Venue based real time crowd modeling and forecasting
First Claim
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1. A method comprising:
- sensing, using sensors of a particular mobile device, environmental data pertaining to an environment in which the particular mobile device is located;
sending the environmental data from the particular mobile device to a server that is separate from the particular mobile device;
obtaining, at the particular mobile device, an estimated wait time for the particular mobile device to traverse a line;
wherein the estimated wait time was determined by;
utilizing an estimate of a quantity of mobile devices of people currently ahead of the particular mobile device in the line, a history of model data that was generated over time, and the environmental data in order to predict a current wait time in the environment;
wherein the history provides;
amounts of time that one or more mobile devices other than the particular mobile device took to traverse the line; and
quantities of other mobile devices of people that were in the line when the one or more mobile devices entered the line; and
presenting the estimated wait time through a user interface of the particular mobile device.
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Abstract
Crowds of people within an environment can be modeled in real time. A multitude of mobile devices located within an environment can periodically transmit their geographical locations over networks to a remote server. The remote server can use these geographical locations to generate a current real-time model of a crowd of people who possess the mobile devices that transmitted the geographical locations. The remote server can transmit the model over networks back to the mobile devices. The mobile devices can use the received model to present useful information to the users of those mobile devices.
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Citations
28 Claims
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1. A method comprising:
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sensing, using sensors of a particular mobile device, environmental data pertaining to an environment in which the particular mobile device is located; sending the environmental data from the particular mobile device to a server that is separate from the particular mobile device; obtaining, at the particular mobile device, an estimated wait time for the particular mobile device to traverse a line; wherein the estimated wait time was determined by; utilizing an estimate of a quantity of mobile devices of people currently ahead of the particular mobile device in the line, a history of model data that was generated over time, and the environmental data in order to predict a current wait time in the environment; wherein the history provides; amounts of time that one or more mobile devices other than the particular mobile device took to traverse the line; and quantities of other mobile devices of people that were in the line when the one or more mobile devices entered the line; and presenting the estimated wait time through a user interface of the particular mobile device. - View Dependent Claims (2, 3, 4, 5, 18, 19, 20, 27, 28)
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6. A method comprising:
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receiving, at a server, from two or more mobile devices, environmental data pertaining to an environment in which each of the two or more mobile devices is located, wherein each of the two or more mobile devices sensed the environmental data using sensors, generating, based at least in part on the environmental data received from each of the two or more mobile devices, model data indicating current characteristics of the environment; sending the model data to each of the two or more mobile devices, wherein the model data indicates characteristics of the environment in addition to characteristics indicated within environmental data received from any single one of the two or more mobile devices; generating a history of the model data over time, wherein the history provides; amounts of time that the two or more mobile devices took to traverse a line; and quantities of mobile devices of people that were in the line when the two or more mobile devices entered the line; utilizing the history, an estimate of a quantity of people currently ahead of a particular mobile device in the line, and the environmental data, to determine an estimated wait time for the particular mobile device to traverse the line in order to predict a current wait time in the environment; and sending the estimated wait time to the particular mobile device. - View Dependent Claims (7, 8, 9, 10, 21, 22, 23, 24, 25, 26)
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11. A computer-readable memory storing instructions which, when executed by one or more processors, cause the one or more processors to perform, at a server:
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generating a history of a model over time of a particular environment based on data received over a network from a plurality of mobile devices located within the particular environment over time; determining, based on the model, a plurality of queues that currently exist within the particular environment; wherein the history provides; amounts of time that mobile devices in the plurality of mobile devices took to traverse queues of the plurality of queues; and quantities of other mobile devices of people that were in queues of the plurality of queues when each mobile device entered the queues of the plurality of queues; determining, by utilizing the history, an estimate of a quantity of people currently in each queue of the plurality of queues, and the environmental data a wait time for each queue of the plurality of queues in order to predict a current wait time in the environment; and sending, over the network, to one or more mobile devices of the plurality of mobile devices, information indicating a wait time for a particular queue of the plurality of queues. - View Dependent Claims (12, 13, 14, 15)
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16. A computer-readable memory storing instructions which, when executed by one or more processors, cause the one or more processors to perform:
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receiving, at a server, from each particular mobile device of a plurality of mobile devices, information that indicates a current location, a current direction, and a current speed of that particular mobile device; aggregating, at the server, over time, the information received from each particular mobile device in order to generate a history of crowd movement behaviors; receiving, at the server, from a particular mobile device, a planned route that a user of the particular mobile device plans to travel; determining, by utilizing the history, for each particular area of a plurality of areas through which the planned route passes, a quantity of time historically taken by other mobile device users to traverse that particular area while that particular area contained a specified quantity of other people; utilizing the quantity of time determined for each area and a quantity of other people currently on the planned route to calculate a total amount of time estimated to be required for the user of the particular mobile device to travel the planned route; and transmitting, from the server to the particular mobile device, data including the total amount of time. - View Dependent Claims (17)
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Specification