Method and system for dynamic content distribution

Abstract

A method for dynamic content distribution, said method comprising: defining an area of interest (130) over which to perform an analysis, the area of interest (130) being associated with a content delivery device (140); obtaining over at least a timestep, from a plurality of user devices (120), minimization of drive test, MDT, information representing at least a respective positional parameter and a respective device characterization of each user device in the plurality of user devices (120); selecting, based on said respective positional parameter, the user devices (120) located in the area of interest; identifying, based on at least the timestep and the device characterization of the plurality of user devices (120) located in the area of interest (130), at least one subset of user devices (120); determining, based on at least the subset of user devices (120), a content to display; providing, to the content delivery device (140), content based on the determined content to display.

Description

[0001] "Method and System for Dynamic Content Distribution" DESCRIPTION

[0002] Background of the invention

[0003] Field of the invention

[0004] The present invention refers to a system and method for dynamic content distribution. Delivering content at an opportune time is key in many fields. Whether the content is aural or visual and pertaining to marketing and advertising, tourism, transport and urban mobility, or municipal and local governmental notices, being able to deliver the content to certain locations at specific times has many obvious functions.

[0005] With people increasingly opting out of personalized location tracking, the possibility of determining and providing targeted content is diminished, especially for secondary devices, devices not located on one's person. Instead, by utilizing network signals which do not require extra permissions while maintaining explicit user privacy, more targeted content delivery is possible without the need for personalized or more intrusive tracking methods.

[0006] Description of the related art

[0007] Content delivery devices in the form of advertisements, notices, or other publications, are ideally located in areas where the most people with interest and means to interact with the content congregate. In many cases, the content many be dynamically updated by control logic or a control signal.

[0008] Document US 11948170 Bl discloses a method for sending advertisements to digital out of home (DOOH) advertising. This method utilizes a combination of an estimated consumer segment and attributes of the same customer segment with a location to estimate a number of impressions for a given DOOH advertising space.

[0009] Document US 2016 / 0292744 Al discloses a system and method for displaying ads on smart billboards. The method utilizes real-time contextual information to determine the best advertisement to display based on the determined likely audience for a smart billboard.

[0010] As is well known in targeted advertising, being able to deliver tailored content to the individual is more valuable. In common / public areas installations, or otherwise static installations, of digital advertising, this capability is greatly diminished by the inability to target the individuals in the vicinity. In the art, therefore, it is advantageous to bring the same targeted content on personal devices to individuals located in public spaces. Notable attempts in the art to utilize contextual information on the individuals within the vicinity of the content display device are disclosed in the above cited documents. Methods known in the art involve utilizing external information to make assumptions of most probable user segments in a given area. The external information typically comes from different sources of information but it might either be inaccurate, not real-time, or privacy destroying.

[0011] Importantly, the determination of potential individuals in the vicinity of the content delivery device is generally unavailable to services in real time without a previous consent agreement. This limitation is becoming more difficult to obtain and intrusive on the privacy of the individual.

[0012] Ideally therefore, live real-time tracking with an associated profile of an individual should respect and maintain the individual's privacy. The Applicant has observed recent changes to methodologies of sending minimization of drive test, MDT, information to a mobile network that allows for anonymized user information as well as location tracking. The Applicant has explored whether these changes can enable a more robust and private methodology for delivering content that is better targeted to individuals.

[0013] Summary of the invention

[0014] The Applicant has developed a system and associated methodology for dynamic content delivery. The content delivery is governed by certain determinations of individuals located in a defined geographic area and facilitated by location tracking and information provided through the MDT technique anonymized and sent by user devices to the network automatically.

[0015] According to a first aspect, the invention refers to a method for dynamic content distribution.

[0016] Preferably, said method comprises defining an area of interest.

[0017] Preferably, an analysis is to be performed over said area of interest.

[0018] Preferably, the area of interest is associated with a content delivery device.

[0019] Preferably, said method comprises obtaining minimization of drive test, MDT, information.

[0020] Preferably, said minimization of drive test, MDT, information is obtained over at least a timestep.

[0021] Preferably, said minimization of drive test, MDT, information is obtained from a plurality of user devices.

