Patent Publication Number: US-9904938-B2

Title: Methods and systems to determine consumer locations based on navigational voice cues

Description:
RELATED APPLICATIONS 
     This patent arises from a continuation of U.S. patent application Ser. No. 14/473,318, which was filed on Aug. 29, 2014 and is incorporated herein by reference in its entirety. 
    
    
     FIELD OF THE DISCLOSURE 
     This disclosure relates generally to consumer monitoring, and, more particularly, to methods and systems to determine consumer locations based on navigational voice cues. 
     BACKGROUND 
     With the development of the global positioning system (GPS), many individuals rely on navigation systems to direct them while driving. Such navigation systems may be built directly into a vehicle, may be manufactured as a standalone device, or may be incorporated into a multifunction device (e.g., a smartphone). Some navigation systems provide voiceover instructions or verbal cues to guide individuals on when and where to turn, and on what roads, to arrive at a pre-selected destination. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram of an example system shown in an example environment in which the teachings disclosed herein may be implemented. 
         FIG. 2  is a block diagram of an example implementation of the example central facility of  FIG. 1 . 
         FIG. 3  is a block diagram of an example implementation of the example meter of  FIG. 1 . 
         FIG. 4  is a flowchart representative of example machine readable instructions that may be executed to implement the example central facility of  FIGS. 1 and/or 2 . 
         FIG. 5  is a flowchart representative of example machine readable instructions that may be executed to implement the example central facility of  FIGS. 1 and/or 2 . 
         FIG. 6  is a block diagram of an example processor platform capable of executing the example machine readable instructions of  FIGS. 4 and/or 5  to implement the example central facility of  FIGS. 1 and/or 3 . 
     
    
    
     DETAILED DESCRIPTION 
     Many businesses (e.g., manufacturers, retailers, etc.) and advertisers try to increase demand for their products or services by influencing the behavior of target consumer segments through advertising campaigns. Often businesses will try to improve their marketing efforts by targeting specific consumer segments based on one or more demographic characteristics. In some instances, the success of a particular advertisement to which consumers are exposed may depend on the circumstances of the consumers and the timing of the exposure to the advertisement. For example, if consumers are located in proximity to a business and/or are heading towards the business at the time that the consumers are exposed to an advertisement or promotional offer from the business, the consumers may be more likely to favorably respond to the advertisement. Accordingly, there is a desire to determine where potential consumers are located and/or heading and to provide them with advertisements that are associated with their location in substantially real time. 
     Navigation systems that use GPS are widely used by many individuals to enable them to determine where they are located and/or to provide directions to locations where they want to go. Frequently, such directions are provided in the form of verbal instructions or voice cues that identify when and where a driver is to turn to arrive at a desired destination. For example, navigational voice cues typically identify upcoming points along a route (e.g., intersections) at which a driver is to take some action (e.g., turn, continuing along the current road, etc.). More particularly, navigational voice cues often give navigation information corresponding to one or more of (1) a distance to the next route point (e.g., intersection or road) where a driver is to perform a turn or take some other action (e.g., keep right at a fork, exit on a ramp, continue on the current road, etc.), (2) the direction of the action to be taken (e.g., turn left, veer right, head west, etc.), and (3) the name of the route point (e.g., intersection or road) where the action is taken. If a driver passes a route point (e.g., an intersection) without following the verbal directions or takes some turn before reaching the verbally identified route point, the navigation system will typically determine a new route to the ultimate destination (e.g., a destination entered into the navigation system as the final location and/or waypoint to be reached). To signal the change of route, many navigation systems provide a voice cue indicating that the route to the ultimate destination is being recalculated. Once the navigation system determines the new route, another voice cue may be provided that defines the new directions (e.g., identifies the next action to take and/or an upcoming route point where an action is to be taken). 
     As used herein, the term “road” is hereby defined to include any road, street, highway, freeway, avenue, boulevard, path, route, expressway, toll way, on ramp, off ramp, alleyway, and/or other passageway designated for vehicular travel. A road will typically be identified in an up to date database of a navigation system. As used herein, the term “intersection” is hereby defined to include any point in a road at which a vehicle may take more than one route (e.g., two or more cross-streets, an off-ramp, an on-ramp, etc.) and/or where a road changes name or direction such that a navigational voice cue might be given. Thus, as used herein, references to an intersection necessarily involve reference to at least one road. Further, while “intersection” includes a point where two roads cross, the term also includes locations where a single road may fork such that a vehicle can continue straight or veer to the left or right (e.g., an off ramp from a main road). Furthermore, “intersection” includes the location where a name of a single road changes to a different name (whether or not there is a physical change in the road). 
     Examples disclosed herein rely on the route points (e.g., intersections, roads, etc.) and/or other navigation information designated in the navigational voice cues to determine the location of a potential consumer and/or the anticipated location of the consumer based on the navigational directions provided by the navigation system. Using this location information, advertisements that are targeted for a particular area can be provided to the consumer when the location and/or anticipated location of the consumer falls within the target area for the advertisement. In this manner, a business is able to provide an advertisement promoting a good or service to a consumer when the consumer is in the area and the consumer is able to learn of the promotional offer(s) when in the area. Furthermore, examples disclosed herein impose little intrusion on the privacy interests of the consumer because the consumer&#39;s location cannot be precisely pinpointed as it would be if the location was determined directly through GPS tracking. Examples disclosed herein determine location based on navigational voice cues and, thus, only approximate the location of consumer(s) with periodic updates. Accordingly, consumer(s) may be more willing to participate in such a marketing scheme to be tracked in this manner. 
     Additionally or alternatively, some examples disclosed herein rely on the route points (e.g., intersections, roads, and/or other navigation information designated in the navigational voice cues to determine the travel path followed by a potential consumer. Using this information, outdoor advertisement(s) (e.g., billboards) that are located at a known location can be compared to the travel path of the consumer to determine whether the consumer was exposed to the outdoor advertisement(s). In some examples, the exposure metrics from multiple consumers may be aggregated to estimate a reach of the outdoor advertisement(s) to inform business(es) of the benefit of outdoor advertisement marketing campaign(s). 
     Example methods disclosed herein include identifying, with a processor, a route point designated by a navigational voice cue output by a navigation system providing directions to an operator of a vehicle. Example methods also include determining, with the processor, at least one of a location or an anticipated location of an occupant of the vehicle based on the route point. 
     Example systems disclosed herein include an interface to receive in-vehicle audio data corresponding to audio output by a navigation system directing a user within a vehicle. The in-vehicle audio data includes a navigational voice cue. Example systems also include a speech analyzer to identify a route point from the navigational voice cue. Example systems further include a location determiner to determine at least one of a location or an anticipated location of the user based on the route point. 
