Abstract: A technique for monitoring and collecting environmental data is provided that supports acquisition and analysis of quality measurements of pollutants by sensors based on different technologies in an integrated manner. The system includes a primary substrate having a plurality of sensor modules, each sensor module configured to couple to a sensor, and a manifold having a plurality of flow hoods, each flow hood disposed on a top surface of a sensor and connected to another flow hood or component in the manifold. In some cases, the sensor modules are gas sensor modules, and the sensor is a gas sensor. The manifold thus provides a closed system through which a fluid sample can flow across a series of gas sensors in an actively controlled manner that enables independent flow control over each individual gas sensor while limiting exposure of the fluid sample to potential sources of contamination.

Abstract: A method and system for utilizing environmental data are described. The method includes receiving external environmental data and receiving in-cabin environmental data. A mitigation action for an in-cabin environment of a vehicle is provided. The mitigation action is based on the external environmental data and the in-cabin environmental data.

Abstract: A method for assessing environmental data is described. The method includes receiving sensor data associated with each of a plurality of time intervals from at least one sensor on at least one mobile sensor platform. The sensor data is associated with position data corresponding to each of the plurality of time intervals. The position data corresponds to a plurality of positions having a characteristic distance not exceeding one hundred meters. The sensor data includes a plurality of measurements for each of the plurality of positions. The method includes determining, based on the sensor data and the position data, anomalous data including least one of a geographic anomaly or a temporal anomaly.

Abstract: A method for monitoring air quality is described. The method includes measuring ethane and methane using a mobile sensor platform to provide sensor data. The sensor data includes methane data and ethane data captured at a nonzero mobile sensor platform speed. Methane and ethane peak(s) are identified in the sensor data. Correlation(s) between the methane and ethane peak(s) and/or between the methane peak(s) and at least one amount of 13C are determined. A source for the methane is determined based on the correlation.

Abstract: A method and system for processing signals from a plurality of groups of sensors are described. Each group includes a first sensor and at least one additional sensor. A first sensor identifier and first sensor data are received from the first sensor. At least one additional sensor identifier and additional sensor data are also received from the additional sensor(s). The first sensor and the additional sensor(s) of each group are co-located. The first sensor identifier is associated with the additional sensor identifier(s) for each group. Calibration information for the first sensor is obtained based on the first sensor identifier and the additional sensor identifier(s). The calibration information is specific to the first sensor having the first sensor identifier. Corrected first sensor data for each of the groups is provided based on the first sensor data, the additional sensor data and the calibration information.

Abstract: A method for associating environmental data with map features is described. The method includes receiving sensor data and receiving position data. The sensor data is associated with each of a plurality of time intervals and is from at least one sensor on at least one mobile sensor platform. The position data is associated with the plurality of time intervals and is from the at least one mobile sensor platform. Trajectories and corrected locations of the mobile sensor platform are generated for the plurality of time intervals using the position data. A position of the mobile sensor platform is assigned to a corresponding map feature for each of the plurality of time intervals based on the trajectories and corrected locations. The sensor data is also processed to generate sensor data values for each of the plurality of time intervals. The sensor data values are assigned to the corresponding map feature of the position of the mobile sensor platform for each of the plurality of time intervals.

Abstract: A method for routing, through a geographic region over a time interval, a sensor platform mounted on a vehicle is described. The method includes receiving a precision level for at least one constituent of an environment measured by a sensor of the sensor platform. The precision level corresponds to a mean concentration of the constituent(s) over the time interval. A reference dataset corresponding to the geographic region and the time interval is selected. From the reference dataset and the precision level, at least one minimum number of distinct samples for a plurality of geographic segments of the geographic region is determined. The method also includes determining a number of passes for the geographic region over the time interval using the minimum number of distinct samples for each of the plurality of geographic segments. Each pass of the number of passes is part of a route for the vehicle.