[0022] Preferably, said minimization of drive test, MDT, information represents at least a respective positional parameter of each user device in the plurality of user devices.

[0023] Preferably, said minimization of drive test, MDT, information represents at least a respective device characterization of each user device in the plurality of user devices.

[0024] Preferabily, said content delivery device is other than said user devices.

[0025] Preferably, said method comprises selecting the user devices having a determined spatial relationship with the area of interest.

[0026] Preferably, the user devices having the determined spatial relationship with the area of interest are selected based on said respective positional parameter.

[0027] Preferably, said method comprises identifying at least one subset of user devices. Preferably, said at least one subset of user devices is identified based on at least the timestep.

[0028] Preferably, said at least one subset of user devices is identified based on at least the device identity of the selected user devices.

[0029] Preferably, said method comprises determining a content to display.

[0030] Preferably, said content to display is determined based on at least the subset of user devices.

[0031] Preferably, said method comprises providing, to the content delivery device, content based on the determined content to display.

[0032] According to a second aspect, the invention refers to a system for dynamic content distribution.

[0033] Preferably, said system comprises a computing device.

[0034] Preferably, said computing device comprises a processor.

[0035] Preferably, said computing device comprises a computer readable medium.

[0036] Preferably, said computing device is configured to perform the method according to said first aspect.

[0037] According to one or more of the above aspects, the invention can comprise one or more of the following preferred features.

[0038] Preferably, the obtaining the MDT information occurs over a period of time.

[0039] Preferably, said method further comprises creating an associated location trace with each device in the selected user devices.

[0040] Preferably, said positional parameter includes an estimated orientation for each device in the selected user devices.

[0041] Preferably said estimated orientation is estimated based on said associated location trace.

[0042] Preferably, said positional parameter includes an estimated future trajectory for each device in the plurality of user devices.

[0043] Preferably said estimated future trajectory is estimated based on said associated location trace.

[0044] Preferably, said determination of the content to display is further based on the orientation of each device in the subset of user devices.

[0045] Preferably, said determination of the content to display is further based on the future trajectory of each device in the subset of user devices.

[0046] Preferably, the created associated location trace with each user device is further used to define a method of transport.

[0047] Preferably, the device identity further comprises said method of transport.

[0048] Preferably, said method further comprises collecting said MDT information over time.

[0049] Preferably, said collecting said MDT information over time comprises identifying temporal clusters of user devices which may take the form of hourly, daily, weekly, monthly, seasonally, and / or yearly clusters.

[0050] Preferably, said processor is configured to create an associated location trace with each device in the plurality of user devices.

[0051] Preferably, said positional parameter includes an estimated orientation for each device in the plurality of user devices.

[0052] Preferably, said estimated orientation is estimated based on said associated location trace.

[0053] Preferably, said positional parameter includes an estimated future trajectory for each device in the plurality of user devices.

[0054] Preferably, said estimated future trajectory is estimated based on said associated location trace.

[0055] Preferably, said processor is configured to determine the content to display based on the orientation of each device in the subset of user devices.

[0056] Preferably, said processor is configured to determine the content to display based on the future trajectory of each device in the subset of user devices. Preferably, said processor is configured to use the created associated location trace with each user device to define a method of transport.

[0057] Preferably, the device identity further comprises said method of transport.

[0058] Preferably, said processor is further configured to identify temporal clusters of user devices which may take the form of hourly, daily, weekly, monthly, seasonally, and / or yearly clusters.

[0059] Preferably, said device characterization comprises a device make.

[0060] Preferably, said device characterization comprises a device model.

[0061] Brief description of the drawings

[0062] The exact methodology and construction of the invention is shown in exemplary embodiments and the associated detailed description. To facilitate understanding, the description is provided and written in reference to the non-limiting figure:

[0063] Figure 1 shows a system schematic of the connection between the invention elements and individual user devices.

[0064] Description of embodiments of the present invention

[0065] The terminology used in this description is general and not intended to limit the system and method unduly. In the context of this invention, content may refer to any type of aural and / or visual advertisements, notices, notifications, or the like meant for an audience of individuals in public and / or private spaces. The content delivery device, as may be construed in light of this application, is any device outside of a user device carried by the individuals which is or can be configured to deliver chosen content to individuals.