       FIG. 1  is a diagram of an example system shown in an example environment of use. As shown in the illustrated example, a person  102  is driving in a vehicle  104 . In some examples, the person  102  is the driver of the vehicle  104 . In other examples, the person  102  is a passenger in the vehicle  104 . In some examples, the person  102  is a potential consumer of goods or services provided by one or more businesses  118 . As such, the business(es)  118  may desire to reach out to the person  102  through an advertisement and/or an advertising campaign (e.g., multiple advertisements presented over time) to try and influence the person  102  to purchase one or more goods and/or services. The person  102  may desire to be made aware of promotional offers or sales from the business(es)  118  to take advantage of the good(s) and/or service(s) being offered for sale. Additionally or alternatively, the business(es)  118  may desire to monitor or track the behavior of the person  102  to assess the effectiveness and/or reach of particular outdoor advertisement(s). As such, in some examples, the person  102  is a panelist having consented to having their location being tracked or monitored by a data collection entity  116 . Panelists are users registered on panels maintained by a research entity (e.g., an audience measurement company, an advertising entity, etc.) that owns and/or operates the data collecting facility  114 . In some examples, the data collection entity  116  may be an audience measurement entity cooperating with an advertising entity. Alternatively, in some examples, the entity  116  may be an advertising entity. In some examples, as part of the process for people to become a panelist, they provide demographic information and/or other personal information (e.g., preferences, interests, etc.) to the data collection entity  116 . 
     In the illustrated example of  FIG. 1 , an example navigation system  106  is located within the vehicle  104 . In some examples, the navigation system  106  is implemented using the global position system (GPS) to determine the location of the navigation system  106  and provide directions to navigate the vehicle  104  to some desired location. In some examples, the navigation system  106  is manufactured with and/or installed (e.g., affixed) in the vehicle  104 . In some examples, the navigation system  106  is a standalone portable device that may be placed inside the vehicle  104 . In some examples, the navigation system  106  is incorporated into a multifunction portable device, such as a smartphone. In the illustrated example, the navigation system  106  includes a speaker  108  through which navigational voice prompts or cues  110  are emitted to provide audible directions to a driver (e.g., the person  102 ) of the vehicle  104 . 
     In the illustrated example of  FIG. 1 , a meter  112  is disposed within the vehicle  104  to detect and/or capture audible noises inside the vehicle (referred to herein as in-vehicle audio data) that includes the navigational voice cues  110 . As used herein, in-vehicle audio data refers to sounds that may be heard within the cabin of the vehicle where the driver is present during vehicular operation. In some examples, the navigational voice cues  110  are detected and analyzed to generate navigation information indicative of the location and route taken by the vehicle  104 . In some examples, the meter  112  is adapted from a portable metering device as described in U.S. Provisional Application Ser. No. 60/511,859, U.S. Provisional Application Ser. No. 60/578,196; U.S. Pat. No. 7,587,732; U.S. Pat. No. 8,539,527; U.S. Pat. No. 8,806,535; and U.S. patent application Ser. No. 14/448,715; all of which are hereby incorporated herein by reference in their entireties. In some examples, the meter  112  is adapted from a metering device as described in U.S. Pat. No. 8,549,552, and U.S. Re-Issue patent application Ser. No. 14/260,890, which are hereby incorporated herein by reference in their entireties. Briefly, such an example meter detects media to monitor exposure of the occupants of the vehicle  104  to media for purposes of audience measurement. In such examples, the detected media may be audio media playing over the radio, audio media playing via a stereo in the vehicle  104 , audio-visual media playing via a video player in the vehicle, and/or any other type of media inside of a vehicle (e.g., media presented via a laptop computer, a smartphone, and/or a tablet such as an iPad™). In some examples, the meter  112  detects and identifies the media playing in the vehicle  104  by detecting watermarks and/or signatures associated with the media. 
     Audio watermarking is a technique used to identify media such as television broadcasts, radio broadcasts, advertisements (television and/or radio), downloaded media, streaming media, prepackaged media, etc. Existing audio watermarking techniques identify media by embedding and/or otherwise associating one or more audio codes (e.g., one or more watermarks), such as media identifying information and/or an identifier that may be mapped to media identifying information, in and/or with an audio and/or video component. In some examples, the audio or video component is selected to have a signal characteristic sufficient to hide the watermark. As used herein, the terms “code” or “watermark” are used interchangeably and are defined to mean any identification information (e.g., an identifier) that may be transmitted with, inserted, and/or embedded in the audio or video of media (e.g., a program or advertisement) for the purpose of identifying the media or for another purpose such as tuning (e.g., a packet identifying header). As used herein “media” refers to audio and/or visual (still or moving) content and/or advertisements. To identify watermarked media, the watermark(s) are extracted and used to access a table of reference watermarks that are mapped to media identifying information. 
     Unlike media monitoring techniques based on codes and/or watermarks included with and/or embedded in the monitored media, fingerprint or signature-based media monitoring techniques generally use one or more inherent characteristics of the monitored media during a monitoring time interval to generate a substantially unique proxy for the media. Such a proxy is referred to as a signature or fingerprint, and can take any form (e.g., a series of digital values, a waveform, etc.) representative of any aspect(s) of the media signal(s) (e.g., the audio and/or video signals forming the media presentation being monitored). A good signature is one that is repeatable when processing the same media presentation, but that is unique relative to other (e.g., different) presentations of other (e.g., different) media. Accordingly, the term “fingerprint” and “signature” are used interchangeably herein and are defined herein to mean a proxy for identifying media that is generated from one or more inherent characteristics of the media. 
     Signature-based media monitoring generally involves determining (e.g., generating and/or collecting) signature(s) representative of a media signal (e.g., an audio signal and/or a video signal) output by a monitored media device and comparing the monitored signature(s) to one or more reference signatures corresponding to known (e.g., reference) media sources. Various comparison criteria, such as a cross-correlation value, a Hamming distance, etc., can be evaluated to determine whether a monitored signature matches a particular reference signature. When a match between the monitored signature and one of the reference signatures is found, the monitored media can be identified as corresponding to the particular reference media represented by the reference signature that matched the monitored signature. Because attributes, such as an identifier of the media, a presentation time, a broadcast channel, etc., are collected for the reference signature, these attributes may then be associated with the monitored media whose monitored signature matched the reference signature. Example systems for identifying media based on codes and/or signatures are long known and were first disclosed in Thomas, U.S. Pat. No. 5,481,294, which is hereby incorporated by reference in its entirety. 
