Real-Time Mapping Using Geohashing

• US 20180017406A1
• Filed: 02/23/2017
• Published: 01/18/2018
• Est. Priority Date: 07/13/2016
• Status: Active Grant

• Current Assignee: Taymour Semnani
• Original Assignee: Taymour Semnani
• Inventors: Semnani, Taymour, Manizad, Kaveh, Geana, Raul, Poamaneagra, Gabriel, Georgui, Ileana, Melone, Jay, Vetan, John
• Granted Patent: US 10,794,721 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01C 21/3438 Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
• CPC Class Codes: G01C 21/3676 Overview of the route on the road map

Abstract

Systems and methods for real-time mapping using geohashing are described. In an example implementation, a method includes receiving current location data from a first computing device in real-time, mapping the current location data in a map that includes collected location data from a second computing device, generating a heat map based on the current location data and the collected location data, determining a line using the generated heat map, and providing a route suggestion based on the determined line to the first computing device.

Claims

1. A method comprising:

receiving current location data from a first computing device in real-time;

mapping the current location data in a map that includes collected location data from a second computing device;

generating a heat map based on the current location data and the collected location data;

determining a line using the generated heat map; and

providing a route suggestion based on the determined line to the first computing device.

2. The method of claim 1, wherein mapping the current location data in the map further comprises:

determining that the current location data satisfies a threshold accuracy; and

mapping the current location data in the map in response to the current location data satisfies the threshold accuracy.

3. The method of claim 1, wherein mapping the current location data in the map further comprises:

mapping the current location data into a geohash overlaying the map, the geohash including a plurality of grid sections.

4. The method of claim 3, wherein determining the line using the heat map further comprises:

decoding a portion of the plurality of the grid sections into coordinate data;

labeling one grid section of the plurality of the grid sections as a grid section of interest based on the coordinate data being associated with an area of interest;

comparing a current timestamp associated with the current location data to a neighboring timestamp associated with previously collected location data in a neighboring grid section;

determining that the neighboring timestamp of the neighboring grid section satisfies a threshold time period; and

labeling the grid section of interest and the neighboring grid section as forming a portion of the line.

5. The method of claim 3, wherein determining the line using the heat map further comprises:

determining a density of each of the grid sections, the density being related to a quantity of location points from separate computing devices collected over a time period;

comparing the densities of each of the grid sections to densities of adjacent grid sections; and

determining the line includes adjacent grid sections that include densities that satisfy a density threshold compared to neighboring grid sections.

6. The method of claim 5, wherein the route suggestion is a wait-time for the determined line.

7. The method of claim 6, wherein the wait-time is determined by comparing the densities of the grid sections of the line to historical data of similar densities of grid sections and estimated times to move through similar densities.

8. The method of claim 1, wherein receiving the current location data from the first computing device further comprises:

detecting that the first computing device has entered a tracking area; and

in response to detecting that the first computing device has entered the tracking area, receiving the current location data from the first computing device.

9. A system comprising:

a processor; and

a memory storing instructions that, when executed, cause the system to perform instructions including;

receiving current location data from a first computing device in real-time;

mapping the current location data in a map that includes collected location data from a second computing device;

generating a heat map based on the current location data and the collected location data;

determining a line using the generated heat map; and

providing a route suggestion based on the determined line to the first computing device.

10. The system of claim 9, wherein mapping the current location data in the map further comprises:

determining that the current location data satisfies a threshold accuracy; and

mapping the current location data in the map in response to the current location data satisfies the threshold accuracy.

11. The system of claim 9, wherein mapping the current location data in the map further comprises:

mapping the current location data into a geohash overlaying the map, the geohash including a plurality of grid sections.

12. The system of claim 11, wherein determining the line using the heat map further comprises:

decoding a portion of the plurality of the grid sections into coordinate data;

labeling one grid section of the plurality of the grid sections as a grid section of interest based on the coordinate data being associated with an area of interest;

comparing a current timestamp associated with the current location data to a neighboring timestamp associated with previously collected location data in a neighboring grid section;

determining that the neighboring timestamp of the neighboring grid section satisfies a threshold time period; and

labeling the grid section of interest and the neighboring grid section as forming a portion of the line.

13. The system of claim 11, wherein determining the line using the heat map further comprises:

determining a density of each of the grid sections, the density being related to a quantity of location points from separate computing devices collected over a time period;

comparing the densities of each of the grid sections to densities of adjacent grid sections; and

determining the line includes adjacent grid sections that include densities that satisfy a density threshold compared to neighboring grid sections.

14. The system of claim 13, wherein the route suggestion is a wait-time for the determined line.

15. The system of claim 14, wherein the wait-time is determined by comparing the densities of the grid sections of the line to historical data of similar densities of grid sections and estimated times to move through similar densities.

16. The system of claim 9, wherein receiving the current location data from the first computing device further comprises:

detecting that the first computing device has entered a tracking area; and

in response to detecting that the first computing device has entered the tracking area, receiving the current location data from the first computing device.

17. A method comprising:

detecting that a computing device has entered into a tracking area and beginning a session related to the computing device;

receiving a plurality of location points related to locations of the computing device at periodic time intervals;

determine an accuracy of each of the plurality of location points and storing location points that satisfy a threshold accuracy;

aggregating the plurality of location points by mapping the plurality of location points into a grid including grid sections;

clustering the location points in each of the grid sections;

decoding a portion of the grid sections into coordinate data and labeling one of the grid sections that corresponds to an area of interest within the tracking area as a grid section of interest;

comparing a timestamp of a location point in the grid section of interest to a timestamp of a neighboring location point in a neighboring grid section;

determining that the comparison satisfies a threshold time period;

aggregating the neighboring grid section and the grid section of interest and labeling the aggregated sections as a line;

determining a wait-time for the session based on the line; and

providing the wait-time to a computing device.

18. The method of claim 17, further comprising:

determining a route through the tracking area based on the line.

19. The method of claim 18, wherein determining the route through the tracking area based on the line further comprises:

identifying a bottleneck where a density of location points satisfies a bottleneck threshold; and

identifying a throughput where a density of location point indicates a flow.

20. The method of claim 17, wherein clustering the location points further comprises:

aggregating the location points in each of the grid sections; and

assigning a density value to each of the grid sections based on the aggregated location points.