Abstract: Event intensity assessment can include detecting an event description within textual input received via a data communication network. An event-correlated data structure based on the event can be generated, the event-correlated data structure including an event descriptor corresponding to the event. An event sentiment can be determined based on the event descriptor and an event impact based on a quantitative temporal-spatial measure corresponding to the event. An event intensity can be determined based on the event sentiment and event impact. A GUI can be modified in response to the event intensity exceeding a predetermined threshold. The GUI can be modified to indicate the event and the event intensity.

Abstract: The invention relates to pre-conditioning an animal(s) to (the risk of) heat stress. The invention provides a control device for controlling a lighting device to illuminate at least one animal in a space, wherein the control device is configured to: obtain prediction data indicative of a value of an environmental condition in said space during a future time period; determine said value of the environmental condition based on the prediction data; determine a prediction of heat stress of the at least one animal in said space during the future time period if said value of the environmental condition falls within a predefined limit for heat stress; control, upon determining said prediction of heat stress, a lighting device to illuminate the at least one animal in said space with a lighting characteristic at least partly before said future time period.

Abstract: Subject soils are classified using a sensing tool. By profiling each of a number of first locations that have a ground truth classification, using a deployed sensing tool, digital soil properties of new locations without ground truth classifications can be obtained to determine corresponding classifications for the new locations. This allows information related to classifications to be utilized for optimal use of the new locations.

Abstract: Systems and methods for converting live weather data to a weather index for offsetting weather risk. Weather data source systems generate one or more weather data streams that include weather forecast model and observations data. A data distribution system receives a weather index request, identifies at least one instrument and at least one location associated with the request. Weather risk indication data is extracted among the weather data streams associated with the identified location based on predefined parameters associated with the identified instrument. The extracted data is converted into a set of weather index values corresponding to the location, based on a predetermined algorithm associated with the identified instrument. A weather index presentation package is generated that includes the set of weather index values for distribution to at least one user device. The weather index presentation package being distributed is updated concurrent with changes to weather risk indication data.

Abstract: Calculating energy loss during an outage, including: determining that windspeed data indicating device windspeeds measured at an energy generating device are unavailable within a particular time duration; receiving meteorological data associated with a site location of the energy generating device, the meteorological data including meteorological windspeed data collected within the particular time duration; and predicting one or more estimated device windspeeds at the energy generating device during the particular time duration based on the meteorological data using a trained model for the energy generating device, the trained model being trained using a machine learning algorithm that utilizes historical meteorological windspeed data associated with the site location collected during a previous time duration and corresponding historical device windspeed data measured at the energy generating device during the previous time duration.

Abstract: A photovoltaic array fault diagnosis method based on composite information is provided. The method includes: collecting and preprocessing composite information data of photovoltaic array working state, including image data and text data; using the image data of photovoltaic array working state to train a pre-established fault classification model of deep convolutional neural network, to thereby obtain an image fault classification model; using the text data of photovoltaic array working state to train a pre-established fault classification model based on a support vector machine, to thereby obtain a text fault classification model; fusing the image fault classification model and the text fault classification model by logistic regression algorithm to obtain a fusion model, and training the fusion model using the composite information data of photovoltaic array working state to thereby obtain the photovoltaic array fault diagnosis model.

Abstract: One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: A computing system can receive monitoring data from the one or more monitoring services. Based on the monitoring data, the system can predict that an event will occur in a given area and determine a subset of users within the given area. For each respective user of the subset of users, the system generates interactive content for display on a computing device of the respective user, the interactive content providing the respective user with contextual information regarding the predicted event.

Abstract: A spatial auto-correlation clustering method for a remote correlation mode. By taking the degree of remote correlation between each spatial grid cell and an adjacent cell thereof into consideration, and on the basis of the definition of a local Moran index, an original value of a correlation coefficient is used without performing centralization processing, thereby improving a local Moran index calculation formula to obtain a new local indicator of spatial auto-correlation (LISAAC), such that the detection of a significant positive or negative remote correlation aggregation range is realized, and the identification of an abnormal value (that is, a non-significant or negative-value grid appears in a significant positive-value area, and a non-significant or positive-value grid appears in a significant negative-value area) is realized.

