Moisture sensing roofing systems and methods thereof

Patent metadata

Field	Value
Publication number	US-11610468-B2
Application number	US-202117222683-A
Country	US
Kind code	B2
Filing date	Apr 5, 2021
Priority date	Oct 1, 2020
Publication date	Mar 21, 2023
Grant date	Mar 21, 2023

Abstract

In some embodiments, the present disclosure provides an exemplary system that includes radio frequency (RF) tags; positioned at locations throughout a roof; a tag reader configured to: generate reader RF signals at one or more frequencies to read the plurality of RF tags, and detect return RF signals from the plurality of RF tags; where the RF signals carry tag data comprising impedance values and tag identifiers; a processor of a computing device, programmed to receive the tag data; determine corresponding locations of the plurality of RF tags; and determine a wet state or dry state of the roof at one or more corresponding locations, and output an indicator of the wet state or the dry state of the roof at the one or more corresponding locations.

First claim

What is claimed is:

1. A method comprising:
receiving, by the at least one processor, at least one return RF signal read by at least one tag reader;
wherein the at least one return RF signal encodes tag data from at least one RF tag associated with the at least one return RF signal;
wherein the tag data comprises at least one impedance value of the at least one RF tag;
wherein the at least one RF tag is associated with at least one location of a roof, wherein the at least one RF tag is installed on the roof, proximate to the roof, in a vicinity of the roof, in the roof, or a combination thereof;

obtaining, by the at least one processor, at least one dry state linear regression function associated with the at least one RF tag;
determining, by the at least one processor, a wet state or a dry state of the at least one location of the roof based, at least in part, on the at least one impedance value of the at least one RF tag and the at least one dry state linear regression function of the at least one RF tag, and
outputting, by the at least one processor to at least one computing device, an indicator of the wet state or the dry state of the at least one location.

2. The method as recited in claim 1 , further comprising:
determining, by the at least one processor, based at least in part on the at least one dry state linear regression function, at least one deviation of the at least one impedance value of the at least one RF tag; and
determining, by the at least one processor, the wet state or the dry state based on the at least one deviation.

3. The method of claim 2 , wherein the corresponding location has a distance between 0.1 inches and 10 inches.

4. The method of claim 2 , wherein the at least one processor is a processor of an Internet-of-Things device that is:
i) located within a building structure having the roof and
ii) configured to upload the tag data to a moisture assessment server.

5. The method of claim 1 , wherein the indicator of the wet state comprises an indication of at least one characteristic of a moisture content at the corresponding location of the roof.

6. The method of claim 1 , further comprising receiving, by the at least one processor, the at least one return RF signal from the at least one tag reader over at least one network.

7. The method of claim 1 , further comprising receiving, by the at least one processor, the at least one return RF signal directly from the at least one tag reader.

8. The method of claim 1 , further comprising receiving, by the at least one processor, the at least one return RF signal from a computing device connected to the at least one tag reader.

9. A non-transitory computer readable medium having software instructions stored thereon, the software instructions configured to cause at least one processor to perform steps comprising:
receiving at least one return RF signal read by at least one tag reader;
wherein the at least one return RF signal encodes tag data from at least one RF tag associated with the at least one return RF signal;
wherein the tag data comprises at least one impedance value of the at least one RF tag;
wherein the at least one RF tag is associated with at least one location of a roof, wherein the at least one RF tag is installed on the roof, proximate to the roof, in a vicinity of the roof, in the roof, or a combination thereof;

obtaining at least one dry state linear regression function associated with the at least one RF tag;
determining a wet state or a dry state of the at least one location of the roof based, at least in part, on the at least one impedance value of the at least one RF tag and the at least one dry state linear regression function of the at least one RF tag, and
outputting, to at least one computing device, an indicator of the wet state or the dry state of the at least one location.

10. The non-transitory computer readable medium as recited in claim 9 , wherein the software instructions are further configured to cause at least one processor to perform steps comprising:
determining based at least in part on the at least one dry state linear regression function, at least one deviation of the at least one impedance value of the at least one RF tag; and
determining the wet state or the dry state based on the at least one deviation.

11. The non-transitory computer readable medium of claim 10 , wherein the corresponding location has a distance between 0.1 inches and 10 inches.

12. The non-transitory computer readable medium of claim 10 , wherein the at least one processor is a processor of an Internet-of-Things device that is:
i) located within a building structure having the roof and
ii) configured to upload the tag data to a moisture assessment server.

13. The non-transitory computer readable medium of claim 9 , wherein the indicator of the wet state comprises an indication of at least one characteristic of a moisture content at the corresponding location of the roof.

14. The non-transitory computer readable medium of claim 9 , wherein the software instructions are further configured to cause at least one processor to perform steps comprising receiving the at least one return RF signal from the at least one tag reader over at least one network.

15. The non-transitory computer readable medium of claim 9 , wherein the software instructions are further configured to cause at least one processor to perform steps comprising receiving the at least one return RF signal directly from the at least one tag reader.

16. The non-transitory computer readable medium of claim 9 , wherein the software instructions are further configured to cause at least one processor to perform steps comprising receiving the at least one return RF signal from a computing device connected to the at least one tag reader.

17. A system comprising:
at least one processor configured to execute software instruction that cause the at least one processor to perform steps to:
receive at least one return RF signal read by at least one tag reader;
wherein the at least one return RF signal encodes tag data from at least one RF tag associated with the at least one return RF signal;
wherein the tag data comprises at least one impedance value of the at least one RF tag;
wherein the at least one RF tag is associated with at least one location of a roof, wherein the at least one RF tag is installed on the roof, proximate to the roof, in a vicinity of the roof, in the roof, or a combination thereof;

obtain at least one dry state linear regression function associated with the at least one RF tag;
determine a wet state or a dry state of the at least one location of the roof based, at least in part, on the at least one impedance value of the at least one RF tag and the at least one dry state linear regression function of the at least one RF tag, and
output to at least one computing device an indicator of the wet state or the dry state of the at least one location.

18. The system as recited in claim 17 , wherein the at least one processor is further configured to execute software instruction that cause the at least one processor to perform steps to:
determine based at least in part on the at least one dry state linear regression function, at least one deviation of the at least one impedance value of the at least one RF tag; and
determine the wet state or the dry state based on the at least one deviation.

19. The system of claim 17 , wherein the at least one processor is further configured to execute software instruction that cause the at least one processor to p

Assignees

• Bmic Llc

Inventors

• Alovert Igor

Classifications

• G08B21/20 Primary

  responsive to moisture · CPC title

• G16Y40/10

  Detection; Monitoring · CPC title

• G08B29/24

  Self-calibration, e.g. compensating for environmental drift or ageing of components · CPC title

• G16Y20/10

  relating to the environment, e.g. temperature; relating to location · CPC title

• G06K7/10366

  the interrogation device being adapted for miscellaneous applications · CPC title