     In some examples, in addition to being able to capture codes and/or signatures for media exposure monitoring, the meter  112  is also structured to capture, detect, and/or identify the navigational voice cues  110  generated by the navigation system  106  as described more fully below. However, in some other examples, the meter  112  is constructed to capture, detect, and/or identify the navigational voice cues  110  without having the functionality to monitor audience exposure to media as described above. In some examples, the meter  112  collects the in-vehicle audio data (including the navigational voice cues  110 ) and transmits the data to a central facility  114  of a data collection entity  116  without processing and/or specifically identifying navigation information based on the directions provided within the navigational voice cues  110 . In such examples, the analysis and processing is performed by the central facility  114 . In other examples, the meter  112  processes and analyzes the in-vehicle audio data internally so as to reduce the amount of data transmitted to the central facility  114 . In some examples, the processing and analysis of the in-vehicle audio data is shared between both the meter  112  and the central facility  114 . 
     By capturing and identifying the navigational voice cues  110  present in the in-vehicle audio, the general location of the vehicle  104  can be determined. In particular, as successive points of the route identified by the navigation system  106  are verbally articulated, captured by the meter  112 , and subsequently analyzed, the approximate location of the vehicle  104  can be determined. In some examples, the location of the vehicle  104  is determined in substantially real time. In some examples, the meter  112  monitors the navigational voice cues  110  to determine a future or anticipated location of the vehicle  104  (e.g., based on an upcoming route point identified by the navigational voice cues  110 ). Further, by connecting successive points of the route identified by the navigational voice cues  110  in a series, the route taken by the vehicle  104  through the navigated trip can be recreated via an interpolation method. 
     In some examples, a particular point on a route (e.g., an intersection (or the road associated therewith)) identified by a voice cue  110  may have a relatively generic or common name. For example, the navigational directions may indicate that a driver is to turn left on to Third Avenue in 0.6 miles. Many cities have a Third Avenue such that the particular city cannot be directly known from the navigational voice cue  110 . However, in some examples, this obstacle is overcome by storing a series of navigational voice cues  110  over time. By connecting multiple route points (e.g., intersections) identified on the route of the vehicle  104 , the cities that have each of the roads identified and that intersect in the same manner as provided by the navigation system  106  can be narrowed down via a process of elimination until the particular city is identified. In other examples, the navigational voice cues  110  may include embedded audio codes or watermarks that identify the particular city in which the vehicle  104  is located. In such examples, the meter  112  can extract the code(s) and identify the city by comparing the code(s) to a reference table. In some examples, the person  102  may manually designate the city where the vehicle  104  is located by entering such as an input into a user interface on the meter  112 . Using any of the above techniques, the location of the vehicle at particular points in time as well as the route traveled by the vehicle  104  can be determined, even when some of the navigational voice cues  110  identify generically named roads. 
     In some examples, the meter  112  also collects information identifying the occupants of the vehicle  104  (referred to herein as vehicle occupant data) for reporting to the central facility  114  of the data collection entity  116  for analysis and/or compilation with the navigation information determined from the in-vehicle audio data. In some examples, the vehicle occupant data is collected through a login or input in the user interface of the meter  112  by the occupants to indicate their presence in the vehicle. In some examples, the vehicle occupant data indicates a number of occupants in the vehicle  104 . In some examples, the vehicle occupant data indicates certain demographic characteristics of the occupants and/or uniquely identifies the occupants. For example, if the person  102  and/or other occupants are consenting panelists, their previously collected demographics may be accessed when they login with their unique login credentials via the meter  112 . 
     The in-vehicle audio data (from which the navigation information is obtained), the vehicle occupant data, and any other data collected by and/or transmitted from the meter  112  to the central facility  114  are collectively referred to herein as meter data. The navigation information determined from the voice cues  110  captured by the meter  112  may be used in a variety of beneficial ways. In some disclosed examples, the navigation information is used to locate the vehicle (and the person  102 ) to provide geographically targeted advertisements or promotional information to the person  102  associated with business(es) located in the vicinity of the person  102 . For example, the business(es)  118  of  FIG. 1  may register with the data collection entity  116  and provide advertisements or promotional offers for distribution within one or more particular geographic regions or target areas. In some examples, the target area(s) correspond to all roads and/or intersections within a threshold distance (e.g., ½ mile, 1 mile, 2 miles, etc.) of particular locations (e.g., the address of the business(es)). In some examples, the target area(s) correspond to specifically identified intersections, roads, and/or portions of roads (e.g., the road(s) on which the business(es) are located and/or the surrounding roads and/or intersections). In some examples, the target area(s) are bounded areas defined by certain roads or other geographic markers. The target area(s) may additionally or alternatively be defined in any other suitable matter. In some examples, the data collection entity  116  compares the navigation information collected via the navigational voice cues  110  in the vehicle  104  with the target areas specified by the business(es)  118  to determine whether the vehicle  104  (and, thus, the person  102 ) is located within or near the target area and/or anticipated to enter the target area. If the data collection entity  116  determines that the person  102  has entered or is anticipated to enter a target area, the data collection entity  116  may provide the advertisement or promotional information associated with the target area to the person  102 . In some examples, the data collection entity  116  is not associated with delivering advertisements. Instead, the data collection entity provides the location information and identifier(s) of the person(s) in the vehicle to the business(es)  118  who use that information to deliver advertisements, coupons, or other content to the person(s). The delivered advertisements, coupons, or other content may be personalized and may be delivered via any suitable medium (e.g., text, email, broadcast media, a personalized billboard changed in real time, etc.). Any of these media can be used irrespective of whether the data collection entity  116 , the business(es)  118 , or both are delivering the advertisements, coupons, and/or other content to the person(s) in the vehicle  104 . 
     In some examples, a point on a route (e.g., an intersection) identified by the navigational voice cue  110  may be located within a target area while the vehicle  104  is still a significant distance outside from the target area. For example, the navigation system  106  may identify the next turn in the voice guided directions to be at a route point (e.g., an intersection) that is 15 miles down the road the vehicle  104  is currently driving down (i.e., 15 miles from the vehicle). In such examples, even though the person  102  may be well outside a target area (e.g., a half mile radius circle that includes the identified route point), the data collection entity  116  and/or the business(es)  118  may nevertheless provide the advertisement associated with the target area to the person  102  because the navigational voice cues  110  indicate the vehicle  104  transporting the person  102  is at least heading in the direction of the target area. That is, the anticipated (e.g., future) location of the vehicle  104  is expected to be within the target area. 
