Monitoring system analytics

Patent metadata

Field	Value
Publication number	US-12450798-B2
Application number	US-202318545469-A
Country	US
Kind code	B2
Filing date	Dec 19, 2023
Priority date	Mar 12, 2015
Publication date	Oct 21, 2025
Grant date	Oct 21, 2025

Abstract

Techniques are described for presenting events detected by a monitoring system. A system receives a selection of a particular time period, identifies security events detected by a monitoring system during the selected time period, and classifies a subset of the identified security events as abnormal events. The system further generates a density of the identified security events over the selected time period, generates a density of the subset of the identified security events classified as abnormal events, and identifies monitoring system data associated with the selected time period. The system additionally generates a graphical representation of the density of the identified security events, the density of the subset of the identified security events classified as abnormal events, and the identified monitoring system data, and provides the graphical representation for display.

First claim

What is claimed is:

1. A computer-implemented method comprising:
identifying, by one or more computers, one or more events detected in an area monitored by a monitoring system during a time period;
for each event of the one or more events:
determining, by the one or more computers, a degree of abnormality of the event; and
determining, by the one or more computers, a respective weight associated with the event using the degree of abnormality of the event;

determining, by the one or more computers and using the respective weights for the one or more events, a time-varying density of the one or more events during the time period, including, for each time interval of multiple time intervals within the time period:
identifying a subset of the one or more events that occurred during the time interval;
weighting each event of the subset of the one or more events that occurred during the time interval by its respective weight; and
combining the weights of the one or more events that occurred during the time interval to obtain a weighted quantity of events that (i) occurred during the time interval and (ii) represents a portion of the time-varying density;

selecting, using the time-varying density, one or more actions to be performed by the monitoring system; and
causing the monitoring system to perform the one or more actions.

2. The computer-implemented method of claim 1 , comprising:
generating, by the one or more computers, a graphical representation of the time-varying density of the one or more events; and
configuring, by the one or more computers, a graphical user interface to display the graphical representations of the time-varying density of the one or more events.

3. The computer-implemented method of claim 2 , wherein the graphical user interface includes a timeline of the events during the time period.

4. The computer-implemented method of claim 2 , comprising:
identifying, by the one or more computers, monitoring system data associated with at least one event of the events, wherein the graphical user interface includes a visual representation of the identified monitoring system data.

5. The computer-implemented method of claim 2 , comprising receiving a selection of the time period, wherein the configuring the graphical user interface is responsive to receiving the selection of the time period.

6. The computer-implemented method of claim 2 , wherein generating the graphical representation of the events from the one or more events comprises:
generating a first graphical representation of a first event using a first weight associated with the first event; and
generating a second graphical representation of a second event using a second weight of the second event,
wherein the first weight is different from the second weight, and the first graphical representation is visually distinguishable from the second graphical representation.

7. The computer-implemented method of claim 6 , wherein:
a degree of abnormality of the first event is greater than a degree of abnormality of the second event,
the first weight determined using the degree of abnormality of the first event is greater than the second weight determined using the degree of abnormality of the second event, and
the first graphical representation is more distinctive than the second graphical representation.

8. The computer-implemented method of claim 2 , wherein generating the graphical representation of the events from the one or more events comprises:
generating first graphical representations of events having weights within a first range of weights; and
generating second graphical representations of events having weights within a second range of weights,
wherein the first graphical representations are visually distinguishable from the second graphical representations.

9. The computer-implemented method of claim 2 , wherein identifying the events detected in the area monitored by the monitoring system during the time period comprises:
obtaining monitoring data generated by multiple different sensors; and
clustering the monitoring data generated by the multiple different sensors into a single event detected in the area monitored by the monitoring system during the time period.

10. The computer-implemented method of claim 9 , wherein generating the graphical representation comprises selecting, for inclusion in the graphical representation, monitoring data representative of the event from the clusters of monitoring data.

11. The computer-implemented method of claim 9 , wherein clustering the monitoring data comprises:
clustering events using data indicating respective identified persons involved in the events; or
clustering events using data indicating respective times of occurrence of the events.

12. The computer-implemented method of claim 2 , wherein the graphical user interface includes:
a graphical representation of each of the multiple time intervals, and
for each time interval of the multiple time intervals:
a graphical representation of the weighted quantity of events that (i) occurred during the time interval and (ii) represents the portion of the time-varying density.

13. The computer-implemented method of claim 1 , comprising:
maintaining historical data associated with multiple different types of events classified as abnormal events, wherein the historical data includes data indicative of patterns of activity and individuals associated with the area monitored by the monitoring system; and
for each event of the events:
determining a confidence level that the event corresponds to one of the multiple different types of events; and
determining the degree of abnormality of the event using the confidence level.

14. The method of claim 1 , wherein the one or more events include at least one of:
a door locking or unlocking;
a door or window opening or closing; or
a light turning on or off.

15. The method of claim 1 , comprising determining a higher respective weight associated with an event having a greater degree of abnormality, and determining a lower respective weight associated with an event having a lesser degree of abnormality.

16. The method of claim 1 , wherein the one or more actions to be performed by the monitoring system include at least one of:
classifying a subset of the one or more events as abnormal events;
activating an alarm;
turning on a light; or
capturing a camera image.

17. The computer-implemented method of claim 1 , wherein the time period comprises one or more days.

18. The computer-implemented method of claim 1 , wherein each time interval of the multiple time intervals comprises one or more minutes or one or more hours.

19. A system comprising:
one or more computers; and
a storage device storing instructions that are operable, when executed by the one or more computers to cause the one or more computers to perform operations comprising:
identifying, by the one or more computers, one or more events detected in an area monitored by a monitoring system during a time period;
for each event of the one or more events:
determining, by the one or more computers, a degree of abnormality of the event; and
determining, by the one or more computers, a respective weight associated with the event using the degree of abnormality of the event,

determining, by the one or more computers and using the respective weights for the one or more events, a time-varying density of the one or more events during the time period, including, for each time interval of multiple time intervals within the

Assignees

• Alarm Com Inc

Inventors

• Kerzner Daniel
• Kinney Abraham Joseph
• Verbena Luis Fernando Guzman

Classifications

• G06T11/26 Primary

  Drawing of charts or graphs · CPC title

• G06V20/52

  Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) · CPC title

• G08B13/19682

  Graphic User Interface [GUI] presenting system data to the user, e.g. information on a screen helping a user interacting with an alarm system · CPC title

• G06F3/048

  Interaction techniques based on graphical user interfaces [GUI] · CPC title

• G08B5/22

  using electric transmission; using electromagnetic transmission · CPC title