Mobile tag sensing and location estimation

1. A building control system, comprising:

a mobile tag operating to move within a structure;

a plurality of sensors operating to sense a condition of the structure; and

a controller, wherein the controller operates to:

form a plurality of convex shapes by grouping a plurality of grid points into sub-pluralities of grid points, each of the sub-pluralities of grid points defining a convex shape within the structure;

generate a first set of weighted likelihoods based on a physical shape of the structure or characteristics of the structure, wherein the first set of weighted likelihoods includes a weighted likelihood of the mobile tag being at each one of a plurality of grid points within the structure;

generate a second set of weighted likelihoods based on the sensed condition of the structure, wherein the second set of weighted likelihoods includes a weighted likelihood of the mobile tag being at each one of the plurality of grid points within the structure;

generate a combined set of likelihoods based on the first set of weighted likelihoods and the second set of weighted likelihoods;

determine a distance between the mobile tag and the plurality of sensors based on at least one beacon received from the mobile tag by the plurality of sensors; and

estimate a location of the mobile tag within the structure based on the combined set of likelihoods and the distance determined based on the at least one beacon.

2. The system of claim 1 , wherein the physical shape of the structure includes a unique wall structure or materials of the structure.

3. The system of claim 1 , wherein the first set of weighted likelihoods is based on a proximity of a grid point to a wall.

4. The system of claim 1 , wherein the first set of weighted likelihoods is based on detection of multipath signals within the structure.

5. The system of claim 1 , wherein the first set of weighted likelihoods is based on determination of RF signal attenuation within the structure.

6. The system of claim 1 , wherein the structure is characterized by a convex shape based on at least one barrier of the structure.

7. The system of claim 6 , wherein the at least one barrier of the structure include at least one physical barrier or wall of the structure.

8. The system of claim 1 , wherein:

a shape of each of the plurality of convex shapes is defined by barriers of the structure; and

connecting points between each of the plurality of convex shapes are defined by openings or paths between the barriers of the structure.

9. The system of claim 1 , wherein estimating the likelihood of the tag being at each of the plurality of grid points comprises estimating a likelihood the tag is within a convex shape associated with the plurality of grid points.

10. A method, comprising:

identifying a physical shape of a structure or characteristics of the structure including:

forming a plurality of convex shapes by grouping the plurality of grid points into sub-pluralities of grid points; and

each of the sub-pluralities of grid points defines a convex shape within the structure;

sensing, by a plurality of sensors, a condition of the structure;

generating a first set of weighted likelihoods based on the physical shape of the structure or characteristics of the structure, wherein the first set of weighted likelihoods includes a weighted likelihood of a mobile tag being at each one of a plurality of grid points within the structure;

generating a second set of weighted likelihoods based on the sensed condition of the structure, wherein the second set of weighted likelihoods includes a weighted likelihood of the mobile tag being at each one of the plurality of grid points within the structure;

generating a combined set of likelihoods based on the first set of weighted likelihoods and the second set of weighted likelihoods;

determining a distance between the mobile tag and the plurality of sensors based on at least one beacon received from the mobile tag by the plurality of sensors; and

estimating a location of the mobile tag within the structure based on the combined set of likelihoods and the distance determined based on the at least one beacon.

11. The method of claim 10 , wherein identifying the physical shape of the structure or characteristics of the structure includes identifying a unique wall structure or materials of the structure.

12. The method of claim 10 , wherein generating the first set of weighted likelihoods includes generating the first set of weighted likelihoods based on a proximity of a grid point to a wall.

13. The method of claim 10 , wherein generating the first set of weighted likelihoods includes generating the first set of weighted likelihoods based on detection of multipath signals within the structure.

14. The method of claim 10 , wherein generating the first set of weighted likelihoods includes generating the first set of weighted likelihoods based on determination of RF signal attenuation within the structure.

15. The method of claim 10 , wherein identifying the physical shape of the structure or characteristics of the structure includes characterizing a convex shape of the structure based on at least one barrier of the structure.

16. The method of claim 15 , wherein the at least one barrier of the structure include at least one physical barrier or wall of the structure.

17. The method of claim 10 , wherein:

identifying the physical shape of the structure or characteristics of the structure includes defining a shape of each of the plurality of convex shapes based on barriers of the structure; and

identifying the physical shape of the structure or characteristics of the structure includes defining connecting points between each of the plurality of convex shapes by openings or paths between the barriers of the structure.

18. The method of claim 10 , wherein estimating the likelihood of the tag being at each of the plurality of grid points comprises estimating a likelihood the tag is within a convex shape associated with the plurality of grid points.