Abstract: A method for monitoring air quality is described. The method includes measuring ethane and methane using a mobile sensor platform to provide sensor data. The sensor data includes methane data and ethane data captured at a nonzero mobile sensor platform speed. Methane and ethane peak(s) are identified in the sensor data. Correlation(s) between the methane and ethane peak(s) and/or between the methane peak(s) and at least one amount of 13C are determined. A source for the methane is determined based on the correlation.

Abstract: A technique for monitoring and collecting environmental data is provided that supports acquisition and analysis of quality measurements of pollutants by sensors based on different technologies in an integrated manner. The system includes a primary substrate having a plurality of sensor modules, each sensor module configured to couple to a sensor, and a manifold having a plurality of flow hoods, each flow hood disposed on a top surface of a sensor and connected to another flow hood or component in the manifold. In some cases, the sensor modules are gas sensor modules, and the sensor is a gas sensor. The manifold thus provides a closed system through which a fluid sample can flow across a series of gas sensors in an actively controlled manner that enables independent flow control over each individual gas sensor while limiting exposure of the fluid sample to potential sources of contamination.

Abstract: A method and system for processing signals from a plurality of groups of sensors are described. Each group includes a first sensor and at least one additional sensor. A first sensor identifier and first sensor data are received from the first sensor. At least one additional sensor identifier and additional sensor data are also received from the additional sensor(s). The first sensor and the additional sensor(s) of each group are co-located. The first sensor identifier is associated with the additional sensor identifier(s) for each group. Calibration information for the first sensor is obtained based on the first sensor identifier and the additional sensor identifier(s). The calibration information is specific to the first sensor having the first sensor identifier. Corrected first sensor data for each of the groups is provided based on the first sensor data, the additional sensor data and the calibration information.

Abstract: A method for processing sensor data in a distributed sensor system includes generating aggregated sensor data values associated with a first sensor and belonging to one or more aggregation time intervals, tagging each aggregated sensor data value with an aggregation indicator. The aggregation indicator has a first value indicating partial aggregation and has a second value indicating complete aggregation. In some embodiments, the method combines the partially aggregated sensor data belonging to the same time interval into a complete aggregated sensor data.

Abstract: Methods, systems, and devices are described for calibrating a sensor of a distributed sensor system. More specifically, the described features generally relate to calibrating one sensor of such a system using information from one or more other sensors of the system. A calibration model may be determined based at least in part on a difference in geospatial location of the sensors. Further, in the case of one or both sensors being mobile, the difference in geospatial location of the sensors may vary over time such that different calibration models may apply to different portions of the sensed data. Also, the relative quality of the data sensed by the sensors may be taken into account for calibration (e.g., directionality of the calibration).

Abstract: A method for processing sensor data in a distributed sensor system includes generating aggregated sensor data values associated with a first sensor and belonging to one or more aggregation time intervals, tagging each aggregated sensor data value with an aggregation indicator. The aggregation indicator has a first value indicating partial aggregation and has a second value indicating complete aggregation. In some embodiments, the method combines the partially aggregated sensor data belonging to the same time interval into a complete aggregated sensor data.

Abstract: A distributed sensor system includes a set of spatially distributed base units and a central server both in communication with a data network. Each base unit includes a controller and one or more sensor modules where each sensor module includes a sensor configured to measure an air quality parameter. Each base unit transmits raw sensor data associated with each of the sensor modules over the data network and the central server receives the raw sensor data from the base units and stores the raw sensor data in a database.

Abstract: A distributed sensor system includes a set of spatially distributed base units and a central server both in communication with a data network. Each base unit includes a controller and one or more sensor modules where each sensor module includes a sensor configured to measure an air quality parameter. Each base unit transmits raw sensor data associated with each of the sensor modules over the data network and the central server receives the raw sensor data from the base units and stores the raw sensor data in a database.

Abstract: Methods of calibrating sensors in a distributed sensor system including a set of spatially distributed base units in communication with a central server over a data network include using a reference sensor, using a reference base unit, using crowd-sourced calibration, using sensor data collected in the same base unit, using sensor cross-sensitivity, or using sensor data from known environmental conditions.