The present application discloses a method for early warning brandish of a transmission wire based on an improved Bayes-Adaboost algorithm, including: forming a classifier by training a historical brandish fault training set, and by using an Adaboost ensemble learning method, and obtaining an early warning result of the brandish of the transmission wire via the classifier according to real-time forecast meteorological information and information of different parameters of the transmission wire. The present invention can realize calculation and processing of forecast information of meteorological characteristic factors of the brandish of the transmission wire, structural parameters of the transmission wire and other related data, and obtain an early warning analysis result of a brandish disaster of the transmission wire in a region.

An information provision device acquires weather information indicating weather of at least one golf course at each of future playing frames included in playing frames of the at least one golf course. The information provision device acquires history information indicating logs of whether any of specific reservation holders canceled a reservation for any of past specific playing frames. Weather at each of the past specific playing frames is predetermined weather that possibly has a negative impact on playing golf. Each of the specific reservation holders has a reservation for one of the future playing frames. The information provision device controls, based on the acquired history information, display priorities of information on specific future playing frames at which weather indicated by the acquired weather information is the predetermined weather, among in the future playing frames.

A method, apparatus and computer program product are provided for controlling a functional road object. For example, at least one processor receives road sign attribute data indicating at least one attribute of a road sign and receives weather forecast data indicating a weather forecast of a location in which the road sign is disposed. The road sign includes at least one machinery for mitigating exposure to one or more weather conditions. The at least one processor identifies a state of visibility for the road sign using the road sign attribute data and the weather forecast data and generates a control signal for controlling the at least one machinery using the state of visibility.

A system for displaying contextually-sensitive braking information on a surface of a vehicle is presented. The system may include a transceiver, one or more memories, an electronic display disposed on the surface, and one or more processors. The one or more processors may be configured to detect a braking event of the vehicle, wherein the braking event has an associated braking force. The one or more processors may compare the braking force to a predetermined threshold braking force to determine whether the braking force exceeds the threshold braking force. The one or more processors may further cause the electronic display to display a braking indication having an intensity that is proportional to the braking force, wherein the braking indication may include a braking rationale corresponding to the braking event in response to determining that the braking force exceeds the threshold braking force.

Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

A system for dynamically adjusting a configuration of an intra-train communication network includes an electronic device and a computer-readable storage medium. The computer-readable storage medium has one or more programming instructions that, when executed, cause the electronic device to receive one or more parameters values associated with a train consist, determine whether a potentially adverse condition that would affect intra-train communication for the train consist is anticipated based on at least a portion of the received parameters, in response to determining that the potentially adverse condition is anticipated, identify one or more updated network parameter settings that will assist in maintaining intra-train communication of the train consist during an occurrence of the potentially adverse condition by executing a machine learning model, and implement the identified one or more updated network parameter settings.

A system (100) for using mobile data to improve weather information is provided. The system (100) includes a weather prediction station (120) configured to receive stationary observation data provided by a plurality of stationary weather stations (110) along with data from a plurality of input weather models (115) and generate unified weather model estimates based on the stationary observation data, the input weather model data, and a processor (130). The processor (130) is configured to aggregate mobile observation data provided by a plurality of non-stationary sensors (140) and use the aggregated mobile observation data to adjust the weather model estimates.

A method of operating an exoskeleton system that includes obtaining at an exoskeleton device, sensor data from one or more sensors; and determining, by the exoskeleton device based at least in part on the sensor data, one or more states, including one or more of: at least one state of the exoskeleton system; at least one state of a user wearing the exoskeleton system; and at least one state of a location where the user and exoskeleton system are located. The method further includes determining, by the exoskeleton device, a response based at least in part on the determined one or more states; and generating the response by the exoskeleton device causing actuation of the exoskeleton system.

The exemplary embodiments disclose a method, a computer program product, and a computer system for determining a personalized weather forecast. The exemplary embodiments may include collecting data of a user and weather conditions of a location, extracting one or more features from the collected data, and determining a personalized weather forecast of the location for the user based on the extracted one or more features and one or more models.