Methods and systems for using video surveillance to detect falling liquids
Apparatus and methods for automatically detecting falling fluid include receiving one or more live video feeds from one or more cameras. The live video feeds are received concurrently. The live video feeds are analyzed to detect a fluid leak using a motion algorithm. False positives are reduced and sensitivity for the fluid leak detection is improved using information from one or more integrated systems, in response to detecting the fluid leak. A notification is generated to inform a user of the detected fluid leak, in response to detecting the fluid leak after reducing the false positives.
1. A method for automatically detecting a fluid leak, comprising:
receiving, by a processor, one or more live video feeds from one or more cameras;
analyzing, by the processor, the one or more live video feeds to detect the fluid leak in response to identifying a motion of a vertically falling fluid using a motion algorithm, wherein the motion comprises the motion of one or more objects travelling at a velocity corresponding to falling under effect of gravity forces, repeatedly falling vertically downward in a same region of a field of view of the one or more cameras, and/or falling with a substantially constant frequency; and
generating a notification, by the processor, to inform a user of the fluid leak, in response to detecting the fluid leak.
2. The method of claim 1 , further comprising, in response to detecting the fluid leak, reducing false positives and improving sensitivity of detection of the fluid leak using information from one or more integrated systems, wherein generating the notification comprises generating the notification after reducing the false positives.
3. The method of claim 2 , wherein the one or more integrated systems comprise at least one of: an occupancy sensor, a weather report, a water pressure meter, and/or a Heating Ventilating and Air Conditioning (HVAC) system.
4. The method of claim 1 , wherein the one or more live video feeds are received concurrently.
5. The method of claim 1 , wherein the fluid leak is detected by identifying one or more fluid drips using one or more dense optical flow techniques.
6. The method of claim 1 , further comprising generating a confidence score of the fluid leak based on the one or more live video feeds, wherein the confidence score is indicative of an accuracy of detection of the fluid leak.
7. The method of claim 1 , wherein the fluid leak is detected using a machine learning model trained using a plurality of video feeds corresponding to one or more types of fluid leaks.
8. The method of claim 1 , further comprising displaying the notification to the user using a Graphical User Interface (GUI).
9. The method of claim 8 , wherein the GUI includes a user interface element configured for filtering received notifications based on at least one of: a geographic location, a building, and/or a room.
10. The method of claim 1 , wherein identifying the motion of the vertically falling fluid comprises measuring a fluid flow velocity.
11. The method of claim 10 , further comprising adjusting a range of velocities associated with the fluid leak based on a range of distances from the one or more cameras to the one or more objects that are being monitored.
12. A system for automatically detecting a fluid leak, comprising:
a hardware processor configured to:
receive one or more live video feeds from one or more cameras;
analyze the one or more live video feeds to detect the fluid leak in response to identifying a motion of a vertically falling fluid using a motion algorithm, wherein the motion comprises the motion of one or more objects travelling at a velocity corresponding to falling under effect of gravity forces, repeatedly falling vertically downward in a same region of a field of view of the one or more cameras, and/or falling with a substantially constant frequency; and
generate a notification to inform a user of the fluid leak, in response to detecting the fluid leak.
13. The system of claim 12 , wherein, in response to detecting the fluid leak, the hardware processor is further configured to reduce false positives and improve sensitivity of detection of the fluid leak using information from one or more integrated systems, wherein the hardware processor is further configured to generate the notification after reducing the false positives.
14. The system of claim 13 , wherein the one or more integrated systems comprise at least one of: an occupancy sensor, a weather report, a water pressure meter, and/or a Heating Ventilating and Air Conditioning (HVAC) system.
15. The system of claim 12 , wherein the one or more live video feeds are received concurrently.
16. The system of claim 12 , wherein the fluid leak is detected by identifying one or more fluid drips using one or more dense optical flow techniques.
17. The system of claim 12 , wherein the hardware processor is further configured to generate a confidence score of the fluid leak based on the one or more live video feeds, wherein the confidence score is indicative of an accuracy of detection of the fluid leak.
18. The system of claim 12 , wherein the fluid leak is detected using a machine learning model trained using a plurality of video feeds corresponding to one or more types of fluid leaks.
19. The system of claim 12 , wherein the hardware processor is further configured to display the notification to the user using a Graphical User Interface (GUI).
20. The system of claim 19 , wherein the GUI includes a user interface element configured for filtering received notifications based on at least one of: a geographic location, a building, and/or a room.