Automated creation of semantically-enriched diagnosis models
AssigneeInternational Business Machines Corporation
InventorsFreddy Lecue, Joern Ploennigs, Anika Schumann
Life of this patent
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Abstract
A system, method and a computer program product may be provided for automatically creating and parameterizing a semantically-enriched diagnosis model for an entity. The system receives a list of data points, from sensors or a database, to be used to create a diagnosis model. The system automatically creates the diagnosis model based on the received list of data points and data stored in a database and parameterizes the diagnosis model. The parameterized diagnosis model reflects rules that determine one or more potential causes of one or more abnormalities of one or more physical conditions in the entity.
Claims20
A method for generating a parameterized semantic diagnosis model, the method comprising:
- sensing, by using a network of sensors, a time series of data points for physical conditions associated with a specified system;
- receiving, by a computer system, the time series of data points from the network of sensors;
- semantically annotating the received data points by adding semantic concepts to each of the data points, to create a semantic data point model comprised of a set of the semantically annotated data points;
- creating variables representing the physical conditions detected by the sensors;
- generating a semantic variable model comprising a data representation of the created variables;
- determining a relationship between the created variables that reflect interactions between the created variables;
- creating a semantic physical model representing the determined relationship;
- based on the created semantic physical model, creating a semantic diagnosis model to diagnose potential causes of the physical conditions of the specified system;
- and
- parameterizing the semantic diagnosis model to create a parameterized semantic diagnosis model to identify one or more potential causes of specified abnormal conditions of the specified system detected by the network of sensors.
An apparatus for generating a semantic diagnosis model, the apparatus comprising:
- a memory device;
- a processor coupled to the memory device, wherein the processor is configured to perform:
- receive from a network of sensors a time series of data points for physical conditions associated with a specified system;
- semantically annotate the received data points by adding semantic concepts to each of the data points, to create a semantic data point model comprised of a set of the semantically annotated data points;
- create variables representing the physical conditions detected by the sensors;
- generate a semantic variable model comprising a data representation of the created variables;
- determine a relationship between the created variables that reflect interactions between the created variables;
- create a semantic physical model representing the determined relationship;
- based on the created semantic physical model, create a semantic diagnosis model to diagnose potential causes of the physical conditions of the specified system;
- and
- parameterize the semantic diagnosis model to create a parameterized semantic diagnosis model to identify one or more potential causes of specified abnormal conditions of the specified system detected by the network of sensors.
A computer program product for generating a semantic diagnosis model on a computer system, the computer program product comprising a storage medium that excludes a propagating signal, the storage medium readable by a processing circuit and storing instructions run by the processing circuit for performing a method, said method steps comprising:
- receiving, by the computer system, from a network of sensors a time series of data points for physical conditions associated with a specified system;
- semantically annotating the received data points by adding semantic concepts to each of the data points, to create a semantic data point model comprised of a set of the semantically annotated data points;
- creating variables representing the physical conditions detected by the sensors;
- generating a semantic variable model comprising a data representation of the created variables;
- determining a relationship between the created variables that reflect interactions between the created variables;
- creating a semantic physical model representing the determined relationship;
- based on the created semantic physical model, creating a semantic diagnosis model to diagnose potential causes of the physical conditions of the specified system;
- and
- parameterizing the semantic diagnosis model to create a parameterized semantic diagnosis model to identify one or more potential causes of specified abnormal conditions of the specified system detected by the network of sensors.
Dependencies are inferred from the claim text.