     In some examples, the driver of the vehicle  104  may disregard the navigational directions and/or independently change course prior to reaching an identified route point (e.g., intersection) in a target area such that the navigation system  106  recalculates a new route that avoids the target area. In some such examples, the data collection entity  116  and/or the business(es)  118  may nevertheless provide the advertisement associated with the target area because the navigational voice cues  110  indicated that the person  102  was at least approaching the target area and, thus, will likely pass nearby (e.g., within a threshold distance of the target area. Furthermore, in some examples, the central facility  114  provides the advertisements in substantially real time as the navigational voice cues  110  are collected and reported by the meter  112 . In such examples, the advertisement may be provided to the person  102  based on the anticipated location of the vehicle  104  before subsequent voice cues  110  indicate a change in the travel path of the vehicle  104 . 
     In some examples, the geographically targeted advertisements are provided through a text message and/or email to the person  102  that may be accessed by a mobile device  120  (e.g., smartphone) of the person  102 . In some examples, the text message and/or email directly contains the advertisement associated with the target area. Additionally or alternatively, in some examples, the text message and/or email contains a link to a website where the promotional information is located. In some such examples, the business(es)  118  may distribute and/or be able to access and/or edit the website to dynamically update the advertisement in substantially real-time. For example, a deli may have a surplus of certain food products that need to be sold. Accordingly, the deli may designate a target area within a one mile radius of its location and upload information onto the website concerning a promotional sale of the surplus products. If after a certain period of time, the surplus products are sold, the deli may remove the promotional information from the website and/or alter it in other ways based on a response to the promotional sale. 
     In some examples, the data collection entity  116  and/or the business(es)  118  may limit advertisements provided to people within the target area to those corresponding to preferences and/or interests of the people (e.g., based on information they provided when establishing a profile when registering to be tracked as disclosed herein). Similarly, in some examples, the data collection entity  116  and/or the business(es)  118  may limit the people to which an advertisement is provided based on target characteristics (e.g., demographic characteristics) of consumers for which the advertisement is intended as identified by the business(es)  118  associated with the advertisement. 
     In some disclosed examples, the navigation information determined from the voice cues  110  captured by the meter  112  may be used to determine exposure of people to outdoor advertisements (e.g., billboards). For example, the business(es)  118  of  FIG. 1  may register with the data collection entity  116  and provide information indicative of the location of outdoor advertisements for which the business(es)  118  desire exposure metrics. In some such examples, the data collection entity  116  analyzes the navigation information based off of the navigational voice cues  110  to generate or recreate a route or travel path of the vehicle  104 . In some examples, the central facility  114  analyzes the travel path of the vehicle  104  to determine whether the vehicle  104  passed the locations of the outdoor advertisements identified by the business(es)  118 . If the central facility  114  determines that the vehicle  104  did pass an advertisement, then the exposure of the person  102  to that advertisement is counted. In some examples, after determining the travel path of the vehicle, the central facility  114  provides the travel path to the business(es)  118  to analyze against the location of advertisement(s) to determine exposure. 
     In some examples, the data collection entity  116  generates the travel path of the vehicle  104  by connecting successive route points (e.g., intersections) identified by the navigational voice cues  110 . However, in some examples, the vehicle  104  may not follow the navigation directions by either taking an unguided turn before reaching an identified route point (e.g., intersection) or passing the identified route point (e.g., intersection) without taking the appropriate action (e.g., failing to turn in the direction designated or turning when continuing straight was directed). Typically, the navigation system  106  will detect that the vehicle  104  has departed from the designated travel path and, thus, generate a new voice cue indicating the navigation system  106  is recalculating. Accordingly, in some examples, the most recent route point (e.g., intersection) identified before the recalculating navigational voice cue is excluded from the chain of route points (e.g., intersections) connected together to define the travel path of the vehicle  104 . This exclusion would be appropriate if, for example, the announced route point is not reached. In other examples, the most recent route point identified before the recalculating cue is nevertheless included in the chain of route points because it is subsequently determined that the vehicle  104  passed the identified route point but failed to take the appropriate action (e.g., continued straight through an intersection (thereby passing the intersection) rather than turning). 
     In some examples, the exposure of the person  102  to the advertisements is aggregated with exposure information collected from other people participating as panelists in a marketing research study to generate a report indicative of the reach of the advertisement. Additionally or alternatively, in some examples, the data collection entity  116  makes correlations between the advertisement exposure to the panelists and different demographic markets based on the demographic information previously received from the panelists. 
     In some examples, the navigation system  106  is integrated with the mobile device  120  of the person  102 , while the meter  112  is a separate device. Alternatively, in some examples, the meter  112  is integrated with the mobile device  120  while the navigation system  106  is a separate device. In other examples, each of the navigation system  106 , the meter  112 , and the mobile device  120  are separate devices. The advantage of separating the navigation system  106  and the meter  112  is that the meter  112  does not have access to the precise GPS location of the vehicle  104  as determined by the navigation system  106 . It is counterintuitive to determine the location of a vehicle based on navigational voice cues from a navigation system that has necessarily already determined the location of the vehicle. However, whereas the navigation system  106  can effectively pinpoint the location of the vehicle  104  at all times to precisely track the movement of the vehicle  104 , the navigation information determined from the navigational voice cues  110  as disclosed herein is limited to general waypoints or markers on a route of the vehicle  104  corresponding to the intersections or other route points identified by the navigational voice cues  110 . Because the meter  112  cannot precisely locate the vehicle  104  to the same degree as a GPS unit (e.g., the navigation system  106 ), consumers may be more willing to volunteer as panelists realizing that there is less intrusion upon their privacy or concern that their constant whereabouts is known. Further, in some examples, consumers may be given additional incentives to encourage their participation in the location monitoring techniques disclosed herein. 
       FIG. 2  is a block diagram of an example implementation of the example central facility  114  of  FIG. 1 . In the illustrated example, the central facility  114  includes an example communication interface  202 , an example voice cue detector  204 , an example speech analyzer  206 , an example audio code analyzer  208 , an example location determiner  210 , an example travel path determiner  212 , an example target area determiner  214 , an example advertisement identifier  216 , an example website generator  218 , an example exposure analyzer  220 , and example database(s)  222 . In some examples, the advertisement identifier  216 , the website generator  218  is not included and is instead implemented by the business(es)  118 . 
