A method and system for determining cloud seeding potential comprises receiving a temperature and a liquid water content (LWC). A seeding index is calculated based on the temperature T, a temperature membership function (T), the LWC, and a liquid water content membership function (LWC) at the plurality of grid points to create a seeding index set. A target region potential flag is set based on the seeding index set.

A method and system for determining cloud seeding potential comprises receiving a temperature and a liquid water content (LWC). A seeding index is calculated based on the temperature T, a temperature membership function (T), the LWC, and a liquid water content membership function (LWC) at the plurality of grid points to create a seeding index set. A target region potential flag is set based on the seeding index set.

A real-time metocean sensor array system may include a one or more floating instruments each including geolocation capabilities and connected to a satellite communication network. In some examples, the floating instruments may further include an omnidirectional hydrophone. Motion and acoustical data gathered by the instruments may be converted by onboard processing logic into wave, current, and/or wind-related observations that may be communicated in real time and analyzed via a cloud-based system.

A real-time metocean sensor array system may include a one or more floating instruments each including geolocation capabilities and connected to a satellite communication network. In some examples, the floating instruments may further include an omnidirectional hydrophone. Motion and acoustical data gathered by the instruments may be converted by onboard processing logic into wave, current, and/or wind-related observations that may be communicated in real time and analyzed via a cloud-based system.

An information processing system is equipped with at least one vehicle and a server that can communicate with the at least one vehicle. The vehicle acquires an image obtained by imaging a landscape outside the vehicle, a humidity outside the vehicle, and an imaging position of the image. The vehicle or the server generates floating substance information on an atmospheric floating substance around the vehicle, based on the image and the humidity. The server stores at least one pair of the floating substance information and the imaging position corresponding thereto, and provides information to a client through the use of the at least one pair of the stored floating substance information and the stored imaging position corresponding thereto.

An information processing system is equipped with at least one vehicle and a server that can communicate with the at least one vehicle. The vehicle acquires an image obtained by imaging a landscape outside the vehicle, a humidity outside the vehicle, and an imaging position of the image. The vehicle or the server generates floating substance information on an atmospheric floating substance around the vehicle, based on the image and the humidity. The server stores at least one pair of the floating substance information and the imaging position corresponding thereto, and provides information to a client through the use of the at least one pair of the stored floating substance information and the stored imaging position corresponding thereto.

A method for prediction of a state of an asset comprises receiving sensor data from one or more sensors measuring a state of the asset over time; generating a comparison measurement of the sensor data over time; identifying when the comparison indicates a state of the asset has changed; creating an output when the state is indicated as having changed, as a prediction of a particular state of the asset.

A method for prediction of a state of an asset comprises receiving sensor data from one or more sensors measuring a state of the asset over time; generating a comparison measurement of the sensor data over time; identifying when the comparison indicates a state of the asset has changed; creating an output when the state is indicated as having changed, as a prediction of a particular state of the asset.

Disclosed in present invention are a method for supporting aviation safety and a server for same, the method comprising the steps of: (a) the server for supporting aviation safety obtaining observation data measured from each of a plurality of weather observation apparatuses located in a specific zone; and (b) the server for supporting aviation safety predicting the weather state in the specific zone at a certain time after the current time by analyzing a generated map by referencing a machine learning database.

A display control system includes a display, a detector, and a controller. The display is configured to display an image. The detector is configured to detect wind. The controller is configured to, in response to the detector detecting wind, control the image based on strength of the detected wind.