Abstract: The present disclosure provides a method and system for hierarchical processing of gas data based on smart gas Internet of Things (IoT). The method is executed via the smart gas IoT. The method includes obtaining gas data sending and receiving information of at least one node in at least one period. The method also includes predicting a gas data communication load of the at least one node in at least one future period based on the gas data sending and receiving information. The method further includes determining a time-sharing processing scheme for the at least one future period based on the gas data communication load of the at least one node in the at least one future period.

Abstract: In accordance with one aspect of the present disclosure, there is provided an apparatus for detecting rain using a wire mesh sensor including: a wire mesh which is configured to include a plurality of transmitters and a plurality of receivers; and a fixing part for fixing the wire mesh; wherein the plurality of transmitters supply electricity to the wire mesh, and wherein, in response to rain being positioned between a specific transmitter among the plurality of transmitters and a specific receiver among the plurality of receivers, the specific receiver is configured to receive the electricity from the specific transmitter and then transmit the electricity to a measuring part, to thereby allow the measuring part to measure conductivity. This hemispherical apparatus can detect rain accurately by making the incident angles of the rain to be vertical regardless of the directions of the rain.

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: A method of controlling an air blowing apparatus includes: determining whether there is precipitation through a rain sensor by a controller; determining whether the air blowing apparatus is in an automatic mode in a precipitation condition by the controller; determining a vehicle speed when the air blowing apparatus is in the automatic mode in the precipitation condition; and setting power and a spray angle of the air blowing apparatus by comparing a rainfall received from the rain sensor to a stored rainfall by the controller. Setting the power and the spray angle of the air blowing apparatus includes compensating the spray angle and a spray amount by measuring a flow speed and a flow angle of rainwater through the rain sensor by the controller.

Abstract: The present disclosure provides systems and methods for flexible renewable energy power generation. The present disclosure also provides systems and methods for firming power generation from multiple renewable energy sources.

Abstract: A system and method provides a route and turn-by-turn directions based on estimates of current and future traffic along the route. A client device may request turn-by-turn directions between an initial and a final location. A server may identify a plurality of routes between the locations. Each route of the plurality of routes may be divided into route segments. For each route segment of a particular route, the server may estimate a travel time. The travel time may be based on estimated vehicle volume data generated from information received from other users vehicle Based on the estimated travel time for each route segment of a particular route, the server may estimate a total travel time for the particular route. The server may repeat this estimate for each of the plurality of routes between the locations and select the route with the lowest estimated travel time. Based on the selected route, the server may generate turn-by-turn directions and transmit the directions to the client device for display.

Abstract: Reduced-size user interfaces for providing weather information are disclosed. At an electronic device with a touch-sensitive display, indications of a location and a temperature at the location may be displayed. In some examples, a user may provide input through a touch on the touch-sensitive display and/or through a rotation of a rotatable input mechanism to display additional weather information, such as weather information for another location, another temperature, another time, and so forth. In some examples, the device may obtain data representing an upcoming activity, determine whether the activity is to begin within a threshold amount of time, and display weather information based on the upcoming activity. In some examples, the device may display an affordance at a position to indicate the time of day for which a weather condition is provided.

Abstract: Systems and methods for machine-learning-based aircraft icing prediction use supervised and unsupervised learning to process real-time environmental data, such as onboard measurements of outside air temperature and dew point, to predict a risk of icing and determine whether to issue an icing risk alert to an onboard crewmember or a remote operator, and/or to recommend an icing avoidance maneuver. The systems and methods can use reinforcement learning to generate a confidence metric in the predicted risk of icing, to determine a time or distance to predicting icing, and/or to not issue an alert or recommend a maneuver in consideration of historical data in a “library of learning” and/or other flight data such as airspeed, altitude, time of year, and weather conditions. The predictive systems and methods are low-cost and low-power, do not require onboard weather radar, and can be effective for use in smaller aircraft that are completely icing-intolerant.

Abstract: Systems and methods for improving the use of precipitation sensors, such as radar and rain gauges, are described herein. In an embodiment, an agricultural intelligence computer system receives one or more digital precipitation records comprising a plurality of digital data values representing precipitation amount at a plurality of locations. The system additionally receives one or more digital forecast records comprising a plurality of digital data values representing precipitation forecasts, each of which comprising predictions of precipitation at a plurality of lead times. The system identifies a plurality of forecast values for a plurality of locations at a particular time, each of the plurality of forecast values corresponding to a different lead time. The system uses the plurality of forecast values to generate a probability of precipitation at each of the plurality of locations.