     In the illustrated example of  FIG. 2 , the central facility  114  is provided with the communication interface  202  to receive in-vehicle audio data, vehicle occupant data, and/or any other data transmitted from the meter  112 . In some examples, the communication interface  202  receives similar data from other meters inside other vehicles. In some examples, the in-vehicle audio data includes audio within the vehicle  104  captured by the meter  112 . In some examples, the in-vehicle audio data includes the navigational voice cues  110  generated by the navigation system  106 . In some examples, the navigational voice cues  110  are captured by the meter  112  with other ambient noises (e.g., talking by the in-vehicle occupants, noise from the vehicle radio, etc.) without any processing, filtering, altering, etc. In other examples, the meter  112  may process, filter, or otherwise alter the captured audio before transmission to the central facility  114 . An example manner of identifying spoken comments is described in U.S. Provisional Application Ser. No. 60/511,859, U.S. Provisional Application Ser. No. 60/578,196; U.S. Pat. No. 7,587,732; U.S. Pat. No. 8,539,527; U.S. Pat. No. 8,806,535; and U.S. patent application Ser. No. 14/448,715 mentioned above. This technique can be applied to collecting the voice commands. 
     In some examples, the vehicle occupant data includes information indicative of the occupants in the vehicle  104 . In some examples, the vehicle occupant data indicates a number of occupants in the vehicle  104 . In some examples, the vehicle occupant data identifies certain demographic characteristics associated with the occupants. In some examples, the vehicle occupant data uniquely identifies the occupants of the vehicle (e.g., as particular panelists and/or guests of a panelist). 
     Further, in some examples, the communication interface  202  receives advertising information provided from business(es) (e.g., the business(es)  118  of  FIG. 1 ). In some examples, the advertising information includes advertisements and/or promotional sales information that are targeted to a particular geographic region or target area. In some examples, the advertising information includes a designation of the target area and/or information with which the target area can be determined. In some examples, the advertising information includes a time and/or duration for the promotional offer and/or advertisement associated with the target area. For example, a particular advertisement may be for a discounted lunch at a restaurant with the distribution of the advertisement being specified as between 11:00 am and 1:30 pm. In some examples, the central facility  114  compares the location of the vehicle, as determined in accordance with the teachings disclosed herein, with the target area to identify advertisements to be provided to the occupants of the vehicle when they are within or approaching the corresponding target areas. In other examples, the location data is passed from the central facility  114  to the business(es)  118  and the business(es)  118  attend to selecting and/or sending the ads to the panelists). 
     Additionally or alternatively, in some examples, the communication interface  202  receives advertising information from the business(es)  118  indicative of the locations of outdoor advertisements, such as billboards. In some such examples, the central facility  114  compares the travel path of the vehicle, as determined in accordance with the teachings disclosed herein, with the location(s) of the outdoor advertisement(s) to measure exposure of the vehicle occupants to the advertisement(s) and/or to estimate the reach of the outdoor advertisement(s). 
     In the illustrated example of  FIG. 2 , the central facility  114  is provided with the voice cue detector  204  to analyze the in-vehicle audio data captured by the meter  112  to detect and/or distinguish the navigational voice cues  110  from other ambient noises. Further, the central facility  114 , of the illustrated example, is provided with the speech analyzer  206  to analyze the detected voice cues  110  using speech recognition technology to determine or extract navigation information corresponding to the content of each navigational voice cue. An example manner of implementing the speech analyzer  206  is described in U.S. Provisional Application Ser. No. 60/511,859, U.S. Provisional Application Ser. No. 60/578,196; U.S. Pat. No. 7,587,732; U.S. Pat. No. 8,539,527; U.S. Pat. No. 8,806,535; and U.S. patent application Ser. No. 14/448,715 mentioned above. For example, some voice cues  110  may indicate a current road the vehicle is travelling on, an upcoming road onto which the vehicle is to travel, the intersection at which the car is to change from the current road to the upcoming road, and/or some other route point. Further, in some examples, the voice cues  110  may provide guidance on how the driver is to get from the current road on to the upcoming road (e.g., by turning right, exiting left, staying straight, heading south, etc.). In some examples, the voice cues  110  also indicate a distance from the present location of the vehicle to the next designated route point (e.g., a next intersection). In some examples, the voice cues  110  indicate the navigation system  106  is recalculating a new route for the vehicle  104  because the vehicle has gone the intended route by changing direction before reaching the upcoming route point (e.g., a next intersection) or passing the route point (e.g., a next intersection) without following the guidance provided. 
     In the illustrated example of  FIG. 2 , the central facility  114  is provided with the audio code analyzer  208  to detect and analyze audio codes (e.g., watermarks) embedded in the navigational voice cues  110 . In some examples, the audio codes indicate the city where the vehicle  104  is located. In this manner, the road designated by each voice cue  110  can be uniquely identified even when the name of the road is generic or common with multiple cities. 
     In the illustrated example of  FIG. 2 , the central facility  114  is provided with the location determiner  210  to determine a location of the vehicle  104  based on the navigation information extracted from the navigational voice cues  110  by the speech analyzer  206 . Further, the example central facility  114  is provided with the travel path determiner  212  to determine a travel path or route of the vehicle  104  based on the navigation information. More particularly, in some examples, the location determiner  210  determines the location of the vehicle  104  at a given point in time based on the particular roads (and corresponding route points such as intersections) identified by the navigational voice cues  110 . In some examples, the location determiner  210  determines an anticipated or upcoming location of the vehicle  104  because the precise location of the vehicle between navigational voice cues may not be known but the guided next route point (e.g., intersection) is known. Thus, while the precise location of the vehicle  104  may not be known, the approximate location can be determined as the vehicle  104  reaches each designated route point and a subsequent navigational voice cue is provided by the navigation system  106 . Similarly, in some examples, the travel path determiner  212  determines the travel path of the vehicle  104  by connecting successive route point (e.g., roads and/or intersections) identified by successive navigational voice cues  110  to effectively re-create or chart out the route taken by the vehicle  104 . 
     In some examples, before the specific location and/or travel path of the vehicle  104  can be determined, the current city where the vehicle  104  is located must be determined. In some examples, the city is determined by the audio code analyzer  208  analyzing audio codes as described above. In other examples, the person  102  is prompted to enter or otherwise provide the appropriate city via the meter  112 . The identifier of the city is transmitted to the central facility  114  along with other meter data (e.g., the in-vehicle audio data and/or the vehicle occupant data). In some examples, the city is determined by storing the navigation information extracted from successive navigational voice cues  110  and matching the navigation information to data representing maps of various cities until the city can be uniquely identified based on a process of elimination. In some such examples, an initial estimate for the proper city is made based on recently visited cities as these are the most likely candidates. To this end, an identification of the most recent city visited is stored in the meter  112  as part of the shutdown/power down process of the meter. 
