range. A sound profile can further include an audio frequency range and its lowest audible volume for a user. A sound profile can be provided to a user without any action from the user's part.

Abstract: Devices, systems and processes for a dynamic microphone system that enhances the passenger experience in autonomous vehicles are described. One example method for enhancing a passenger experiences includes generating, using an artificial intelligence algorithm, a plurality of filters based on a plurality of stored waveforms previously recorded by each of one or more passengers and a plurality of recordings of one or more noise sources, capturing voice commands from at least one of the one or more passengers inside the autonomous vehicle, generating voice commands with reduced distortion based on processing the voice commands using the plurality of filters, and instructing, based on the voice commands with reduced distortion, the autonomous vehicle to perform one or more actions.

Abstract: Devices, systems and processes for the detection of unsafe cabin conditions that provides a safer passenger experience in autonomous vehicles are described. One example method for enhancing passenger safety includes capturing at least a set of images of one or more passengers in the vehicle, determining, based on the set of images, the occurrence of an unsafe activity in an interior of the vehicle, performing, using a neural network, a classification of the unsafe activity, and performing, based on the classification, one or more responsive actions.

Abstract: Disclosed herein are systems, devices, and processes that use millimeter wave radar or other remote sensing to enhance mobility applications. Obstacles may be detected using remote sensing. Acceleration of a mobility apparatus may be controlled based on detection of the obstacle. The controlling may be performed based on characteristics of the obstacle, including location, type of obstacle, and/or trajectory of the obstacle.

Abstract: Method and devices for testing a headphone with increased sensation are provided. The headphone can filter and amplify low frequency audio signals, which are then sent to a haptic device in the headphone. The haptic device can cause bass sensations at the top of the skull and at both ear cups. The testing system can evaluate the haptic and acoustic sensations produced by the headphone to evaluate if they have been properly assembled and calibrate the headphones if necessary.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate first sensor data and second sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the first sensor data. The system may also include a second computing device configured to determine a state of the resource-constrained environment based on input of the second sensor data to the neural network structure. The system may also include a controller located in the resource-constrained environment configured to control a device in the resource-constrained environment based on the state of the resource-constrained environment determined by the second computing device.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.

Abstract: Systems and methods are disclosed for applying neural networks in resource-constrained environments. A system may include a sensor located in a resource-constrained environment configured to generate sensor data of the resource-constrained environment. The system may also include a first computing device not located in the resource-constrained environment configured to produce a neural network structure based on the sensor data. The system may further include a second computing device located in the resource-constrained environment configured to provide the sensor data as input to the neural network structure. The second computing device may be further configured to determine a state of the resource-constrained environment based on the input of the sensor data to the neural network structure.