Event timeline generation

1. A method performed by a processor for selecting events from an event log for presentation along a timeline, comprising:

receiving information associated with the timeline to define an interval of interest and a partition size, wherein the received information is indicative of a start time and an end time to define the interval of interest on the timeline;

dividing the timeline into a plurality of segments based on the partition size;

determining, for each segment in the plurality of segments along the timeline, if at least one event starts within the corresponding segment and overlaps with the interval of interest wherein the determining further comprises performing a structured query language (SQL) query on the event log to determine events which overlap with the interval of interest to identify events of interest, and performing an SQL query on the event log for each segment to ascertain whether any events of interest start in the queried segment;

identifying that the corresponding segment includes at least one relevant event therein in response to determining that at least one event starts within the corresponding segment and overlaps with the interval of interest, wherein the identifying comprises classifying the ascertained events as relevant events for the queried segment;

determining parameters associated with the at least one relevant event for the corresponding segments, based on the identification that the corresponding segments include at least one relevant event therein; and

providing, to a client device to generate the timeline of the at least one relevant event, the determined parameters along with an index which designates each corresponding segment.

2. The method of claim 1 , wherein the determining parameters associated with at least one relevant event for each corresponding segment further comprises:

determining an earliest start time associated with the at least one relevant event;

determining a latest end time associated with the at least one relevant event; and

determining a count of the at least one relevant event.

3. The method of claim 1 , wherein the received start time, end time, and partition size are initially defined graphically at the client device.

4. The method of claim 1 , wherein the events are represented by data generated by at least one peripheral device.

5. The method of claim 4 , further comprising:

classifying events based on their associated peripheral device; and

filtering events based on the classification.

6. The method of claim 4 , wherein at least one of the peripheral device collects image data, video data, or a combination thereof, along with time data consistent with the timeline.

7. The method of claim 6 , further comprising:

filtering events based on metadata associated with the image or video data, including frames-per-second, resolution, format, and associated audio data.

8. The method of claim 4 , further comprising:

classifying events based on the information determined from the generated data; and

filtering events based on the classification.

9. The method of claim 8 , wherein the filtering is based on metadata generated by the at least one peripheral device, wherein the metadata comprises: position of the peripheral device, identification of the peripheral device, and a media type associated with the event.

10. The method of claim 4 , wherein the at least one peripheral device comprises a camera, a window sensor, a door sensor, a temperature controller, a proximity sensor, or any combination thereof.

11. The method of claim 1 , wherein the plurality of segments are uniformly distributed along the timeline.

12. An apparatus for selecting events from an event log which are associated with a defined time interval, comprising:

a processor; and

a memory, coupled to the processor, which stores instructions causing the processor to

receive information associated with a timeline to define an interval of interest and a partition size, wherein the received information is indicative of a start time and an end time to define the interval of interest on the timeline,

divide the timeline into a plurality of segments based on the partition size,

determine, for each segment in the plurality of segments along the timeline, if at least one event starts within the corresponding segment and overlaps with the interval of interest, wherein the instructions to determine further cause the processor to perform a structured query language (SQL) query on the event log to determine events which overlap with the interval of interest to identify events of interest, and perform an SQL query on the event log for each segment to ascertain whether any events of interest start in the queried segment,

identify that the corresponding segment includes at least one relevant event therein in response to determining that the at least one event starts within the corresponding segment and overlaps with the interval of interest, wherein the instructions to identify further cause the processor to classify the ascertained events as relevant events for the queried segment,

determine parameters associated with the at least one relevant event for the corresponding segments, based on the identification that the corresponding segments include at least one relevant event therein, and

provide, to a client device to generate the timeline of the at least one relevant event, the determined parameters along with an index which designates each corresponding segment.

13. The apparatus of claim 12 , wherein the instructions for determining parameters associated with at least one relevant event for each corresponding segment comprises further instructions causing the processor to

determine an earliest start time associated with the at least one relevant event,

determine a latest end time associated with the at least one relevant event, and

determine a count of the at least one relevant event.

14. The apparatus of claim 12 , wherein the received information indicative of the start time, end time, and partition size are initially defined graphically at the client device.

15. The apparatus of claim 12 , wherein the events are represented by data generated by at least one peripheral device.

16. The apparatus of claim 15 , wherein the memory further comprises instructions causing the processor to

classify events based on their associated peripheral devices, and

filter relevant events based on the classification.

17. The apparatus of claim 15 , wherein at least one of the peripheral devices collects image data, video data, or a combination thereof, along with time data consistent with the timeline.

18. The apparatus of claim 17 , wherein the memory further comprises instructions causing the processor to

filter events based on metadata associated with the image or video data, including frames-per-second, resolution, format, and associated audio data.

19. The apparatus of claim 15 , wherein the memory further comprises instructions causing the processor to

classify events based on the information determined from the generated data, and

filter relevant events based on the classification.

20. The apparatus of claim 19 , wherein the filtering is based on metadata generated by the at least one peripheral device, and further wherein the metadata comprises: position of the peripheral device, identification of the peripheral device, a media type associated with the event.

21. The apparatus of claim 15 , wherein the at least one peripheral device comprises a camera, a window sensor, a door sensor, a temperature controller, proximity sensor, or any combination thereof.