WO2013075890A1

WO2013075890A1 - Apparatus and method for a communications network

Info

Publication number: WO2013075890A1
Application number: PCT/EP2012/070577
Authority: WO
Inventors: Chandrasekaran Vasudevan; Vinish KATHURIA
Original assignee: Telefonaktiebolaget L M Ericsson (Publ)
Priority date: 2011-11-21
Filing date: 2012-10-17
Publication date: 2013-05-30

Abstract

A plurality of user devices in a selected location area are monitored. Information relating to the device type is determined for each of the user devices being monitored in the location area. User devices are classified according to the device type information, and the result of the classifying used to provide a distribution profile of the types of user devices in the location area. The distribution profile of the types of user devices can be used for a number of different applications, including targeted advertising, or automatic social class modelling.

Description

Apparatus and Method for a Communications Network Technical Field

The present invention relates to an apparatus and method for a

communications network, and in particular to an apparatus and method for providing a distribution profile of the types of user devices in a location area of the network, for use in applications such as social class modelling or targeted advertising. Background

Footfall is a term used to measure and monitor people traffic in a geographical area, for example in shops or public spaces. Such measuring and monitoring of people traffic is carried out for a number of different applications, for example to assist with the planning of layouts in public spaces or shops, or for targeting potential customers though advertising campaigns in a particular location. Out- of-home (OOH) advertising comprises various types of advertising media that people are exposed to when not at home, such as billboards, advertisements on public vehicles, street furniture advertisements, and so on. Footfall techniques are used by the owners of out-of-home media to measure the audience of their advertisements in order to determine the value of their inventory and to determine the most valuable locations to place their media. The spending on out-of-home advertising in 2008 was estimated as 29 billion USD, and an estimated 145 million USD was spent by media owners on audience measurements.

Current audience measurements are often taken manually by researchers visiting particular locations and counting people. Known automated techniques involve the use of either camera or sensor based technologies. Footfall measurements using camera or sensor based technologies suffer from the disadvantage of requiring the object to be in the line of sight of the measuring device. In addition, multiple or simultaneous crossing by the same object in the location area cannot be uniquely measured in a camera or sensor based system. Measurement of footfall using cameras also suffers from lighting related problems, such as being unable to provide monitoring in low light conditions or darkness.

Camera or sensor based monitoring is inherently costly to perform because it requires the installation of monitoring equipment or sensors in the area of interest. Furthermore, such monitoring results in only limited data being available to media owners and advertisers. For example, the data only relates to people numbers, without providing any further insight over and above the flow of people traffic in a particular area.

Summary

It is an aim of the present invention to provide a method and apparatus which obviate or reduce at least one or more of the disadvantages mentioned above. According to a first aspect of the present invention there is provided a method for use in a communications network. The method comprises the steps of monitoring a plurality of user devices in a selected location area, and

determining device type information for each of the user devices being monitored in the location area. The user devices are classified according to their device type information, and the result of this classifying step used to provide a distribution profile of the types of user devices in the location area.

The invention has the advantage of enabling the types of user device in a location area to be determined, rather than merely the number of people in a location area. This information can then be used for various applications, such as targeted advertising based on the type and/or brand of phones that people are using. Furthernnore, in one application the embodiments of the invention can be used to provide automated social class modeling of footfall, based on a distribution profile of the different types of user devices in a location area. This has the advantage of avoiding the need to perform social class modelling of footfall using surveys or questionnaires answered by visitors to a particular area.

According to another aspect of the present invention, there is provided a network node comprising a location monitor configured to monitor a plurality of user devices in a selected location area, and a processor adapted to determine device type information for each of the user devices being monitored by the location monitor. The processor is further adapted to classify the user devices according to their device type information, and provide a distribution profile of the types of user devices in the location area based on the result of the classifying process.

Brief description of the drawings

For a better understanding of the present invention, and to show more clearly how it may be carried into effect, reference will now be made, by way of example only, to the following drawings in which:

Figure 1 shows a typical network;

Figure 2 shows the steps performed by a method according to a first

embodiment of the invention;

Figure 3 shows a node according to an embodiment of the invention;

Figure 4 shows a node according to another embodiment of the present invention, illustrating an example application; and Figure 5 is a flow chart illustrating the steps performed by the embodiment of Figure 4.