[0066] With reference made to figure 1, information coming from a cellular network can be used to identify and control the content which is displayed on a content delivery device. The mobile network 110, represented in schematic form by a series of network antennae, provides a mobile network connection between the mobile network 110 and a plurality of user devices 120.

[0067] Of particular interest is the MDT information provided by each user device 120, to the network 110. MDT information is enabled as a feature of the mobile core network and is based upon the replacement of manual network quality mapping with network quality mapping performed automatically as mobile user devices 120 roam across areas covered by the network.

[0068] MDT information may be logged or immediate, referring to the transience and frequency of the signals sent to the network. Logged MDT refers to past MDT information not sent in real-time due to an inactive state of the user devices. Logged MDT information is not a requirement for manufacturers to support and is not available for all user devices. Immediate MDT refers to information sent when user devices are connected to the network and are not in an inactive state. Immediate MDT information is of special importance due to real-time and higher frequency transmission.

[0069] In data packets sent to the Radio Access Network, RAN, the MDT information related to an individual's user device 120 contains several data points used by the network operator to monitor the performance and quality of the network and plan / perform maintenance or other network infrastructure work.

[0070] A positional parameter representing a geolocation of the user device is provided inside the MDT information. The geolocation of the user device is ideally obtained from a global navigation satellite system, GNSS. For example, a GPS system can be used. The geolocation may optionally be computed by other known methods in the art such as radio signal triangulation or inertial navigation if a GNSS signal is unavailable.

[0071] In addition to the positional parameter, the MDT information includes a device characterization of the respective user device 120.

[0072] The device characterization can be indicative of the device belonging to a group and / or category, based on the device's features. For example, hardware / software features of the device can be taken into consideration.

[0073] For example, device's make and / or model can be taken into consideration.

[0074] In an embodiment, the device characterization is in the form of the International Mobile Equipment Identity, IMEI or, with additional information about the software version, IMEISV, to the network 110. This code contains, as a subset, the Type Allocation Code, or TAC which allows for easy identification and extraction of the make and model of the user device. The TAC can be found in the first eight numbers contained in the IMEISV. The IMEI can be composed of 15 digits subdivided into 4 sections: AAAAAA BB CCCCCC D

[0075] "A" represents the Type Approval Code which identifies the manufacturer and model of the user device, "B" represents the Final Assembly Code which identifies the location of assembly of the user device, "C" identifies the serial number of the user device, and "D" is defined as SP (Spare), or CD (Check Digit) reserved to verify the correctness of the IMEI code. The IMEISV has 16 digits instead which removes the "D" digit and instead contains 2 digits which represent the software version of the mobile device. This data is transmitted as part of the MDT information along with the positional parameter to the network, for network use. The Applicant has found that this data can be repurposed for content determination.

[0076] The content may comprise images, videos, audio, or any combination thereof for display to individuals in a public and / or private place. Over a geographical area, a number of content delivery devices 140 may be installed to provide more opportunities for content delivery. The description will focus on a singular content delivery device, but the invention extends to a plethora of such devices. The content delivery device may take the form of a maxi-screen, electronic billboard, or any such addressable and dynamically updatable content delivery device. The content delivery device 140 is other than the user devices 120. Specifically, the content delivery device 140 is typically not a device from which MDT information is obtained and is preferably entirely dedicated to the display of contents. In particular, the content delivery device 140 is preferably not a mobile device and is part of a fixed installation, although it may be connected through the mobile network.

[0077] The dynamic update of content displayed or played on the content delivery device may be updated in real-time according to a control input received from a computer system. The connected system may be characterized by a computer system comprising at least a processor 100a and an associated computer readable medium 100b. The processor 100a is configured to perform a content determination for the content delivery device.

[0078] The content determination takes shape from a first step of defining an area of interest 130. This area of interest 130 is preferably characterized by a certain shape and geographical location. The area of interest 130 is additionally associated with the content delivery device 140. The area of interest 130 may preferably be a location in front of, within audio range of, and / or within the viewing angle of the content delivery device 140. The size of the geographical location may be limited to a small area / square or extend over larger distances; it can include a stretch of road along a highway, for example.