Abstract: A communications device inputs channel state information to an artificial neural network. The communications device predicts weather conditions with the artificial neural network based on the channel state information. The communications device further adjusts communications based on the predicted weather conditions.

Abstract: Systems and methods for incorporating social content items into a produced video are provided. The system presents a producer interface to a user that allows the user to query for social content items. The user may then select and arrange social content items in an on-air queue. In an on-air mode, the system generates a broadcast-ready on-air format of the social content items and provides a video stream including the broadcast-ready social content items in the on-air queue to a video production system. The broadcast-ready social content items are incorporated into a produced video by the video production system. The user may navigate through the social content items in the on-air queue while on camera as part of the produced video.

Abstract: Train a machine learning model, using an image-based knowledge graph of tropical cyclone data, for implementing a surface field modeling architecture that produces images of at least surface wind fields and surface rainfall fields from images of at least tropical cyclone tracks and pressure intensities. Generate model images of a modeled surface wind field and a modeled surface rainfall field by providing images of at least a user-generated tropical cyclone track and pressure intensity to the trained machine learning model.

Abstract: A method, apparatus, system, and computer program product for visualizing aircraft configurations. A computer system determines a set of weight differences between weights for spatial zones in an aircraft and corresponding spatial zones in a comparison aircraft. The computer system displays a visual representation of the aircraft in a graphical user interface on a display system. The computer system displays the spatial zones in the visual representation of the aircraft in association with a set of graphical indicators identifying the set of weight differences between the spatial zones and the corresponding spatial zones in the graphical user interface on the display system. According to other illustrative embodiments, a computer system and a computer program product for visualizing aircraft configurations are provided.

Abstract: A weather intelligence system retrieves weather forecast data for a number of geographic regions. The weather intelligence system determines, using the weather forecast data for each of the geographic regions, a set of geographic regions predicted to experience a weather anomaly, or unusual weather condition, during a particular time interval. The weather intelligence system determines, through a machine-learning process, whether the weather forecast data indicates conditions that people would generally consider to be unusually hot or cold. The weather intelligence system can then programmatically enable a trigger to transmit a service-related offer associated with the weather anomaly to user devices located within one of the geographic regions where that weather anomaly is determined.

Abstract: Disclosed is a method for processing an irradiation forecast. The method includes: acquiring irradiation forecast data corresponding to a target time period; calling a stacked generalization model including a first-layer generalizer and a second-layer generalizer; determining, using the first-layer generalizer, intermediate forecast data based on the irradiation forecast data corresponding to the target time period; and determining, using the second-layer generalizer, an output forecast value corresponding to the target time period based on the intermediate forecast data. In a technical solution according to an embodiment of the present disclosure, a method for processing an irradiation forecast is achieved.

Abstract: Systems and methods are provided for impervious surface mapping of a target geographic area. The impervious surface mapping utilizes four-band imagery data and light detection and ranging (LIDAR) data collected from the target geographic area. The identified impervious surfaces can be attributed to parcels within the target geographic area for purposes of generating bills for storm water runoff to parcel owners.

Abstract: Methods and systems for generating a multi-model ensemble of global climate simulation data from a plurality of pre-existing global climate simulation model (GCM) datasets, are disclosed. The methods and systems perform steps of computing a GCM dataset validation measure based on at least one sample statistic for at least one climate variable from the pre-existing GCM dataset; selecting a validated subset of the plurality of pre-existing GCM datasets; selecting a subset of GCM datasets; generating one or more candidate ensembles of GCM datasets; computing an ensemble forecast skill score for each candidate ensemble of GCM datasets; generating the multi-model ensemble of GCM datasets by selecting a candidate ensemble of GCM datasets with a best ensemble forecast skill score; and training the NN-based climate forecasting model using the multi-model ensemble of GCM datasets.

