DETECTING RELATIVE CROWD DENSITY VIA CLIENT DEVICES

• US 20140189096A1
• Filed: 01/03/2013
• Published: 07/03/2014
• Est. Priority Date: 01/03/2013
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Miller, Grant D., Pollyea, Scott W., Yaswi, Hamza
• Granted Patent: US 9,003,030 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• 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: G06F 11/3048 where the topology of the computing system or computing system component explicitly influences the monitoring activity, e.g. serial, hierarchical systems
• CPC Class Codes: H04N 7/18 Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
• CPC Class Codes: H04W 4/022 with dynamic range variability

Abstract

Detecting crowds is provided. A location is selected in a set of locations a user of a client device wants to go to based on data within a profile associated with the user. A set of data inputs is monitored to determine a number of people currently at the selected location. Then, in response to determining that the number of people currently at the selected location is not greater than a user-defined threshold level of people for the selected location, a mapped route to the selected location is sent to the client device of the user.

Claims

1. A method for detecting crowds, the method comprising:

selecting, by a computer, a location in a set of locations a user of a client device wants to go to based on data within a profile associated with the user;

monitoring, by the computer, a set of data inputs to determine a number of people currently at the selected location; and

responsive to the computer determining that the number of people currently at the selected location is not greater than a user-defined threshold level of people for the selected location, sending, by the computer, a mapped route to the selected location to the client device of the user.

2. The method of claim 1 further comprising:

detecting, by the computer, a presence of the client device of the user at the selected location; and

retrieving, by the computer, a set of tasks the user of the client device wants to perform at the selected location from the profile associated with the user.

3. The method of claim 2 further comprising:

selecting, by the computer, a task in the set of tasks the user of the client device wants to perform at the selected location based on the data within the profile associated with the user;

monitoring, by the computer, the set of data inputs to determine a number of people currently at a site corresponding to the selected task; and

responsive to the computer determining that the number of people currently at the site corresponding to the selected task is not greater than a user-defined threshold level of people for the site, sending, by the computer, a mapped route to the site corresponding to the selected task to the client device of the user.

4. The method of claim 3 further comprising:

recording, by the computer, activity of the user of the client device at the site corresponding to the selected task using a video camera system.

5. The method of claim 1 further comprising:

recording, by the computer, movement of the client device of the user at the selected location using a tracking system.

6. The method of claim 1, wherein the computer estimates future crowd densities at the selected location based on recorded historical crowd density patterns at the selected location.

7. The method of claim 1, wherein the computer monitors a crowd density at a currently crowded location having greater than the user-defined threshold level of people on a predetermined time interval basis and reroutes the user of the client device based on the monitored crowd density.

8. The method of claim 1, wherein the computer collects data regarding the user of the client device to determine a behavior pattern of the user at the selected location.

9. The method of claim 1, wherein the set of data inputs includes at least one of video camera data, motion sensor data, radio frequency identification reader data, social media web site data, and location map data.

10. The method of claim 1, wherein the computer receives tracking data from the client device of the user.

11. The method of claim 1, wherein the client device of the user is one a cellular telephone, a smart phone, a personal digital assistant, a gaming device, or a handheld computer.

12-25. -25. (canceled)