Abstract: A steering control system for a commercial vehicle having a braking system to brake dissymmetrically wheels. The steering control system, including a sensor unit and a control module, is configured to detect a braking request or deceleration of the vehicle and/or to detect a lateral offset and to generate a brake indication signal and/or steering demand. The control module is configured to receive the brake indication signal and/or steering demand. If the steering demand is below a predetermined threshold value, the control module is configured to generate the steering signal only if the brake indication signal indicates a braking request. If the steering demand exceeds the predetermined threshold value, the control module is configured to generate the steering signal even if the brake indication signal indicates no braking request. The control module provides the steering signal to the braking system to brake the vehicle dissymmetrically to steer the vehicle.

Abstract: A method, computer program product and system to generate higher resolution geospatial images is provided. A processor receives time sequenced spatial data images at a first resolution. A processor determines from the plurality of spatial data images physics laws applicable to the spatial data images. A processor subdivides each of the plurality of spatial data images into a plurality of small spatial region images. A processor solves each of the physics laws in each of the small spatial region images. A processor trains a neural network to apply each of the physics laws to each small spatial region image by applying a regional physics law loss function. A processor determines the most applicable regional physics law based on the difference between the small spatial region image and the image predicted for that region by the physics law. A processor generates a second higher-resolution image than the first resolution.

Abstract: In an approach for estimating emission source location from satellite plume data, a processor creates a dataset of plume concentration data. A processor down samples the dataset to an array at satellite resolution. A processor partitions the array into two separate datasets according to a preset proportion. A processor trains two machine learning models on at least one of the two separate datasets, wherein a first machine learning model of the two machine learning models is for identifying a presence of a plume and a second machine learning model of the two machine learning models is for identifying a source position and magnitude of the plume. A processor applies the two machine learning models to new concentration data.

Abstract: An embodiment includes identifying a tree type of vegetation depicted in an image. The embodiment segments that portion of the image using edge-detection processing resulting in a contour line that defines a tree perimeter. The embodiment detects that the tree is within a buffer distance from a power line. The embodiment determines the tree's species by comparing the contour line to candidate contour lines of different tree species and calculates a diameter of the tree's crown using the contour line. The embodiment estimates the tree's height using the species and the diameter of the crown. The embodiment calculates a risk value for the tree based on a risk of contact between the power line and the tree and issues a work order to maintain the tree to prevent contact with the power line.

Abstract: In some examples, a method of vector-raster data fusion includes receiving vector data for a geographical location, and statistically analyzing the vector data to obtain vector statistics. In some examples the method further includes rasterizing the vector statistics, and storing at least one of the vector data and the rasterized vector statistics together in a key-value store together with previously stored raster data for the geographical location. In some examples, the vector data further includes metadata, and the method further includes storing the metadata in at least one of the key-value store or a separate vector database.

Abstract: Aspects of the invention include includes detecting, using a first machine learning model, a first well pad at a first location based at least in part on a first set of data comprising spectral data describing a gas emission from the first location. Detecting an environmental event within a threshold distance of the well pad. Determining a probability of damage to the first well pad from the environmental event.

Abstract: Aspects of the invention include using a controller to control a transceiver to transmit a sensor query signal to a first sensor at a first location of one or more locations having one or more sensors, wherein the sensor query signal energizes a first power supply for the first sensor, wherein energizing the power supply causes the first sensor to perform a sensor reading at the first location and transmit to the transceiver an encoded response signal representing the sensor reading, and analyzing, using the controller, the encoded response signal to determine the sensor reading at the first location.

Abstract: Methods and systems for managing vegetation include training a machine learning model based on an image of a training data region before a weather event, an image of the training data region after the weather event, and information regarding the weather event. A risk score is generated for a second region using the trained machine learning model based on an image of the second region and predicted weather information for the second region. The risk score is determined to indicate high-risk vegetation in the second region. A corrective action is performed to reduce the risk of vegetation in the second region.

Abstract: A system and method provide remote tracking of progress at construction sites. When possible, the progress can be monitored remotely via satellite imagery. But once satellite imagery cannot determine the progress that needs to be monitored at the construction site, multiple unmanned aerial vehicles (UAVs) that use RF emitters and receivers are deployed to the construction site to determine progress based on RF scans. A number and type of UAVs, along with their respective flight plans, are determined from site specifications and expected progress at the construction site. The UAVs are programmed with their respective flight plans, synchronized, then deployed to inspect the construction site using RF scans. The UAVs execute their respective flight plans, with some emitting RF signals and others receiving those emitted RF signals. The UAV RF data is then analyzed and compared to the site specifications to determine the progress at the construction site.

Abstract: A computer-implemented method executed by one or more satellites for assessing crop development by using synthetic aperture radar (SAR) is presented. The method includes generating SAR images from scanning fields including crops, monitoring grown of the crops within the fields during a predetermined time period, and estimating a height of the crops during the predetermined time period by using interferometric information from one or more of the SAR images and tracking change in height and growth rates. The method further includes differentiating between crops in different fields by monitoring changes in the height of the crops during an entire growing season.