Abstract: A terrain referenced navigation system for a vehicle is disclosed and includes an inertial measurement unit and one or more generic terrain sensors configured to collect terrain-dependent data. The terrain referenced navigation system includes one or more processors in electronic communication with the generic terrain sensors and the inertial measurement unit, and a memory coupled to the processors. The memory stores data into one or more databases and program code that, when executed by the processors, causes the terrain referenced navigation system to determine a predicted terrain value based on a terrain value, where the terrain value is retrieved from one or more sensor specific terrain databases. The pre-Kalman filter processing values are sent to a Kalman filter. The Kalman filter determines navigation corrections and sensor corrections based on the pre-Kalman filter processing values.

Abstract: The present invention belongs to the field of nowcasting early-warning technology, and discloses a thunderstorm gale early-warning method, system, equipment and terminal. The thunderstorm gale early-warning method comprises: preprocessing single radar data to identify potential thunderstorm gale areas; and in real-time service, calling the thunderstorm gale parameter model in the potential thunderstorm gale areas identified by single radar every time to perform extrapolation for 1 hour, thereby forming a thunderstorm gale early-warning product within the next hour. The thunderstorm gale early-warning method provided by the present invention makes full use of the identification technology of dual polarization radar to identify the potential of thunderstorm gale, acquires falling areas of potential thunderstorm gale within the next hour by the extrapolation technology, and has better advance and accuracy compared with the existing thunderstorm gale early-warning method.

Abstract: An apparatus, method, and non-transitory medium for betting on weather predictions are disclosed herein. A plurality of longitude and latitude coordinate pairs may be received from a remote device. The display device may render data representing a binary option based on whether a storm will make landfall within the certain radius. A request to purchase the binary option may be received. It may be determined whether the landfall location corresponds to a zip code associated with the given longitude latitude pair in the memory.

Abstract: An evaluation method for evaluating a precipitation-induced landslide disaster loss under climate change is provided. The evaluation method belongs to the technical field of geological disaster prevention and treatment. The evaluation method uses a physical process based model, in considering of spatial heterogeneity of land-surface features of grids in the area, to obtain precipitation thresholds corresponding to the respective grids in the area having the spatial heterogeneity. Historical data and climate model data are taken in combination to select suitable climate models, and the model then is used to simulate landslide prone zones and possible influence zones caused by landslides. An influence zones simulated by the evaluation method can better match disaster loss grid data, which can solve the problem that climate change scenarios and influence of landslide are difficult to be evaluated in landslide disaster evaluation.

Abstract: The present invention discloses an intelligent soft measurement method for wind speed in front of a wind turbine. The method includes: first using laser radar data as a data sample, judging delay orders between input and output by using an AIC or BIC criterion, defining a dynamic difference regression vector according to the delay orders, dividing hyperplanes according to a clustering result by using a machine learning algorithm, and performing dynamic differential input/output nonlinear mapping modeling in a global scope and sub-scopes by using an artificial intelligence dynamic regression algorithm, respectively. Empirical mode decomposition and power spectral density analysis are performed on the wind speed in front of a laser radar measuring machine and the wind speed in front of a soft measurement machine, thereby further verifying the estimation performance of intelligent soft measurement for the wind speed in front of a wind turbine.

Abstract: A method includes generating a time-varying charge/discharge control signal for an electrical storage device, wherein generating the time-varying charge/discharge control signal comprises identifying a prioritization order of a stack of simultaneously operating control modes, the stack of simultaneously operating control modes including a staging mode and at least two additional control modes, each control mode of the stack comprising a plurality of control signal candidate values; identifying an intersection of one or more control signal candidate values from the plurality of control signal candidate values of each control mode of the stack according to the prioritization order; and determining, based on the prioritization order, at least one time-varying charge/discharge control signal for the electrical energy storage device from the intersection of control signal candidate values.

Abstract: A method and system is presented for short to long-term flood forecasting. At the core of the method is a neural network-based flood forecasting model. The method and system performs the steps to implement and use the neural network-based flood forecasting model comprising obtaining historical data from the region, including but not limited to climate and water level data; sampling and structuring the historical data in conjunction with data queried from a GIS (geographic information system) into a dataset; dividing the dataset into pre-processed training and validation partitions; configuring the neural network and training hyperparameters; training the neural network-based flood forecasting model on the pre-processed training partition; performing validation on the neural network-based flood forecasting model with the pre-processed validation partition. Embodiments of the invention are capable of performing flood forecasting over a region in short to long-term time intervals.