Detailed description

Figure 1 shows an example of a communications network with which

embodiments of the present invention may be used. The example shows three adjoining cells 101 a, 101 b and 101 c, each served by a respective base station 103a, 103b and 103c. The network may also comprise one or more pico-cells or femto-cells (not shown). Various user devices 105 are shown as being located within the cells 101 a to 101 c. A plurality of user devices 105 are also shown within a location area 107. Embodiments of the present invention are concerned with providing a distribution profile of the types of user devices within a location area 107, as will be explained in further detail below. Figure 2 shows the steps performed by an embodiment of the invention. In step 201 a plurality of user devices in a selected location area 107 are monitored. Information relating to the device type is then determined for each of the user devices being monitored in the location area, step 203. In step 205 the user devices are then classified according to the device type information. The result of the classifying step 205 is then used to provide a distribution profile of the types of user devices in the location area.

It is noted that the location area may be selected in any manner. For example, the location area may be chosen or selected by a user or administrator of a monitoring system. Alternatively, the location area may be predetermined or selected in advance, according to some other requirement or criteria. The selected location area may comprise any form of area where an analysis needs to take place. For example, the location area may correspond to a shopping area, a sporting arena or event, an office, a public highway, and so on. The selected location area can be of any size or shape. The plurality of user devices may be monitored using known techniques for determining which user devices are in a particular location area. For example, the location area can be configured such that a telecommunications network can determine which user devices are within the location area, based on standard information used by a telecommunications network to monitor the location of user devices. Current technology exists for identifying the movement of a mobile device into and out of a geographical area. An area might be configured, for example, by identifying the cell-ID of the network that is being served in that area. Alternatively, an area can be defined using latitude and longitude coordinates of a map to define a polygon. Technology such as cell-ID, for example Cell Global Identity plus Timing Advance (CGI+TA), can be used to identify the presence of user devices inside the location area (geographical area). The cells can be of any size including, but not limited to, micro, macro, pico, femto or other types of cell. It is noted that both terminal based solutions and network based solutions for determining the position of a user device in a location area are intended to be covered by the embodiments of the invention.

According to one embodiment, the device type information of a user device is determined using an identification label associated with the user device. For example, the identification label may comprise a portion of an international mobile equipment identity (IMEI) number of a user device. In one embodiment the device type information is obtained in response to sending a request to a network node. Alternatively, the device type information is obtained in response to a network node sending an alert when a user device enters the selected location area. The portion of the IMEI may be a portion that is freely available to network operators or users, for example, without requiring any special privileges. This enables the monitoring to be performed anonymously.

The device type information retrieved for each of the user devices being monitored in the location area may comprises any one or more of the following: a brand of the user device;

a model of the user device;

a type of operating system used by the user device (for example Android, iOS, Windows Mobile, Symbian, etc.);

- a technical specification of the user device, including a technical specification comprising any one or more of a screen resolution, memory size, processor speed;

a form factor of a user device, including a form factor selected from one or more of a candy-bar type phone, flip type phone, smart phone, tablet, laptop, dongle, computer pad, vehicle;

a retail price of the user device.

The information above may be acquired entirely from the information gathered from the network, or alternatively at least some of the information may be acquired based partly on information gathered from the network, and partly from information gathered from a separate source, such as a separate database. For example, in one embodiment the brand/model information is obtained from the IMEI data, with the type of operating system for that brand/model, or the retail price of that brand or model, for example, retrieved from a separate database.

The user devices can therefore be classified according to any one or more of these criteria.

The classified information is used to provide a distribution profile of the types of user devices in the location area, which can then be used to perform various applications. In other words, the distribution profile of user devices in the location area can be used to perform a further operation in the network. For example, a monitoring system can be configured to monitor the number of android phones visiting a particular location area, and this information used to target which area is best suited to receive advertisements relating to android phones. The advertisements may be conventional physical advertisements which are placed at the location area (for example traditional billboard), or electronic (digital) advertisements which can be updated automatically in response to the distribution profile of user devices in the area being monitored. For example, if a large number of people descend on a particular location, with the majority of those people having android phones, then the advertisements in that area could be changed automatically to target users of android phones. As another example, if the majority of user devices relate to phones of a particular brand, the advertising information could be changed automatically to show accessories for that brand of phone.

According to another application, a shop or restaurant uses a small cell (for example a pico-cell or a femto-cell) to form a distribution profile of the types of user devices carried into the shop or restaurant. This application is particularly useful for an electronics or gadget store, or a phone-accessory shop, whereby the types of user devices in the store can be used to provide targeted advertising.

Embodiments of the invention may also be used to automatically communicate with a particular classification of user devices, for example a particular type of phone, or a particular type of device in the location area.

