Information management system and method
A computer-implemented method, computer program product and computing system for: defining an incident as the occurrence of a plurality of required alarms; defining an event as the occurrence of a plurality of required incidents; monitoring a plurality of devices to detect the occurrence of alarms, thus defining a plurality of detected alarms; and defining the event as having occurred if the plurality of detected alarms includes the plurality of required alarms for each of the plurality of required incidents.
1. A computer-implemented method, executed on a computing device, comprising:
defining an incident as the occurrence of a plurality of required alarms;
defining an event as the occurrence of a plurality of required incidents;
monitoring a plurality of devices to detect the occurrence of alarms, thus defining a plurality of detected alarms, including:
monitoring the plurality of devices to receive data signals indicative of the plurality of devices; and
comparing the data signals to defined signal norms to identify one or more of the plurality of detected alarms wherein the defined signal norms include patient-specific signal norms that are automatically defined by processing data signals concerning a patient over a defined period of time;
defining the event as having occurred if the plurality of detected alarms includes the plurality of required alarms for each of the plurality of required incidents;
processing one or more of the plurality of detected alarms to determine an authenticity of one or more of the plurality of detected alarms; and
adjusting one or more monitoring criteria of one or more of the plurality of devices producing the plurality of detected alarms when one or more of the plurality of detected alarms is non-authentic.
2. The computer-implemented method of claim 1 wherein defining an incident as the occurrence of a plurality of required alarms includes:
defining an incident as the occurrence of a plurality of required alarms within a defined period of time.
3. The computer-implemented method of claim 1 wherein defining an event as the occurrence of a plurality of required incidents includes:
defining an event as the occurrence of a plurality of required incidents within a defined period of time.
4. The computer-implemented method of claim 1 wherein the data signals concern one or more details of the plurality of devices and/or one or more uses of the plurality of devices.
5. The computer-implemented method of claim 1 wherein the defined signal norms include user-defined signal norms.
6. The computer-implemented method of claim 1 wherein the defined signal norms include machine-defined signal norms.
7. The computer-implemented method of claim 6 wherein the machine-defined signal norms are defined via massive data sets that are processed by machine learning.
8. The computer-implemented method of claim 6 wherein the machine-defined signal norms are compartmentalized (e.g., gender, race, age, location, device type, device class, seasonality, time of day, etc.).
9. The computer-implemented method of claim 1 wherein the plurality of devices includes one or more of: a medical device, a process control device, a networking device, a computing device, a manufacturing device, an agricultural device, an energy/refining device, an aerospace device, a forestry device, and a defense device.
10. The computer-implemented method of claim 1 wherein the plurality of devices are geographically dispersed.
11. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:
defining an incident as the occurrence of a plurality of required alarms;
defining an event as the occurrence of a plurality of required incidents;
monitoring a plurality of devices to detect the occurrence of alarms, thus defining a plurality of detected alarms, including:
monitoring the plurality of devices to receive data signals indicative of the plurality of devices; and
comparing the data signals to defined signal norms to identify one or more of the plurality of detected alarms wherein the defined signal norms include patient-specific signal norms that are automatically defined by processing data signals concerning a patient over a defined period of time;
defining the event as having occurred if the plurality of detected alarms includes the plurality of required alarms for each of the plurality of required incidents;
processing one or more of the plurality of detected alarms to determine an authenticity of one or more of the plurality of detected alarms; and
adjusting one or more monitoring criteria of one or more of the plurality of devices producing the plurality of detected alarms when one or more of the plurality of detected alarms is non-authentic.
12. The computer program product of claim 11 wherein defining an incident as the occurrence of a plurality of required alarms includes:
defining an incident as the occurrence of a plurality of required alarms within a defined period of time.
13. The computer program product of claim 11 wherein defining an event as the occurrence of a plurality of required incidents includes:
defining an event as the occurrence of a plurality of required incidents within a defined period of time.
14. The computer program product of claim 11 wherein the data signals concern one or more details of the plurality of devices and/or one or more uses of the plurality of devices.
15. The computer program product of claim 11 wherein the defined signal norms include user-defined signal norms.
16. The computer program product of claim 11 wherein the defined signal norms include machine-defined signal norms.
17. The computer program product of claim 16 wherein the machine-defined signal norms are defined via massive data sets that are processed by machine learning.
18. The computer program product of claim 16 wherein the machine-defined signal norms are compartmentalized (e.g., gender, race, age, location, device type, device class, seasonality, time of day, etc.).
19. The computer program product of claim 11 wherein the plurality of devices includes one or more of: a medical device, a process control device, a networking device, a computing device, a manufacturing device, an agricultural device, an energy/refining device, an aerospace device, a forestry device, and a defense device.
20. The computer program product of claim 11 wherein the plurality of devices are geographically dispersed.
21. A computing system including a processor and memory configured to perform operations comprising:
defining an incident as the occurrence of a plurality of required alarms;
defining an event as the occurrence of a plurality of required incidents;
monitoring a plurality of devices to detect the occurrence of alarms, thus defining a plurality of detected alarms, including:
monitoring the plurality of devices to receive data signals indicative of the plurality of devices; and
comparing the data signals to defined signal norms to identify one or more of the plurality of detected alarms wherein the defined signal norms include patient-specific signal norms that are automatically defined by processing data signals concerning a patient over a defined period of time;
defining the event as having occurred if the plurality of detected alarms includes the plurality of required alarms for each of the plurality of required incidents;
processing one or more of the plurality of detected alarms to determine an authenticity of one or more of the plurality of detected alarms; and
adjusting one or more monitoring criteria of one or more of the plurality of devices producing the plurality of detected alarms when one or more of the plurality of detected alarms is non-authentic.
22. The computing system of claim 21 wherein defining an incident as the occurrence of a plurality of required alarms includes:
defining an incident as the occurrence of a plurality of required alarms within a defined period of time.
23. The computing system of claim 21 wherein defining an event as the occurrence of a plurality of required incidents includes:
defining an event as the occurrence of a plurality of required incidents within a defined period of time.
24. The computing system of claim 21 wherein the data signals concern one or more details of the plurality of devices and/or one or more uses of the plurality of devices.
25. The computing system of claim 21 wherein the defined signal norms include user-defined signal norms.
26. The computing system of claim 21 wherein the defined signal norms include machine-defined signal norms.
27. The computing system of claim 26 wherein the machine-defined signal norms are defined via massive data sets that are processed by machine learning.