Abstract: A system comprises an optical air data system that measures aerosol and molecular scattering of light, and an optical instrument that measures aerosol and/or molecular scattering of light. A processor receives data from the air data system and from the optical instrument. The processor performs one or more signal analysis and data fusion methods comprising: (a) determining aerosol and/or molecular concentration from the received data, modifying a data analysis algorithm to optimize any remaining unknown parameters, and outputting enhanced air data parameters; (b) determining aerosol concentration from the received data, dynamically optimizing hardware settings in the air data system to enhance a signal level and avoid system saturation, and outputting enhanced air data parameters; or (c) determining aerosol and/or molecular concentration from the received data, estimating a confidence level of an air data algorithm, verifying optical health of the air data system, and reporting the optical health to a user.

Abstract: A device, system and method for controlling speed of a vehicle are provided. The device includes a locational information module for determining location information and speed, a storage module for storing at least one geographic map including at least one route, and a speed limit for at least one route. Further, the device includes a processing module configured to receive the location information and retrieve at least one geographic map based on the location information. The processing module is configured to determine a speed limit based on the location information, compare the speed of the device to the determined speed limit, and a display module for alerting a user if the speed of the device exceeds the determined speed limit. The system and method can be for communicating a subject vehicle's speed to a central server and be utilized to analyze traffic congestion patterns or notify selected companies or individuals.

Abstract: A crop yield estimation method based on spatio-temporal deep learning including: obtaining regional historical crop yield data and meteorological data, preprocessing the meteorological data and the yield data to respectively obtain meteorological parameters and a detrended yield as input and output of the crop yield spatio-temporal deep learning model; constructing the spatio-temporal deep learning model for crop yield estimation, and optimizing hyperparameters; and building a training set by taking the meteorological parameters as an input and the detrended yield as output to train the model and obtain parameters of the model; for the crop yield to be estimated, feeding meteorological parameters into the trained model, and obtaining the crop yield estimation result. The model combined temporal and spatial learning to achieve better crop yield estimation accuracy and stability at large spatial scales.

Abstract: A forecast engine is configured to analyze aerial and/or satellite images depicting a geographic area to identify the existence of solar panels within the geographic area at different times. Based on the installation time of each solar panel, the forecast engine estimates the solar power generation capacity of the solar panel. The forecast engine also analyzes meteorological data, including weather forecasts, to estimate a level of insolation at each solar panel within the geographic area across a range of times. The forecast engine can then determine the total amount of solar power generation within the given geographic area at a particular time using the solar power generation capacity of each solar panel and the level of insolation at each solar panel at the particular time.

Abstract: Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

Abstract: A machine learning device includes at least one processor; and at least one memory device configured to store a program, the program executed by the at least one processor to cause the at least one processor to obtain at least one first information from a communication relay device, the first information changing due to communication of the communication relay device; and to correlate the obtained at least first information with at least one characteristic of a replaceable candidate device to perform machine learning.

Abstract: A system that includes a vehicle horn can reduce noise pollution caused by vehicles. The system can include a vehicle horn that has a signal-based mode and a sound-based mode. In the signal-based mode, the vehicle horn can output an electronic signal. In the sound-based mode, the vehicle horn can output an audible signal. The system can select one of the signal-based mode and the sound-based mode for the vehicle horn based on the driving environment data acquired by one or more sensors. Upon receiving a horn command, the system can cause the vehicle horn to output a signal based on the selected mode.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media for generation of autonomous unmanned aerial vehicle flight plans based on triggered sensor information. One of the methods includes accessing information correlated from sensors monitoring features of weather events, and determining an upcoming weather event, the determination comprising one or more areas expected to be affected by the weather event. A likelihood of damage associated with the weather event is determined to be greater than a threshold in the areas. The weather event is monitored while areas in which the likelihood is greater than the threshold are updated accordingly. Subsequent to the weather event, properties to be inspected by unmanned aerial vehicles are determined based on severity information associated with the weather event.