     In some examples, one or more of the navigational voice cues  110  may be a “recalculating” cue. In some such examples, even though the vehicle may no longer be approaching the route point identified in the immediately preceding voice cue, the location determiner  210  nevertheless uses the preceding voice cue as an approximation of the location of the vehicle  104 . The immediately preceding voice cue may still be relied on because the recalculating by the navigation system  106  is likely to derive a new path to the final destination that will pass near, if not guide the vehicle  104  back to, the previously identified route point. Of course, as a subsequent voice cue  110  is provided, the location determiner  210  of the illustrated example will update the location or anticipated location of the vehicle based on the new navigation information. By contrast, in some examples, the route point identified by a voice cue immediately preceding a “recalculating” cue is excluded from the travel path of the vehicle  104  as determined by the travel path determiner  212 . The travel path determiner  212  may exclude or disregard a navigational voice cue immediately preceding a “recalculating” cue because the “recalculating” cue indicates the vehicle  104  has departed from the route indicated by the preceding voice cue. However, in some examples, the navigation system  106  may have provided the “recalculating” cue because the vehicle  104  failed to take the appropriate action at the designated route point (e.g., failed to turn at a designated intersection) but nevertheless passed through the route point. Accordingly, in some examples, the travel path determiner  212  analyzes navigation information from subsequent navigational voice cues  110  before determining whether to include or omit the route point identified before the “recalculating” cue as part of the travel path of the vehicle  104 . Such analysis may use interpolation or other techniques to determine whether the route point (e.g., intersection) was, in fact, passed. 
     For purposes of explanation, the following is an example series of navigational voice cues captured by the meter  112  of the illustrated example and transmitted to the central facility  114 :
         (1) “Head west on 12th Street”   (2) “In 1.6 miles, turn right onto Forest Avenue”   (3) “In 8.1 miles, turn right onto Benton Street”   (4) “Recalculating”   (5) “In 0.5 miles, turn left onto Jules Avenue”       

     In the above example, the first navigational voice cue identifies a direction (West) and a street (12th Street). Many cities have a 12th Street such that the particular city cannot be determined in this example based solely on the voice cue unless the city is identified through an audio code detected via the audio code analyzer  208  and/or is input by the person  102  (e.g., by specifying the city name, by entering the city name into the meter  112  via an input device, etc.). Further, even if the city is known, the specific location of the vehicle  104  may not be known because the first voice cue does not designate where along 12th Street the vehicle  104  is located. However, the second navigational voice cue identifies Forest Avenue as an upcoming intersecting road, thereby identifying a first route point (e.g., intersection) where the vehicle  104  is to turn right. As a result, the location determiner  210  may determine the location of the vehicle  104  at the time of the second voice cue as approximately 1.6 miles east of the intersection of Forest Avenue and 12th Street. Furthermore, the location determiner  210  may determine that a future or anticipated location of the vehicle  104  is at the designated route point (e.g., intersection). The time at which this is expected to occur may be determined based on the 1.6 mile instruction, the known speed limit of 12th Street, and/or a current traffic report. The travel path determiner  212  may begin generating the travel path by defining a line beginning 1.6 miles east of Forest Avenue on 12 th  Street and moving in a direction towards the intersection. The line may not be straight. Instead, it may be curved and aligned with the actual path of 12th Street. 
     Before either the location determiner  210  or the travel path determiner  212  can precisely determine the location or travel path of the vehicle  104 , the city must be known. Of the cities that have a 12th Street, only a subset is likely to also have a Forest Avenue intersecting 12th Street. Based on this information, the location determiner  210  and/or travel path determiner  212  may be able to determine the particular city by narrowing down the cities that meet the criteria defined by the navigational voice cues. If there are still multiple cities that have all the roads and intersections as indicated, then the location determiner  210  and/or travel path determiner  212  may store the navigation information already received and wait for another voice cue to further filter possible cities until the particular city is identified via a process of elimination. 
     Typically, a subsequent navigational voice cue  110  is provided soon after the driver follows the previous voice cue. As such, when the third voice cue instructs the driver, “In 8.1 miles, turn right onto Benton Street,” the location determiner  210  may determine that the vehicle  104  has just turned right from 12th Street onto Forest Avenue. Thus, while the precise location of the vehicle  104  may not be known at any given moment, each time a new navigational voice cue is provided, the location determiner  210  can determine the general location of the vehicle as being near the previously identified route point (e.g., intersection). Further, in some examples, additional voice cues may be provided immediately before a route point (e.g., an intersection) to serve as a reminder to a driver about the upcoming route point. As such, the location determiner  210  may determine the location of the vehicle  104  as being near the upcoming route point when a corresponding voice cue is detected. Furthermore, in some examples, the location determiner  210  may monitor the timing of each voice cue to predict the approximate location of the vehicle between identified route points. 
     The fourth navigational voice cue in the above example indicates that the navigation system  106  is recalculating the route for the vehicle  104 . The recalculating voice cue in the above example may suggest that the driver has turned off of Forest before reaching Benton Street or that the driver failed to turn right onto Benton Street (e.g., drove passed the Benton Street intersection without turning). Because the recalculating voice cue indicates the vehicle  104  has diverted from the guided route, in some examples, the travel path determiner  212  disregards the Forest Avenue and Benton Street intersection as being on the travel path of the vehicle  104 . However, the location determiner  210  may nevertheless store the intersection as a prediction of the general area to which the vehicle  104  is being navigated (e.g., an anticipated location of the vehicle  104 ). 
     In some examples, the location determiner  210  and/or the travel path determiner  212  distinguish between the driver turning off of Forest Avenue before Benton Street versus staying on Forest Avenue but driving past Benton Street based on the road identified in the navigational voice cue following the recalculating voice cue. For example, the fifth voice cue in the above example identifies Jules Avenue as the new next road to turn on (instead of Benton Street). As such, if Jules Avenue intersects with Forest Avenue beyond Benton Street, the location determiner  210  and/or the travel path determiner  212  may determine that the vehicle  104  is still on Forest Avenue but has missed the Benton Street turn. On the other hand, if Jules Avenue does not intersect with Forest Avenue after the Benton Street intersection (e.g., runs parallel to Forest Avenue), then the location determiner  210  and/or the travel path determiner  212  may determine that the vehicle  104  has turned off of Forest Avenue onto another road towards an upcoming intersection (that is 0.5 miles away) with Jules Avenue. In this latter scenario, the name of the cross street may not be known. However, as future navigational voice cues are detected, the location determiner  210  will be able to reassess the approximate location of the vehicle  104 . Similarly, while the particular cross-street may not be identified by the voice cues, as additional voice cues are detected the travel path determiner  212  may be able to retrace the path of the vehicle  104  to at least approximate the cross street. Furthermore, in some examples, the location determiner  210  may predict the approximate location where the vehicle turned off of Forest Avenue based on an estimated speed of the vehicle and a time since the vehicle turned onto Forest Avenue corresponding to the time of the third navigational voice cue in the above example. Likewise, the timing of the recalculating voice cue relative to the immediately preceding voice cue can be used to determine whether the vehicle  104  has turned before reaching the designated route point (the intersection at Benton Street) or passed the route point without turning. 
