Patent classifications
G08B31/00
Systems and methods for forecasting and assessing hazard-resultant effects
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.
Building risk analysis system with natural language processing for threat ingestion
A building management system includes one or more computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to receive threat events from one or more data sources, each threat event including a description and for each threat event determine whether the description for the threat event corresponds to one of a multiple predefined threat categories, generate a standardized threat object for the threat event using the corresponding predefined threat category, and in response to determining the description does not correspond to one of the predefined threat categories, process the description using a natural language processing engine to identify one of the predefined threat categories to be assigned to the threat event and generate a standardized threat object for the threat event using the predefined threat category identified by the natural language processing engine.
Building risk analysis system with natural language processing for threat ingestion
A building management system includes one or more computer-readable storage media having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to receive threat events from one or more data sources, each threat event including a description and for each threat event determine whether the description for the threat event corresponds to one of a multiple predefined threat categories, generate a standardized threat object for the threat event using the corresponding predefined threat category, and in response to determining the description does not correspond to one of the predefined threat categories, process the description using a natural language processing engine to identify one of the predefined threat categories to be assigned to the threat event and generate a standardized threat object for the threat event using the predefined threat category identified by the natural language processing engine.
DYNAMIC GAUGES FOR DISPLAYING PRESENT AND PREDICTED MACHINE STATUS
A facility creates a dynamic gauge for indicating the status of equipment. The facility causes a gauge to be displayed with an initial satisfactory range and an initial unsatisfactory range. The facility accesses historical data describing the status of a sensor attached to equipment. The facility determines a new satisfactory range and a new unsatisfactory range, and alters the gauge to visually indicate the new satisfactory range and the new unsatisfactory range.
DYNAMIC GAUGES FOR DISPLAYING PRESENT AND PREDICTED MACHINE STATUS
A facility creates a dynamic gauge for indicating the status of equipment. The facility causes a gauge to be displayed with an initial satisfactory range and an initial unsatisfactory range. The facility accesses historical data describing the status of a sensor attached to equipment. The facility determines a new satisfactory range and a new unsatisfactory range, and alters the gauge to visually indicate the new satisfactory range and the new unsatisfactory range.
IoT based fire prediction
In an approach to fire prediction, a layout and model of an electrical system is created. Data from one or more sensors in the electrical system is received. One or more peak temperatures and one or more steady-state temperatures for the electrical system are calculated based on data from the sensors. Whether at least one of the peak temperatures or steady-state temperatures exceeds a threshold is determined. Responsive to determining that at least one of the peak temperatures or steady-state temperatures exceeds a threshold, an alarm is signaled. The model of the electrical system sensors is recalibrated based on the data from the sensors.
OPERATION RULE DETERMINATION DEVICE, OPERATION RULE DETERMINATION METHOD, AND RECORDING MEDIUM
An operation rule determination device includes an environment execution unit that obtains a state of a control target after each operation and the degree associated with the state for a series of operations on the control target, by using degree information in which the state and the degree of desirability of the state are associated with each other, and a risk-considered history generation unit that calculates a cumulative degree obtained by accumulating the obtained degree for the series of operations, and, when the cumulative degree satisfies a condition, reduces the degree associated with the state after the series of operations in the degree information.
OPERATION RULE DETERMINATION DEVICE, OPERATION RULE DETERMINATION METHOD, AND RECORDING MEDIUM
An operation rule determination device includes an environment execution unit that obtains a state of a control target after each operation and the degree associated with the state for a series of operations on the control target, by using degree information in which the state and the degree of desirability of the state are associated with each other, and a risk-considered history generation unit that calculates a cumulative degree obtained by accumulating the obtained degree for the series of operations, and, when the cumulative degree satisfies a condition, reduces the degree associated with the state after the series of operations in the degree information.
METHOD FOR OPERATING A HEARING SYSTEM
A method for operating a hearing aid system. The hearing aid system includes a hearing aid with at least one input transducer, an output transducer, and a motion sensor. The movement of a hearing aid system user is captured as movement data of the motion sensor. A probability for a future fall or trip event on the part of the hearing aid system user is determined on the basis of the captured movement data. A perceptible warning signal is generated when the probability reaches or exceeds a stored threshold value.
METHOD FOR OPERATING A HEARING SYSTEM
A method for operating a hearing aid system. The hearing aid system includes a hearing aid with at least one input transducer, an output transducer, and a motion sensor. The movement of a hearing aid system user is captured as movement data of the motion sensor. A probability for a future fall or trip event on the part of the hearing aid system user is determined on the basis of the captured movement data. A perceptible warning signal is generated when the probability reaches or exceeds a stored threshold value.