[0079] Once an area of interest 130 has been defined, the content determination procedure begins by obtaining MDT information representing a position and user device information from a plurality of devices over at least one time step. The information obtained can then be filtered, returning only those having a determined spatial relationship with the area of interest 130.

[0080] For example, the position of each user device 120 is compared with the boundaries of the area of interest 130 and, in case such position falls within the boundaries, then the respective MDT information is preferably considered for further processing; otherwise, if the position of a user device 120 falls outside the boundaries, then the respective MDT information is preferably discarded.

[0081] In addition or as an alternative, user devices 120 outside the area of interest 130 can be taken into consideration. For example, user devices 120 in the vicinity of (i.e. within a certain distance from) the area of interest 130 can be taken into account. This allows more sophisticated analysis, based not only on the position of the individuals but also on the trajectories that users follow when approaching and / or leaving the area of interest 130.

[0082] Preferably, obtaining information may also collect MDT information over a series of time steps. MDT information, for example, is provided consistently to the RAN with average intervals of anywhere in the range of around 120 milliseconds to 60 minutes. Utilizing a history of signals, a path tracing may occur. Path tracing may occur utilizing MDT information sent in a single cell area with a constant anonymized (or pseudonymized) ID. In addition or as an alternative, path tracing may occur between cells through the user device identifying information. The low probability with which a device with a specific make, model, software, etc. transits between cell areas allows a historical path trace to be generated. The historical path of an individual user device 120 may provide a vector to calculate additional positional parameters of the associated individual. Possible positional parameters may include past movement, pattern of movement, orientation, future trajectory, method of transport, or the like. For example, trajectories of users can be analyzed according to the technique disclosed in international patent application WO 2022 / 219457 Al, in the name of the same Applicant.

[0083] Given the trajectory and features thereof, it is possible determining whether a certain cluster of user devices 120 (and the individuals belonging the latter) is likely to be, within a certain time, in the area of interest 130 - so as to properly manage the content displayed by the content delivery device 140.

[0084] The device characterization can be extracted from the MDT information, revealing the identifying information for the respective user device 120. The classification of individuals is thus based on said MDT information containing at least the positional parameter and the associated device characterization and defines a subset of user devices 120 most probably being able to view and / or being interested in the content provided to the content delivery device 140.

[0085] The classification may be performed according to any general clustering technique and may be opportunely performed according to a time, a time history, a device make, a device model, a relative position inside of the area of interest, and / or a pattern of movement inside the area of interest or a combination of the same. As said, movements also outside the area of interest 130 but in the vicinity thereof may also be taken into consideration. The classification may be performed utilizing relationships between data points as determined by an algorithm. The classification may be performed by any generic classification or clustering methodology adapted to predict / determine groupings based at least in part on the respective location and device characterization: optionally one of linear regression, logistical regression, decision trees, supervised or unsupervised machine learning, neural networks or the like as is known in the art.

[0086] Additionally, the user device characterization or location may be used in conjunction with external information, i.e. data related to identifying a user not contained inside the MDT information, to develop / create a classification of said user. The classification of a user may occur, e.g., based on inferences made about the individual associated to each user device. The inferences are based in part on the extracted user device identifying information. Inferences may be made in combination with external sources of information which may include but are not limited to a geographic data, statistics for brand diffusion, wealth rates, and / or combinations of the same or similar. The profile may, as an example, create class connections between more expensive user device brands and a propensity for higher spending, a brand-new user device make and model in a region without said make and model, or any similar relationship or connection between the data points.

[0087] In an embodiment, additional information can be considered, for example regarding the place from which certain user devices 120 come. For example, if a user device comes from an office or a factory, the respective individual is likely to work there, so is likely to live in that zone; if a user device comes from a museum, the respective individual is likely to be a tourist. This may have an impact on the content to be displayed, if and when such devices approach the area of interest 130.

[0088] In an embodiment, additional information can be considered, for example based on a previous learning of people moving behavior. For example, the system may come to learn that every day, at a certain time, a great number of devices moves from one place (e.g. a school, or an arena) and is likely to reach the area of interest 130. This piece of information can be leveraged in order to select / generate proper contents to be delivered through the content delivery device(s) 140.