Abstract: A rover includes a base having wheels and a propulsion system coupled to the wheels to propel the rover around a field. A tower is coupled to the base and extends over the base. Sensors are set on the tower and the base and are configured to sense environmental conditions around the rover at different elevations. A computing system includes a processor and memory. The memory is configured to receive measured data from the sensors and determine an amount and manner of water to be dispensed on plant life in the field.

Abstract: A water irrigation system is provided for irrigating a plurality of zones. The water irrigation system includes a set of acoustic pressure modulators for generating a set of modulated acoustic pressure signals that include an actuating pressure signal and a de-actuating pressure signal. The set of acoustic pressure modulators include different subsets. The different subsets control different ones of the plurality of zones by selectively providing the same or different ones of the actuating and de-actuating pressure signals to the different ones of the plurality of zones at any given time. The water irrigation system further includes a set of acoustically-reactive irrigating elements disposed in each of the plurality of zones, each including an acoustically-reactive oscillating disk based water emitter. The acoustically-reactive oscillating disk based water emitter is selectively actuated or de-actuated responsive to the actuating pressure signal and the de-actuating pressure signal, respectively.

Abstract: Aspects of the invention include using a controller to control a transceiver to transmit a sensor query signal to a first sensor at a first location of one or more locations having one or more sensors, wherein the sensor query signal energizes a first power supply for the first sensor, wherein energizing the power supply causes the first sensor to perform a sensor reading at the first location and transmit to the transceiver an encoded response signal representing the sensor reading, and analyzing, using the controller, the encoded response signal to determine the sensor reading at the first location.

Abstract: Aspects of the invention include includes detecting, using a first machine learning model, a first well pad at a first location based at least in part on a first set of data comprising spectral data describing a gas emission from the first location. Detecting an environmental event within a threshold distance of the well pad. Determining a probability of damage to the first well pad from the environmental event.

Abstract: A computer-implemented method is provided for improving farm management by determining farm boundary delineations within a target geographic area based on crop recognition. The method includes evaluating the data using a classification algorithm to generate one or more line segments at an interface separating each pixel in at least one pair of adjacent pixels. It also includes connecting the one or more line segments to an adjacent line segment to form a boundary delineation. The method further includes generating a boundary delineation map including the boundary delineation as well as generating a farm management plan including the boundary delineation map and a recommended crop type. The farm management plan can be generated based on at least a type of vegetation present.

Abstract: Embodiments for controlling precipitation collection vessels to accurately and efficiently collect, measure, and aggregate precipitation accumulation data are disclosed. In one embodiment according to aspects of the present invention, a computer-implemented method includes collecting snow in a plurality of collection vessels by orienting an open end of each of the plurality of collection vessels perpendicularly to a direction of the wind based at least in part on a wind model. The computer-implemented method further includes measuring a snow level of the snow in each of the plurality of collection vessels to generate snow level data for each of the plurality of collection vessels. The computer-implemented method further includes aggregating the snow level data for each of the plurality of snow collection by assembling the snow accumulation data from each of the plurality of collection vessels.

Abstract: A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.

Abstract: Embodiments for controlling precipitation collection vessels to accurately and efficiently collect, measure, and aggregate precipitation accumulation data are disclosed. In one embodiment according to aspects of the present invention, a computer-implemented method includes collecting snow in a plurality of collection vessels by orienting an open end of each of the plurality of collection vessels perpendicularly to a direction of the wind based at least in part on a wind model. The computer-implemented method further includes measuring a snow level of the snow in each of the plurality of collection vessels to generate snow level data for each of the plurality of collection vessels. The computer-implemented method further includes aggregating the snow level data for each of the plurality of snow collection by assembling the snow accumulation data from each of the plurality of collection vessels.

Abstract: Road condition prediction for potentially hazardous road segments is described. For roadways that may contain accumulated frozen precipitation, a road segment for road condition prediction is selected based on weather conditions. Various models including a solar radiation budget model, a permanent structures model, a dynamic structures model, and a road condition model are generated for the selected road segment and account for shading effects on the road segment caused by objects near the road segment. A road condition prediction for hazardous conditions on the road segment is determined based on the road condition model and provided to a driver to alert the driver of any potentially hazardous conditions.

Abstract: Embodiments for controlling precipitation collection vessels to accurately and efficiently collect, measure, and aggregate precipitation accumulation data are disclosed. In one embodiment according to aspects of the present invention, a computer-implemented method includes measuring a frozen precipitation level of the frozen precipitation in a collection vessel. The method further includes heating the collection vessel to convert the frozen precipitation into melted precipitation. The method further includes measuring a melted precipitation level to determine an equivalent water accumulation of the frozen precipitation.