IP Library Granted Patent US 12,555,136
Granted Patent B2
US 12,555,136 · App. 18/739,451 · Granted Feb 17, 2026

Geospatially informed resource utilization

Inventors: Yan Mayster (Aurora, CO); Robert Bruce Bahnsen (Boulder, CO); Brian D. Shucker (Superior, CO)
Assignee: Google LLC
G06Q30/0246G06Q30/0205
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,555,136
App. No.
18/739,451
Granted
Feb 17, 2026
Kind
B2
Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adjusting physical location usage for a plurality of particular locations. Methods can include obtaining a three-dimensional (3D) representation of the given geographic area, wherein the 3D representation depicts a view of the given geographic area from a specified viewing perspective. For the given geographic area, traffic data is obtained indicating different traffic volumes during different time periods and one or more traffic characteristics. The 3D representation is segmented into a plurality of particular locations. For each particular location among the plurality of particular locations and based on the traffic data, a viewability score is determined that indicates an aggregate amount of time that the particular location is viewable by traffic passing the different locations. Physical location usage is then adjusted based on the viewability scores for the plurality of particular locations.

Claims (72)

1 . A computer-implemented method, comprising:

obtaining, for a given set of users, trip data specifying a geographic path traversed by a given set of users;

obtaining, for the geographic path, semantic data specifying content to which the given set of users was exposed while traversing the geographic path;

determining, based on the geographic path and the semantic data, an exposure time indicating an aggregate amount of time that the given set of users was exposed to specific content while traversing the geographic path;

generating a contribution score for the content to which the given set of users was exposed while traversing the geographic path based on the exposure time;

segmenting attribution of user actions performed by the given set of users based on the contribution score for the content; and

adjusting physical location usage based on a portion of the segmented attribution that is assigned to the content, wherein adjusting the physical location usage comprises:

selecting, based on the contribution score, a location from among a plurality of locations to present the content on a physical structure at the selected location; and

adjusting, based on the contribution score, viewability of the content presented on a surface of a physical structure at the selected location by adjusting an existing display property of the surface, wherein adjusting the existing display property includes toggling power of a display of the physical structure.

2 . The method of claim 1 , wherein segmenting attribution of user actions performed by the user comprises segmenting attribution between exposure while traversing the geographic path and other techniques of content exposure.

3 . The method of claim 1 , wherein segmenting attribution of user actions performed by the user further comprises segmenting attribution between different exposures to content while traversing the geographic path, wherein the content for each of the different exposures was presented on different physical structure in a different location.

4 . The method of claim 1 , wherein adjusting physical location usage comprises:

removing existing physical structures from the physical location;

changing power usage characteristics for the display of content on the physical structures in the physical location;

placing one or more contents on the physical structure of the physical location; or

adjusting viewing characteristics of the one or more contents that is presented on the physical structure of the physical location.

5 . The method of claim 1 , wherein determining the contribution score comprises:

determining a viewing time of the content of the set of users in vehicles while travelling on the geographic path;

determining an attention factor of the users in the vehicles while travelling on the geographic path through the physical location based on one or more traffic characteristics;

determining an expected number of users in the vehicles in the traffic;

computing a viewability score based on the viewing time, attention factor and the expected number of users in a vehicle; and

computing the contribution score based on the viewability score.

6 . The method of claim 5 , wherein the one or more traffic characteristics comprises (i) a speed of the vehicles that pass through the given geographic path, (ii) a number of drivers or passengers of the vehicles that pass through the given geographic path, (iii) visibility characteristics during a time of the day when the one or more traffic characteristics are recorded.

7 . A system, comprising:

one or more processors;

a memory device having stored thereon computer readable instructions configured to cause the one or more processors to perform operations comprising:

obtaining, for a given set of users, trip data specifying a geographic path traversed by a given set of users;

obtaining, for the geographic path, semantic data specifying content to which the given set of users was exposed while traversing the geographic path;

determining, based on the geographic path and the semantic data, an exposure time indicating an aggregate amount of time that the given set of users was exposed to specific content while traversing the geographic path;

generating a contribution score for the content to which the given set of users was exposed while traversing the geographic path based on the exposure time;

segmenting attribution of user actions performed by the given set of users based on the contribution score for the content; and

adjusting physical location usage based on a portion of the segmented attribution that is assigned to the content, wherein adjusting the physical location usage comprises:

selecting, based on the contribution score, a location from among a plurality of locations to present the content on a physical structure at the selected location; and

adjusting, based on the contribution score, viewability of the content presented on a surface of a physical structure at the selected location by adjusting an existing display property of the surface, wherein adjusting the existing display property includes toggling power of a display of the physical structure.