Abstract: A computer processing device for determining whether to allow or deny access to a database associated with the device is provided. The device is configured to determine the origin of data signed with a first key by comparing the key to one or more keys stored in a further database to identify the source of the data; search the database to determine one or more access rules associated with the source of the data, wherein the access rules define whether write access to the database is allowed or denied for the data; and allow or deny write access to the database based on the determined rule or rules.

Abstract: Methods, systems, and devices for identifying the habitual places of a user, the habitual places of a user being the places where the user spends most of his/her time. In some embodiments, historical location information of a user is accessed, and a plurality of visit points are identified based on the historical location information. The plurality of visit points is clustered into a plurality of clusters. Each one of the clusters is then associated with a habitual place of the user. When the server receives, from a client device associated with the user, current location information of the user, the server identifies a current location of the user based on the current location information, and, if the current location of the user is in a neighborhood of one of the clusters, determine that the user is at the habitual place associated with the cluster.

Abstract: An example device is configured to determine, based on a sky image of a portion of sky over a power distribution network and using a convolutional neural network (CNN)-based image regression model, an estimated global horizontal irradiance (GHI) value and manage or control the power distribution network using the estimated GHI value. The device may also be configured to determine, based on GHI values and aggregate load values for at least a portion of the power distribution network, using a Bayesian Structural Time Series model, an estimated photovoltaic power output value for the at least a portion of the power distribution network. The device may manage or control the power distribution network using the estimated photovoltaic power output value.

Abstract: An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.

Abstract: Provided is a wind park, a wind park controller, and a method for controlling a first wind turbine of a plurality of wind turbines of a wind park, wherein a second wind turbine of the plurality of wind turbines can be affected by a wake region caused by the first wind turbine which is positioned upstream of the second wind turbine. A current yaw state is determined and is selected from at least one of: a) an actual rotor yaw misalignment angle of the first wind turbine, wherein the actual rotor yaw misalignment angle is an angle between a rotating axis of a rotor of the first wind turbine and a current wind direction at the rotating axis upstream of the first wind turbine, b) an identifier representing whether the actual rotor yaw misalignment angle is either in a range of positive yaw misalignment angles or of negative yaw misalignment angles.

Abstract: Systems and methods for converting live weather data to a weather index for offsetting weather risk. Weather data source systems generate one or more weather data streams that include weather forecast model and observations data. A data distribution system receives a weather index request, identifies at least one instrument and at least one location associated with the request. Weather risk indication data is extracted among the weather data streams associated with the identified location based on predefined parameters associated with the identified instrument. The extracted data is converted into a set of weather index values corresponding to the location, based on a predetermined algorithm associated with the identified instrument. A weather index presentation package is generated that includes the set of weather index values for distribution to at least one user device. The weather index presentation package being distributed is updated concurrent with changes to weather risk indication data.

Abstract: An adaptive method and device for predicting a weather-related characteristic of a surface of a segment of a road network. The method includes obtaining a location and of measuring a weather-related characteristic of the surface of the roadway of a road segment on which a measuring vehicle is traveling; predicting a weather-related surface characteristic of the road segment using a weather-observation history and a first prediction model associated with the road segment; associating a second prediction model with the road segment when a difference between the measured characteristic and the predicted characteristic is greater than a threshold; and transmitting to a vehicle a prediction made by applying the associated model to the weather-observation history.

Abstract: A computer device, having at least two long-range wireless profiles and coupled with a communication bus of a vehicle, receives a notice that a vehicle-centric download for the computer device, or for a vehicle device coupled to the communication bus, is pending from a remote server. The vehicle computer device determines the size and security requirement associated with the pending download, and a current operational state of the vehicle. If the size or security requirement is low, a consumer-centric profile may be used for the download even if the vehicle is currently being used. If the download file size is large or requires very high security, or if a user is currently using the computer device according to the consumer-centric profile, the computer device may schedule the download to occur after receiving a trigger event occurrence message.

Abstract: A method includes receiving a satellite image of an area and classifying each pixel in the satellite image as representing water, land or unknown using a model. For each of a plurality of possible water levels, a cost associated with the water level is determined, wherein determining the cost associated with a water level includes determining a number of pixels for which the model classification must change to be consistent with the water level and determining a difference between the water level and a water level determined for the area at a previous time point. The lowest cost water level is selected and used to reclassify at least one pixel.