Using augmented reality to visualize optimal water sensor placement
View Patent ↗Systems and methods disclosed herein relate to using augmented reality (AR) to visualize an optimal placement location of one or more water sensors proximate a structure. Underlay layer data indicative of a field of view associated with an AR viewer device is correlated with overlay layer data that includes an indication of the water sensor optimal placement locations to create an AR display. The AR viewer displays the AR display which includes an instruction for the placing one or more water sensors proximate the structure.
1 . A computer-implemented method of using Augmented Reality (AR) for visualizing an optimal placement location of one or more water sensors proximate a structure, the method comprising:
receiving, with one or more processors, underlay layer data indicative of a field of view associated with an AR viewer device;
receiving, with the one or more processors, overlay layer data including an indication of multiple possible optimal placement locations of the one or more water sensors proximate the structure;
correlating, with the one or more processors, the overlay layer data with the underlay layer data;
creating, with the one or more processors, an AR display based upon the correlation, the AR display including an instruction for placing the one or more water sensors;
identifying, by the one or more processors, a location associated with the structure based upon the field of view associated with the AR viewer device;
querying, by the one or more processors, the overlay layer data to determine that the location is included in the indication of the multiple possible optimal placement locations of the one or more water sensors proximate the structure; and
displaying, with the one or more processors, the AR display to a user via the AR viewer device.
2 . The computer-implemented method of claim 1 , wherein the underlay layer data is generated by a camera coupled to the AR viewer device.
3 . The computer-implemented method of claim 1 , wherein the indication of the optimal placement location of the one or more water sensors proximate the structure is generated by a trained machine learning model.
4 . The computer-implemented method of claim 1 , wherein creating the AR display further comprises including text and/or graphical elements describing placing a water sensor near an object.
5 . The computer-implemented method of claim 1 , further comprising:
detecting, by the one or more processors, the one or more water sensors in the underlay data; and
responsive to detecting the one or more water sensor in the underlay data, updating, by the one or more processors, a record associated with the structure to indicate the placement of the water sensor.
6 . The computer-implemented method of claim 1 , further comprising:
generating, by the one or more processors, guidance information to a location of the structure associated with the optimal placement location of the one or more water sensors proximate the structure, wherein creating the AR display includes the guidance information.
7 . The computer-implemented method of claim 1 , further comprising:
determining, by the one or more processors, a number of water sensors to place proximate the structure; and
providing, by the one or more processors via the AR display, a number of ranked potential sources of water damage which correspond to the number of water sensors to place proximate the structure.
8 . The computer-implemented method of claim 1 , further comprising removing, by the one or more processors, one or more optimal placement locations which do not exist at the structure.
9 . A computer system configured to use Augmented Reality (AR) to visualize visualizing an optimal placement location of one or more water sensors proximate a structure, the computer system comprising:
one or more processors; and
one or more non-transitory memories storing processor-executable instructions that, when executed by the one or more processors, cause the system to:
receive underlay layer data indicative of a field of view associated with an AR viewer device;
receive overlay layer data including an indication of the multiple possible optimal placement locations of the one or more water sensors proximate the structure;
correlate the overlay layer data with the underlay layer data;
create an AR display based upon the correlation, the AR display including an instruction for placing the one or more water sensors;
identify a location associated with the structure based upon the field of view associated with the AR viewer device;
query the overlay layer data to determine that the location is included in the indication of the multiple possible optimal placement locations of the one or more water sensors proximate the structure; and
display the AR display to a user via the AR viewer device.
10 . The computer system of claim 9 , wherein the underlay layer data is generated by a camera coupled to the AR viewer device.
11 . The computer system of claim 9 , wherein the indication of the optimal placement location of the one or more water sensors proximate the structure is generated by a trained machine learning model.
12 . The computer system of claim 9 , wherein creating the AR display further comprising instructions that, when executed by the one or more processors, cause the system to include text and/or graphical elements describing placing a water sensor near an object.
13 . The computer system of claim 9 , further comprising instructions that, when executed by the one or more processors, cause the system to:
detect the one or more water sensors in the underlay data; and
responsive to detecting the one or more water sensor in the underlay data, update a record associated with the structure to indicate the placement of the water sensor.
14 . The computer system of claim 9 , further comprising instructions that, when executed by the one or more processors, cause the system to:
generate guidance information to a location of the structure associated with the optimal placement location of the one or more water sensors proximate the structure, wherein creating the AR display includes the guidance information.
15 . The computer system of claim 9 , further comprising instructions that, when executed by the one or more processors, cause the system to:
determine a number of water sensors to place proximate the structure; and
provide via the AR display a number of ranked potential sources of water damage which correspond to the number of water sensors to place proximate the structure.
16 . The computer system of claim 9 , further comprising instructions that, when executed by the one or more processors, cause the system to:
remove one or more optimal placement locations which do not exist at the structure.
17 . A non-transitory computer-readable medium storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to:
receive underlay layer data indicative of a field of view associated with an AR viewer device;
receive overlay layer data including an indication of multiple possible optimal placement locations of one or more water sensors proximate a structure;
correlate the overlay layer data with the underlay layer data;
create an AR display based upon the correlation, the AR display including an instruction for placing the one or more water sensors;
identify a location associated with the structure based upon the field of view associated with the AR viewer device;
query the overlay layer data to determine that the location is included in the indication of the multiple possible optimal placement locations of the one or more water sensors proximate the structure; and
display the AR display to a user via the AR viewer device.
18 . The non-transitory computer-readable medium of claim 17 , wherein the indication of the optimal placement location of the one or more water sensors proximate the structure is generated by a trained machine learning model.