8 . The system of claim 7 , wherein segmenting attribution of user actions performed by the user comprises segmenting attribution between exposure while traversing the geographic path and other techniques of content exposure.

9 . The system of claim 7 , wherein segmenting attribution of user actions performed by the user further comprises segmenting attribution between different exposures to content while traversing the geographic path, wherein the content for each of the different exposures was presented on different physical structure in a different location, wherein adjusting the existing display property includes toggling power of a display of the physical structure.

10 . The system of claim 7 , wherein adjusting physical location usage comprises:

removing existing physical structures from the physical location;

changing power usage characteristics for the display of content on the physical structures in the physical location;

placing one or more contents on the physical structure of the physical location; or

adjusting viewing characteristics of the one or more contents that is presented on the physical structure of the physical location.

11 . The system of claim 7 , wherein determining the contribution score comprises:

determining a viewing time of the content of the set of users in vehicles while travelling on the geographic path;

determining an attention factor of the users in the vehicles while travelling on the geographic path through the physical location based on one or more traffic characteristics;

determining an expected number of users in the vehicles in the traffic;

computing a viewability score based on the viewing time, attention factor and the expected number of users in a vehicle; and

computing the contribution score based on the viewability score.

12 . The system of claim 11 , wherein the one or more traffic characteristics comprises (i) a speed of the vehicles that pass through the given geographic path, (ii) a number of drivers or passengers of the vehicles that pass through the given geographic path, (iii) visibility characteristics during a time of the day when the one or more traffic characteristics are recorded.

13 . A non-transitory computer readable medium storing instructions that, upon execution by one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising:

obtaining, for a given set of users, trip data specifying a geographic path traversed by a given set of users;

obtaining, for the geographic path, semantic data specifying content to which the given set of users was exposed while traversing the geographic path;

determining, based on the geographic path and the semantic data, an exposure time indicating an aggregate amount of time that the given set of users was exposed to specific content while traversing the geographic path;

generating a contribution score for the content to which the given set of users was exposed while traversing the geographic path based on the exposure time;

segmenting attribution of user actions performed by the given set of users based on the contribution score for the content; and

adjusting physical location usage based on a portion of the segmented attribution that is assigned to the content, wherein adjusting the physical location usage comprises:

selecting, based on the contribution score, a location from among a plurality of locations to present the content on a physical structure at the selected location; and

adjusting, based on the contribution score, viewability of the content presented on a surface of a physical structure at the selected location by adjusting an existing display property of the surface, wherein adjusting the existing display property includes toggling power of a display of the physical structure.

14 . The non-transitory computer readable medium of claim 13 , wherein segmenting attribution of user actions performed by the user comprises segmenting attribution between exposure while traversing the geographic path and other techniques of content exposure.

15 . The non-transitory computer readable medium of claim 13 ,

wherein segmenting attribution of user actions performed by the user further comprises segmenting attribution between different exposures to content while traversing the geographic path, wherein the content for each of the different exposures was presented on different physical structure in a different location.

16 . The non-transitory computer readable medium of claim 13 , wherein adjusting physical location usage comprises:

removing existing physical structures from the physical location;

changing power usage characteristics for the display of content on the physical structures in the physical location;

placing one or more contents on the physical structure of the physical location; or

adjusting viewing characteristics of the one or more contents that is presented on the physical structure of the physical location.

17 . The non-transitory computer readable medium of claim 13 , wherein determining the contribution score comprises:

determining a viewing time of the content of the set of users in vehicles while travelling on the geographic path;

determining an attention factor of the users in the vehicles while travelling on the geographic path through the physical location based on one or more traffic characteristics;

determining an expected number of users in the vehicles in the traffic;

computing a viewability score based on the viewing time, attention factor and the expected number of users in a vehicle; and

computing the contribution score based on the viewability score.