According to one embodiment of the invention, the distribution profile is used to automatically perform social class modeling of footfall, based on the type of user devices identified in a particular location area. This may be used where there is a correlation between device class and social class of the device holder. This correlation may be stronger in some geographical regions than others. As mentioned in the background section, a social class model of footfall is generally obtained through a survey or questionnaire answered by visitors, or by manual passive observation of visitors and their belongings such as dress and accessories. This embodiment of the invention therefore has the advantage of allowing anonymous social classification to be carried out automatically, based on the classification of user devices in a given location area.

According to another embodiment, a functional model is provided for mapping device types with a plurality of events, and wherein the distribution profile is used to trigger an event corresponding to the device type having the largest number in the distribution profile. For example, if there are more tablet devices than mobile phones in a given location, an advertising system can be

configured to place advertisements specific to tablet devices, rather than mobile phones. As another example, if the largest number of user devices in a location area corresponds to user devices having android operating systems, the display of an advert for an android application can be automatically triggered in the location area, or some form of application triggered on the user device itself in the location area.

Figure 3 shows a node 301 according to an embodiment of the present invention. The node 301 comprises a location monitor 303 configured to monitor a plurality of user devices in a selected location area. A processor 305 is adapted to determine device type information for each of the user devices being monitored by the location monitor 303. The processor is further adapted to classify the user devices according to their device type information, and provide a distribution profile of the types of user devices in the location area based on the result of the classifying process. Figure 4 shows an embodiment for use in performing automatic social class modeling, the social class modeling based on the type of user devices in a particular location area. The node 401 comprises a Social Model Reporter (SMR) subsystem 403, which is coupled to receive information from a user (shown as communication signal 1 ), the information relating to the monitoring operation to be performed. For example, the received information may define the selected location area (geographical area) relating to where the footfall social model classification is to be performed. The received information can also include time information, such as a time-period for which the footfall social model classification is required. The SMR subsystem 403 interfaces with a Location Alert Client (LAC) subsystem 405 (shown as communication signal 2). The LAC subsystem 405 is configured to register and receive location alerts for a location area. For example, the location alerts may be received from a network entity such as a Network Positioning System 410 (using communication signals 3 and 4).

According to one embodiment the LAC 405 can be configured to automatically receive location alerts for each user device as it enters a selected location area. Alternatively, the LAC 405 may be configured to interrogate one or more network nodes to retrieve information regarding which user devices are within the selected location area.

A Social Model Mapper (SMM) subsystem 407 is configured to store information which can be used to map a user device with a particular social class. For example, the SMM subsystem 407 can be configured to provide information that a particular brand of mobile phone is used by a particular social class of user. The SMM subsystem 407 can be used to provide any functional relationship between a type of user device and a particular feature. The relationship may be quite direct, for example iPhone owners can be correlated with a particular social class. Other correlations are also possible, such as iPhone owners are expected to be interested in iPhone accessories. However, more unexpected correlations are possible, such as owners of iPhones being more likely to buy vegetarian ready meals.

A Data Store (DS) subsystem 409 is provided for storing information gathered by the node 401 . For example, the DS subsystem 409 can be configured to store time-stamped anonymous location alerts and their associated social class. The SMR subsystem 403 is also configured to analyze and provide social class modeling for a given geographical area, for example over a given time-period, from the DS subsystem 409, and output the social class model to a user (shown as communication signal 8).

The embodiment of the invention described above has advantages over conventional techniques in which anonymous social classification is heavily labor intensive. By determining the type of user devices in a selected location area, and then classifying the devices according to their device type to provide a distribution profile, the system is able to automatically (and anonymously) provide a social class model of visitors to a selected location area. As such, the classification of the mobile devices present within a geographical location can be used to create an anonymous social classification of visitors. Figure 5 illustrates the steps performed by another embodiment of the present invention. In step 501 a point of interest is defined. This may involve a user defining a geographical area in which a footfall classification is required (for example a polygon defined using a set of latitude and longitude signals). This step may also comprise the setting of a time-span during which the footfall classification is required (for example a start-timestamp and an end-timestamp). This step may also comprise a Social Model Reporter (SMR) registering a point of interest to a Location Alert Client (LAC), and a LAC registering to a Network Positioning System for location alerts for the point of interest. It is noted, however, that other methods of identifying and selecting a location area or point of interest (and of gathering information about user devices in the location area or point of interest) are also intended to be embraced by the present invention.

In step 503 location alert signals are received for user devices in the location area, including device IDs of the user devices. This may comprise receiving location alerts from a network positioning system. Alternatively, this may involve probing or interrogating one or more network nodes to obtain information about user devices in a location area or point of interest.

In step 505 the device IDs received in step 503 are mapped with a social class data model, and used to create a footfall social model for the point of interest, step 507. The step of mapping the received user device IDs with a social class data model may involve storing anonymous social class coded location alerts into a data store, and analysing data from the data store to create a social model for the point of interest. The footfall social model for the geographical area is provided to a user, and can be used for any one of numerous

applications.

