# US 9,003,030 B2 · Detecting relative crowd density via client devices > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,003,030 B2 - Document ID: US9003030B2 - Status: Granted - Kind: B2 - Application number: 13/733,234 - Filed: 2013-01-03 - Published: 2014-07-03 - Granted: 2015-04-07 - Earliest claimed: 2013-01-03 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Grant D. Miller; Scott W. Pollyea; Hamza Yaswi - Web page: https://patentgrep.com/patent/US9003030B2 ## CPC - G06F 11/3048: {where the topology of the computing system or computing system component explicitly influences the monitoring activity, e.g. serial, hierarchical systems} - G01C 21/20: Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) - G01C 21/3438: {Rendezvous; Ride sharing} - H04N 7/18: Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast - H04W 4/022: {with dynamic range variability} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) ## 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 ### Claim 1 A method for detecting crowds, the method comprising: selecting, by a computer device, 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 device, a set of data inputs to determine a number of people currently at the selected location; responsive to the computer device 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 device, a mapped route to the selected location to the client device of the user; selecting, by the computer device, a task in a 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 device, the set of data inputs to determine a number of people currently at a site within the selected location corresponding to the selected task in the set of tasks; responsive to the computer device determining that the number of people currently at the site within the selected location corresponding to the selected task in the set of tasks is not greater than a user-defined threshold level of people for the site, sending, by the computer device, a mapped route to the site within the selected location corresponding to the selected task in the set of tasks to the client device of the user; responsive to the computer device determining that the client device of the user arrived at the site within the selected location corresponding to the selected task in the set of tasks within an estimated time of arrival, recording, by the computer device, activity of the user of the client device at the site within the selected location corresponding to the selected task in the set of tasks; and responsive to the computer device determining that the client device of the user left the site within the selected location corresponding to the selected task in the set of tasks, determining, by the computer device, whether another task exists in the set of tasks the user of the client device wants to perform at the selected location. ### Claim 2 (depends on 1) The method of claim 1 further comprising: detecting, by the computer device, a presence of the client device of the user at the selected location; and retrieving, by the computer device, the set of tasks the user of the client device wants to perform at the selected location from the profile associated with the user. ### Claim 3 (depends on 1) The method of claim 1, wherein the computer device records the activity of the user of the client device at the site within the selected location corresponding to the selected task using a video camera system. ### Claim 4 (depends on 1) The method of claim 1 further comprising: recording, by the computer device, movement of the client device of the user at the selected location using a tracking system. ### Claim 5 (depends on 1) The method of claim 1, wherein the computer device estimates future crowd densities at the selected location based on recorded historical crowd density patterns at the selected location. ### Claim 6 (depends on 1) The method of claim 1, wherein the computer device 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. ### Claim 7 (depends on 1) The method of claim 1, wherein the computer device collects data regarding the user of the client device to determine a behavior pattern of the user at the selected location. ### Claim 8 (depends on 1) 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. ### Claim 9 (depends on 1) The method of claim 1, wherein the computer device receives tracking data from the client device of the user. ### Claim 10 (depends on 1) 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.