18 . The non-transitory computer readable medium of claim 17 , wherein the one or more traffic characteristics comprises (i) a speed of the vehicles that pass through the given geographic path, (ii) a number of drivers or passengers of the vehicles that pass through the given geographic path, (iii) visibility characteristics during a time of the day when the one or more traffic characteristics are recorded.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 26, 2024
From: MAYSTER, YAN; BAHNSEN, ROBERT BRUCE; SHUCKER, BRIAN D.
To: GOOGLE LLC
Reel/Frame 068101/0020 →
Continuity (2)
Continuation 17802248
Related Publication 20240330979A1 · Oct 3, 2024
References Cited (36)
US 7920072B2 · Smith · 2011 [cited by examiner]
US 8850011B2 · Kimchi · 2014 [cited by examiner]
US 10042359B1 · Konrardy et al. · 2018 [cited by applicant]
US 11170138B2 · Stroila · 2021 [cited by examiner]
US 20050143902A1 · Soulchin et al. · 2005 [cited by applicant]
US 20060053110A1 · McDonald · 2006 [cited by examiner]
US 20100050201A1 · Kubota · 2010 [cited by examiner]
US 20110131597A1 · Cera · 2011 [cited by examiner]
US 20150161682A1 · Karamchedu · 2015 [cited by examiner]
US 20150227965A1 · Drysch · 2015 [cited by examiner]
US 20150286454A1 · Hickman · 2015 [cited by examiner]
US 20200151265A1 · Gupta · 2020 [cited by examiner]
US 20200184862A1 · Kim · 2020 [cited by examiner]
EP 1872294 · 2008 [cited by applicant]
JP 2019036048 · 2019 [cited by applicant]
JP 2019036049 · 2019 [cited by applicant]
KR 101213857 · 2012 [cited by applicant]
KR 1020190070961 · 2019 [cited by applicant]
WO WO2006029022 · 2006 [cited by applicant]
WO WO2008062819 · 2008 [cited by applicant]
WO WO2012073027A2 · 2012 [cited by examiner]
WO WO2020183652 · 2020 [cited by applicant]
Yang, Xu; Zimba, Billy; Qiao, Tingting; Gao, Keyan; Chen, Xiaoya, Exploring IoT Location Information to Perform Point of Interest Recommendation engine: Traveling to a New Geographical Region (English), Sensors (Basel, … [cited by examiner]
Banerjee et al., “Assessing brand visibility using machine learning Technical Disclosure” Oct. 30, 2017, 11 pages. [cited by applicant]
Extended European Search Report in European Appln. No. 23211019.7, mailed on Feb. 26, 2024, 6 pages. [cited by applicant]
Huang et al., “Interest-Driven Outdoor Advertising Display Location Selection Using Mobile Phone Data (English)” IEEE Access, vol. 7, Jan. 2019, 30878-30889. [cited by applicant]
International Search Report and Written Opinion in International Appln. No. PCT/US2021/025853, mailed on Dec. 22, 2021, 13 pages. [cited by applicant]
Ip.com [online], “Determining Optimal Dimming of Displays” Jan. 5, 2018, retrieved on Jan. 19, 2024, retrieved from URL <https://Ip.com/IPCOM000252351>, 39 pages. [cited by applicant]
Liu et al., “SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations” IEEE Transactions on Visualization and Computer Graphics, vol. 23, No. 1, Jan. 2017, 10 pages. [cited by applicant]
Notice of Allowance in Japanese Appln. No. 2022-557924, mailed on Nov. 6, 2023, 5 pages (with English translation). [cited by applicant]
Notice of Allowance in Japanese Appln. No. 2023-204762, mailed on Aug. 13, 2024, 5 pages (with English translation). [cited by applicant]
Notice of Allowance in Korean Appln. No. 10-2022-7032011, mailed on Jul. 10, 2024, 5 pages (with English translation). [cited by applicant]
Office Action in Canadian Appln. No. 3,185,316, mailed on Nov. 30, 2023, 4 pages. [cited by applicant]
Office Action in Korean Appln. No. 10-2022-7032011, mailed on Apr. 29, 2024, 14 pages (with English translation). [cited by applicant]
Simmons et al., “Hub Map: A new approach for vizualizing traffic data sets with multi-attribute link data (English)” 2015 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), Jan. 2016, 219-223. [cited by applicant]
Office Action in Indian Appln. No. 202227048932, mailed on Apr. 2, 2025, 6 pages (with English translation). [cited by applicant]