Abstract: A chemical sensing system is described. The chemical sensing system can include a plurality of sensors arranged on at least one substrate. The sensors may have differing sensitivities to sense different analytes, and may each be configured to output a signal in response to sensing one or more of the different analytes. The chemical sensing system can further include a computer processor programmed to receive the signals output from the plurality of sensors. The computer processor may be further programmed to determine a concentration of analytes in the sample based, at least in part, on the received signals and a model relating the signals or information derived from the signals to an output representation having bases corresponding to analytes.

Abstract: Described herein is a chemical sensing system that can be deployed in an environment and automatically monitor the environment. The chemical sensing system includes one or more chemical sensing units with sensing elements that sense chemicals in the environment. The chemical sensing system analyzes measured values output by the sensing elements to identify patterns indicative of events. After identifying an event, the chemical sensing system may generate an inference about the environment using measured values output by the sensing elements during the event.

Abstract: Described herein is a chemical sensing system that can be deployed in an environment and automatically monitor the environment. The chemical sensing system includes one or more chemical sensing units with sensing elements that sense chemicals in the environment. The chemical sensing system analyzes measured values output by the sensing elements to identify patterns indicative of events. After identifying an event, the chemical sensing system may generate an inference about the environment using measured values output by the sensing elements during the event.

Abstract: Systems and methods for training models across multiple sensing units in a chemical sensing system are described. The chemical sensing system comprises at least one computer processor and at least one computer readable medium including instructions that, when executed by the at least one computer processor, cause the chemical sensing system to perform a training process. The training process comprises accessing a training dataset including first values representing first signals output from a first chemical sensing unit of multiple chemical sensing units, and second values representing second signals output from a second chemical sensing unit of the multiple chemical sensing units, and training a set of models to relate the first values and the second values to a mutual latent representation using the training dataset.

Abstract: Systems and methods for training models across multiple sensing units in a chemical sensing system are described. The chemical sensing system comprises at least one computer processor and at least one computer readable medium including instructions that, when executed by the at least one computer processor, cause the chemical sensing system to perform a training process. The training process comprises accessing a training dataset including first values representing first signals output from a first chemical sensing unit of multiple chemical sensing units, and second values representing second signals output from a second chemical sensing unit of the multiple chemical sensing units, and training a set of models to relate the first values and the second values to a mutual latent representation using the training dataset.

Abstract: A chemical sensing system is described. The chemical sensing system can include a plurality of sensors arranged on at least one substrate. The sensors may have differing sensitivities to sense different analytes, and may each be configured to output a signal in response to sensing one or more of the different analytes. The chemical sensing system can further include a computer processor programmed to receive the signals output from the plurality of sensors. The computer processor may be further programmed to determine a concentration of analytes in the sample based, at least in part, on the received signals and a model relating the signals or information derived from the signals to an output representation having bases corresponding to analytes.

Abstract: A chemical sensing system is described. The chemical sensing system can include a plurality of sensors arranged on at least one substrate. The sensors may have differing sensitivities to sense different analytes, and may each be configured to output a signal in response to sensing one or more of the different analytes. The chemical sensing system can further include a computer processor programmed to receive the signals output from the plurality of sensors. The computer processor may be further programmed to determine a concentration of analytes in the sample based, at least in part, on the received signals and a model relating the signals or information derived from the signals to an output representation having bases corresponding to analytes.

Abstract: A chemical sensing system is described. The chemical sensing system can include a plurality of sensors arranged on at least one substrate. The sensors may have differing sensitivities to sense different analytes, and may each be configured to output a signal in response to sensing one or more of the different analytes. The chemical sensing system can further include a computer processor programmed to receive the signals output from the plurality of sensors. The computer processor may be further programmed to determine a concentration of analytes in the sample based, at least in part, on the received signals and a model relating the signals or information derived from the signals to an output representation having bases corresponding to analytes.

Abstract: A system and method are provided to control the transmission of data based at least in part on a detected or sensed human state (e.g., emotion) of the user. Personal data of a user may be detected by a sensor of the system. Human state information may be determined based on the personal data. Human state information may be used to control transmission of an intended data transmission of the user. The user may be notified of data transmission control. The system may further user complementary information to determine to control data transmission.

Abstract: An adaptive system and method are provided for modelling the behavioral and non-behavioral state of individual human subjects according to a set of past observations through sensed signals via a multi-modal pattern recognition algorithm. The system may take into consideration both subjective parameters that are learnt from the user over time, and contextual factors that are provided to the system, to achieve the model development.