     In the illustrated example, the central facility  114  is provided with the target area determiner  214  to determine one or more target area(s) corresponding to geographically defined area(s) in which advertisement(s) provided by one of the business(es)  118  is to be disseminated. In some examples, the advertisement(s) are a promotional offer for goods or services located within the target area. In some examples, the target area(s) are defined based on a threshold distance (e.g., a radius, as traveled by a vehicle) from specific location(s) such as, for example, the address(es) of the business(es) providing the promotional offer(s) or other advertisement(s). For example, a business  118  may provide the central facility  114 , via the communication interface  202 , with an advertisement for a promotional sale at a location of the business  118 . Along with the advertisement, the business  118  may provide an address of the location of the business and request the advertisement to be provided to people detected to be travelling within two miles of the address. In some examples, the two mile threshold distance is defined as a radius defining a circle around the business address. In such examples, the target area determiner  214  generates a target area by identifying the roads and/or intersections within the two mile radius of the specified address. 
     In some examples, the target area(s) are defined based on specifically identified intersections, roads, and/or portions of roads selected or identified by the business(es)  118  associated with the advertisement(s) to be disseminated. For example, a business  118  may be aware of the high-traffic (and/or high speed) roads near where the business is located and, thus, identify these roads (and corresponding intersections) over a relatively large distance (e.g., five miles) from the business address and then identify less busy (and/or lower speed) roads that are closer to the business address (e.g., within one mile). In such examples, the target area determiner  214  stores the identified roads and/or intersections as the target area for the corresponding advertisement. 
     In some examples, the target area(s) are bounded areas defined by certain roads or other geographic markers. For example, a business  118  may identify two roads running east and west and two cross-roads running north and south to define a rectangular area within which the business desires the advertisement to be disseminated. In such examples, the target area determiner  214  generates a target area by identifying the roads and intersections within the geographic area bounded by the designated roads. 
     In some examples, other methods to define the target area(s) may be implemented and/or a combination of more than one of the above techniques may be implemented. Further, in some examples, any particular target area may include more than one discrete geographic area. For example, a business  118  may define an area within a one mile radius of the address of the business as part of the target area and separately define a main road that passes through the city near the business  118  but outside the one mile radius as another part of the target area. Additionally or alternatively, a business  118  may have multiple locations where the promotional offer is valid (e.g., addresses of a chain of stores) such that the target area includes geographical areas corresponding to the multiple locations. 
     In the illustrated example of  FIG. 2 , the central facility  114  is provided with the advertisement identifier  216  to identify advertisement(s) to be provided to the person  102  based on the detected travel path of the vehicle  104 . That is, in some examples, the advertisement identifier  216  compares the route points (e.g., roads and/or intersections) identified by the navigational voice cues  110  to the roads and/or intersections within the target area. If there is a match (e.g., the voice directed travel path of the vehicle  104  enters the target area), the example targeted advertisement identifier  216  identifies the advertisement(s) associated with the target area for providing to the person  102  in the vehicle  104 . In some examples, multiple business(es)  118  may provide different advertisements corresponding to different target areas and/or different target demographics to the central facility  114 . In such examples, the advertisement identifier  216  compares each route point (e.g., road and/or intersection) designated by the navigational voice cues  110  with each of the target areas. In some such examples, the voice cues  110  may guide the vehicle  104  through more than one target area. Accordingly, in some examples, the targeted advertisement identifier  216  identifies multiple advertisements to be provided to the person  102 . In some examples, the advertisement identifier  216  identifies different advertisements to be provided to different occupants in the vehicle  104  (e.g., a first advertisement for the person  102  and a second different advertisement for a different occupant). In some such examples, as both occupants are at the same location (e.g., within the same vehicle) the particular advertisement identified for each occupant may be based on other factors such as, for example, the demographics and/or preferences of the occupants. 
     As the purpose of advertisements distributed in this matter is to target individuals geographically located near a particular area, in some examples, the detection and analysis of the navigational voice cues  110  and the resulting identification and provision of advertisements to such individuals is accomplished in substantially real-time. In this manner, the advertisements will be provided to the person  102  (or other targeted consumers) while the person  102  is still near to the target area. In some examples, although the navigational voice cues  110  identify a road, intersection, or other route point within a target area, the person  102  may not be physically located in the target area. For instance, using the example outlined above, the third voice cue identifies the intersection of Forest Avenue and Benton Street as being 8.1 miles away. In some examples, the intersection may be within a target area associated with a one mile radius circle. In such examples, even though the vehicle  104  is 8.1 miles away, the advertisement identifier  216  nevertheless identifies the advertisement associated with the target area to be provided to the person  102  because the person is at least headed in the direction of the target area. Furthermore, in some examples, the advertisement identifier  216  identifies the advertisement to be provided even if the vehicle  104  changes course to avoid the previously designated intersection or to avoid the entire target area. Thus, the advertisement identifier  216  identifies advertisement(s) based on an expected path of the vehicle  104  or the anticipated location of the vehicle  104  corresponding to approaching roads and/or intersections or other route point rather than waiting until the vehicle  104  is actually located within the target area. 
     In some examples, in addition to identifying the target area, the business(es)  118  may identify one or more demographics and/or other characteristics of individuals targeted for the advertising campaign. Accordingly, in some examples, the advertisement identifier  216  compares the demographic characteristic(s) of the person  102  (as stored in a profile for the person  102 ) with the one or more criteria specified by the business(es)  118 . If the person  102  has characteristic(s) matching the criteria, the advertisement identifier  216  identifies the associated advertisement(s) to be provided to the person  102 . However, if the person  102  does not meet the criteria set by the business(es)  118 , the advertisement identifier  216  will exclude the associated advertisement(s) from being provided to the person  102  even if the designated travel path of the vehicle  104  passes through the corresponding target area. 
     In some examples, the person  102  may indicate particular interests and/or preferences relating to which the person  102  desires to receive notification of advertisements. Additionally or alternatively, the person  102  may indicate one or more particular categories or types of advertisements to which the person  102  does not want to receive advertisements. In some examples, such preferences are stored in a profile associated with the person  102 . In some such examples, the advertisement identifier  216  will exclude advertisement(s) from being provided to the person  102  if they do not meet the preference(s) indicated even if the designated travel path of the vehicle  104  passes through the corresponding target areas. 
