Abstract: A system may receive hazard data including an indication of one or more events, for example based on one or more of current climate conditions or future climate conditions. The system may receive geographic data. The system may determine, for example based at least in part on the geographic data, a portfolio including a plurality of locations. The system may group each of the one or more events into one or more annual groups. The system may forecast, for example based at least in part on the hazard data and the geographic data, a geographic extent and/or a severity of the one or more events. The system may forecast, for example based at least in part on the hazard data and/or the geographic data, a likelihood that a hazard will occur within a time frame associated with a first annual group of the one or more annual groups.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: Hazard-resultant effects to land and buildings are predicted based on various inputs. Hazards may include any appropriate type of hazard (e.g., flood, wildfire, climate-related hazards, or the like). Inputs may include the likelihood that that a specific type of hazard may occur for various scenarios, terrestrial boundaries, property boundaries, census geographies, or the like. Relationships between the inputs are determined and used to quantify parameters pertaining to a specific type of hazard. For example, the depth of flood water may be predicted for a particular terrestrial boundary, a city or town, or a building, for specific climate scenarios. A risk likelihood of the quantified parameter may be determined for a particular period of time and environment. For example, flooding to a building may be determined, broken down by depth threshold and year of annual risk for specific climate scenarios. Economic loss also may be predicted.

Abstract: A method includes receiving a signal associated with one or more sensors. The method also includes examining one or more parameters of a signal conditioning circuit to determine whether clipping of the signal has occurred. The method further includes, upon a determination that clipping of the signal has occurred, decreasing a gain of the signal conditioning circuit. In addition, the method includes, upon a determination that clipping of the signal has not occurred, determining whether a cut-off frequency of the signal conditioning circuit is within a range of a frequency response of an object measured by the one or more sensors. The method can further include changing the cut-off frequency of the signal conditioning circuit and increasing a resistance or a capacitance of the signal conditioning circuit.

Abstract: A method includes receiving a signal associated with one or more sensors. The method also includes examining one or more parameters of a signal conditioning circuit to determine whether clipping of the signal has occurred. The method further includes, upon a determination that clipping of the signal has occurred, decreasing a gain of the signal conditioning circuit. In addition, the method includes, upon a determination that clipping of the signal has not occurred, determining whether a cut-off frequency of the signal conditioning circuit is within a range of a frequency response of an object measured by the one or more sensors. The method can further include changing the cut-off frequency of the signal conditioning circuit and increasing a resistance or a capacitance of the signal conditioning circuit.

Abstract: A method includes transmitting first wireless signals towards a conveyor belt having multiple layers of material. The first wireless signals penetrate one or more layers in the conveyor belt. The method also includes receiving second wireless signals that have interacted with the conveyor belt. The method further includes identifying a condition of the conveyor belt using the second wireless signals and outputting an indicator identifying the condition of the conveyor belt. Identifying the condition of the conveyor belt could include identifying a thickness of at least one of the layers in the conveyor belt. This could be done by identifying pulses in the second wireless signals and using time of flight calculations.

Abstract: A method includes transmitting first wireless signals towards a conveyor belt having multiple layers of material. The first wireless signals penetrate one or more layers in the conveyor belt. The method also includes receiving second wireless signals that have interacted with the conveyor belt. The method further includes identifying a condition of the conveyor belt using the second wireless signals and outputting an indicator identifying the condition of the conveyor belt. Identifying the condition of the conveyor belt could include identifying a thickness of at least one of the layers in the conveyor belt. This could be done by identifying pulses in the second wireless signals and using time of flight calculations.

Abstract: A method and system are provided for in-belt conveyor idler condition monitoring. A sensor is mechanically coupled to a conveyor belt and senses a characteristic of a support structure associated with the conveyor belt. The sensor wirelessly transmits a corresponding signal to a monitor system. The monitor system determines a condition of the support structure based upon the transmitted signal. The support structure may be one of a plurality of support structures and characteristics of each of the support structures may be sensed, associated with identifiers for the support structures, and transmitted to the monitor system. The support structure may include a plurality of elements and a characteristic of each element may be sensed and transmitted by one of a corresponding plurality of sensors.

Abstract: A method and system are provided for in-belt conveyor idler condition monitoring. A sensor is mechanically coupled to a conveyor belt and senses a characteristic of a support structure associated with the conveyor belt. The sensor wirelessly transmits a corresponding signal to a monitor system. The monitor system determines a condition of the support structure based upon the transmitted signal. The support structure may be one of a plurality of support structures and characteristics of each of the support structures may be sensed, associated with identifiers for the support structures, and transmitted to the monitor system. The support structure may include a plurality of elements and a characteristic of each element may be sensed and transmitted by one of a corresponding plurality of sensors.