[0089] Based on the evaluation of the subset of users in an area of interest, a computing device 100 is then able to determine content to display on the content delivery device. The computing device 100 is then able to provide the content to the content delivery device 140. Fittingly, the resulting content displayed or played on the content delivery device is adapted or tailored to the individuals chosen in the subset of user devices 120.

[0090] Tailoring the delivered content may be performed a number of different ways in implementable embodiments. In a particular embodiment, the computing device 100, comprised of the processor 100a and the computer readable medium 100b, is configured to select from a plurality of content stored in the computer readable medium 100b. Optionally, the plurality of content may be stored or selected from additional external sources.

[0091] The computing device 100 comprising the processor 100a and the computer readable medium 100b is not intended to be limited. Optionally, the same processes controlled by the computing device 100 may optionally be split over a number of computers providing access, or services to a main computing device 100. This may opportunely take the form of a server, a plurality of servers, or other assembly of network devices able to carry out the analyses.

[0092] Of particular interest is the capability of providing third parties the opportunity to leverage real-time user device subsets to deliver content. In this embodiment, the computing device 100 is further configured to transmit information about a subset of user devices to the third party. Utilizing the information provided by the computing device, third parties may be configured to interface directly with the content delivery device 140.

Claims

CLAIMS1. A method for dynamic content distribution, said method comprising: defining an area of interest (130) over which to perform an analysis, the area of interest (130) being associated with a content delivery device (140); obtaining over at least a timestep, from a plurality of user devices (120), minimization of drive test, MDT, information representing at least a respective positional parameter and a respective device characterization of each user device in the plurality of user devices (120), wherein said content delivery device (140) is other than said user devices (120); selecting, based on said respective positional parameter, the user devices (120) having a determined spatial relationship with the area of interest (130); determining, based on at least the timestep and the device characterization of the selected user devices (120), a content to display; and providing, to the content delivery device (140), content based on the determined content to display.

2. The method according to claim 1 wherein the determining content to display comprises: identifying, based on at least the timestep and the device characterization of the selected user devices (120), at least one subset of user devices (120); and determining, based on at least the subset of user devices (120), a content to display.

3. The method according to claim 2 wherein the obtaining the MDTinformation occurs over a period of time, wherein the method further comprises creating an associated location trace with each device in the selected user devices (120).

4. The method according to claim 2 or 3 wherein said positional parameter includes an estimated orientation and / or future trajectory for each device in the selected user devices (120) estimated based on said associated location trace.

5. The method according to claim 4, wherein said determination of the content to display is further based on the orientation and / or future trajectory of each device in the subset of user devices (120).

6. The method according to claim 3 wherein the created associated location trace with each user device (120) is further used to identify a method of transport, and wherein the device identity further comprises said method of transport.

7. The method according to anyone of the preceding claims further comprising collecting said MDT information over time, identifying temporal clusters of user devices (120) which may take the form of hourly, daily, weekly, monthly, seasonally or yearly clusters.

8. The method according to anyone of the preceding claims, wherein said device characterization comprises a device make or a device model.

9. A system for dynamic content distribution comprising: a computing device (100) comprising a processor (100a) and a computer readable medium (100b), said computing device (100) being configured toperform the method according to claim 1.

10. The system according to claim 9, wherein said computing device (100) is further configured to create an associated location trace with each device in the plurality of user devices (120).

11. The system according to claim 9 or 10, wherein said positional parameter includes an estimated orientation and / or future trajectory for each device in the plurality of user devices (120) estimated based on said associated location trace.

12. The system according to claim 11, wherein said computing device (100) is further configured to determine the content to display based on the orientation and / or future trajectory of each device in the subset of user devices (120).

13. The system according to claim 10, wherein said computing device (100) is further configured to use the created associated location trace with each user device (120) to identify a method of transport, and wherein the device identity further comprises said method of transport.

14. The system according to anyone of claims 9-13, wherein computing device (100) is further configured to identify temporal clusters of user devices (120) which may take the form of hourly, daily, weekly, monthly, seasonally or yearly clusters.

15. The system according to anyone of claims 9-14, wherein said device characterization comprises a device make or a device model.

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