The embodiments of the invention can provide near simultaneous social classification data for multiple visitors and multiple locations with a single solution.

This embodiment is effectively using the reverse of mobile phone design. In other words, phones are usually designed for a particular social class, and here that information is being used in reverse, whereby the brand/model of phone is used to provide social class information of visitors to a particular location.

The embodiments of the invention described above enable an automatic anonymous social class modeling to be provided, utilizing mobile phones connected to the mobile network within a given geographical area of interest. Such a social model of anonymous footfall for a given geographical location is provided without any questionnaire or personal interaction with the subjects.

The embodiments of the invention have the advantage of utilizing existing public network infrastructure, and do not require any specific cameras or sensors. It is noted that the embodiments of the invention are intended to cover the selected location area being configured in any relationship to cells in the communication network. For example, the location area may fall entirely within one cell, cross between two or more cells, encapsulate multiple cells, or any other configuration. It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. The word "comprising" does not exclude the presence of elements or steps other than those listed in a claim, "a" or "an" does not exclude a plurality, and a single processor or other unit may fulfil the functions of several units recited in the claims. Any reference signs in the claims shall not be construed so as to limit their scope.

Claims

1 . A method for use in a communications network, the method comprising the steps of:

monitoring a plurality of user devices in a selected location area; determining device type information for each of the user devices being monitored in the location area;

classifying the user devices according to their device type information; and

using the result of the classifying step to provide a distribution profile of the types of user devices in the location area.

2. A method as claimed in claim 1 , wherein the determining step comprises the step of obtaining the device type information of a user device using an identification label associated with the user device.

3. A method as claimed in claim 2, wherein the identification label comprises a portion of an international mobile equipment identity (IMEI) number of a user device.

4. A method as claimed in claim 2 or 3, wherein the device type information is obtained in response to sending a request to a network node.

5. A method as claimed in claim 2 or 3, wherein the device type information is obtained in response to a network node sending an alert when a user device enters the selected location area.

6. A method as claimed in any one of the preceding claims, wherein the monitoring and determining steps are performed over a selectable period of time.

7. A method as claimed in any one of the preceding claims, wherein the device type information comprises one or more of the following:

a brand of the user device;

- a model of the user device;

a type of operating system used by the user device;

a technical specification of the user device, including a technical specification comprising any one or more of a screen resolution, memory size, processor speed;

- a form factor of a user device, including a form factor selected from one or more of a candy bar, flip-phone, smart-phone, tablet, laptop, dongle, computer pad, vehicle;

a retail price of the user device.

8. A method as claimed in any one of the preceding claims, further comprising the step of modelling the social class of users in the location area based on the distribution profile of the user devices.

9. A method as claimed in any one of the preceding claims, further comprising the step of using the distribution profile of user devices to perform a further operation in the network.

10. A method as claimed in any one of the preceding claims, wherein the distribution profile of user devices is used for any one or more of the following operations:

determining which digital advertisements are to be displayed in the location area;

determining which physical advertisements are to be displayed in the location area;

- determining which advertisements are to be sent to user devices, based on their device type.

1 1 . A method as claimed in any one of the preceding claims, further comprising the step of providing a functional model for mapping device types with a plurality of events, and wherein the distribution profile is used to trigger an event corresponding to the device type having the largest number in the distribution profile.

12. A network node comprising:

a location monitor configured to monitor a plurality of user devices in a selected location area;

a processor adapted to determine device type information for each of the user devices being monitored by the location monitor;

wherein the processor is further adapted to classify the user devices according to their device type information, and provide a distribution profile of the types of user devices in the location area based on the result of the classifying process.

13. A network node as claimed in claim 12, wherein the processor is arranged to determine the device type information of a user device using a portion of an international mobile equipment identity (IMEI) number of a user device.

14. A network node as claimed in claim 12 or 13, wherein the processor is arranged to determine the device type information in response to sending a request to another network node.

15. A network node as claimed in claim 12 or 13, wherein the processor is arranged to determine the device type information in response to receiving an alert from another node, indicating that a user device has entered the selected location area.

16. A network node as claimed in any one of claims 12 to 15, wherein the location monitor and processor are configured to monitor the location area and determine the device type information over a selectable period of time.

17. A network node as claimed in any one of claims 12 to 15, wherein the processor is adapted to model the social class of users of the plurality of user devices according to how the user devices have been classified.

18. A communications network comprising a network node as claimed in any one of claims 12 to 17.