     In some examples, identified advertisement(s) are communicated to the person  102  via the communication interface  202 . More particularly, in some examples, the communication interface  202  communicates the advertisement(s) identified by the advertisement identifier  216  via a text message and/or an email to a mobile device  120  of the person  102 . In some examples, the advertisement is self-contained within the email or text message. In other examples, the email or text message indicates that there is a new advertisement associated with a good or service near where the person  102  is located that can be viewed by accessing a website that manages and/or aggregates such advertisement(s). In some examples, the email or text message provides a link to the website. In some examples, the website generator  218  is provided to generate and/or manage the website. For example, the website generator  218  may aggregate different advertisement(s) received from different business(es)  118  and place them in the website. In some examples, the website generated by the website generator  218  requires a login such that the person  102  is directed to a portion of the website with the advertisement(s) identified by the advertisement identifier  216  particular for the person and/or the location of the person. 
     In the illustrated example of  FIG. 1 , the central facility  114  is provided with the exposure analyzer  220  to determine exposure of the person  102  to outdoor advertisement(s). In some examples, the exposure analyzer  220  determines such exposure by comparing the travel path of the vehicle  104  (as determined by the travel path determiner  212 ) with the location(s) of outdoor advertisement(s) (as provided from the business(es)  118 ). If the travel path of the vehicle  104  passes by the location of a particular advertisement, the exposure analyzer  220  determines that the person  102  in the vehicle was exposed to the advertisement. In some examples, the exposure analyzer  220  may aggregate exposure data from multiple individuals and then statistically extrapolate the data to a more general population to estimate a reach of the advertisement. In some examples, the exposure analyzer  220  generates reports of such exposure and/or reach metrics for the business(es)  118 . 
     In the illustrated example of  FIG. 1 , the central facility  114  is provided with the database(s)  222  to store the meter data received from the meter  112 , the navigation information extracted from the navigational voice cues  110  (whether generated and provided by the meter  112  or generated at the central facility  114 ), and/or the location, anticipated location, and/or travel path of the vehicle  104  determined based on the navigational voice cues  110 . Further, in some examples, the database(s)  222  store advertising information received from the business(es)  118  corresponding to the advertisement(s) and/or associated information to be provided to potential customers, information regarding the target areas of such advertisements, and/or the information regarding to the location of outdoor advertisements of the business(es)  118 . Further still, in some examples, the database(s)  222  store reference maps or similar navigation based information to look up the roads, intersections, and other route points detected from the navigational voice cues  110 . 
     While an example manner of implementing the central facility  114  of  FIG. 1  is illustrated in  FIG. 2 , one or more of the elements, processes and/or devices illustrated in  FIG. 2  may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, the example communication interface  202 , the example voice cue detector  204 , the example speech analyzer  206 , the example audio code analyzer  208 , the example location determiner  210 , the example travel path determiner  212 , the example target area determiner  214 , the example advertisement identifier  216 , the example website generator  218 , the example exposure analyzer  220 , the example database(s)  222 , and/or, more generally, the example central facility  114  of  FIG. 2  may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of the example communication interface  202 , the example voice cue detector  204 , the example speech analyzer  206 , the example audio code analyzer  208 , the example location determiner  210 , the example travel path determiner  212 , the example target area determiner  214 , the example advertisement identifier  216 , the example website generator  218 , the example exposure analyzer  220 , the example database(s)  222 , and/or, more generally, the example central facility  114  could be implemented by one or more analog or digital circuit(s), logic circuits, programmable processor(s), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to cover a purely software and/or firmware implementation, at least one of the example communication interface  202 , the example voice cue detector  204 , the example speech analyzer  206 , the example audio code analyzer  208 , the example target area determiner  214 , the example location determiner  210 , the example travel path determiner  212 , the example advertisement identifier  216 , the example website generator  218 , the example exposure analyzer  220 , and/or the example database(s)  222  is/are hereby expressly defined to include a tangible computer readable storage device or storage disk such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc. storing the software and/or firmware. Further still, the example central facility  114  of  FIG. 1  may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated in  FIG. 2 , and/or may include more than one of any or all of the illustrated elements, processes and devices. 
       FIG. 3  is a block diagram of an example implementation of the example meter  112  of  FIG. 1 . The example meter  112  of  FIG. 3  includes an example user interface  302 , an example microphone  304 , an example voice cue detector  306 , an example speech analyzer  308 , an example audio code analyzer  310 , an example location determiner  312 , an example time stamper  314 , and an example communication interface  316 . 
     In the illustrated example of  FIG. 3 , the meter  112  is provided with the user interface  302  to enable the person  102  and/or other occupants in the vehicle  104  to identify their presence in the vehicle  104 . The user interface may be implemented by a touchscreen, push button, switches, a microphone, and/or any other form of input device. The information entered by the vehicle occupants is combined to form the vehicle occupant data to be transmitted to the central facility  114 . As described above, in some examples, the vehicle occupant data may include a count of the number of occupants in the vehicle  104 , an identification of a demographic characteristic of the vehicle occupants, and/or the unique identification of the occupants. For example, the occupants may be panelists with a unique user account and/or identifier that is obtained upon (or shortly after) their entry into the vehicle by logging in via the user interface  302 . In some examples, one or more of the occupants may not be panelists but guests in a panelist&#39;s vehicle. In such examples, the guests may enter that they are guests without being uniquely identified via the user interface  302 . In some examples, the user interface  302  is provided to enable the person  102  to enter the city where the vehicle  104  is located to assist in determining the location of the vehicle in accordance with the teachings disclosed herein. In some examples, tags, near field or Bluetooth devices, smart phones, etc., are used to automatically log onto the meter upon entry into the vehicle. 
     In the illustrated example of  FIG. 3 , the meter  112  is provided with the microphone  304  to monitor and/or capture the in-vehicle audio data, which may include the navigational voice cues  110  and/or other ambient noises produced in the vehicle  104  where the meter  112  is located. 
     In the illustrated example of  FIG. 3 , the example voice cue detector  306 , the example speech analyzer  308 , the example audio code analyzer  310 , and the example location determiner  312  of the example meter  112  function similar or identical to the corresponding example voice cue detector  204 , the example speech analyzer  206 , the example audio code analyzer  208 , and the example location determiner  210  of the example central facility  114  described above in connection with  FIG. 2 . That is, in some examples, the meter  112  locally analyzes and processes the in-vehicle audio data to extract navigation information and/or determine the location of the vehicle  104  based on the navigational voice cues  110 . In some such examples, the example voice cue detector  204 , the example speech analyzer  206 , the example audio code analyzer  208 , and/or the example location determiner  210  may be omitted from the central facility  114 . By contrast, if the analysis is to be implemented by the central facility  114  as described above, then some or all of the corresponding elements may be omitted from the meter  112 . Further, in some examples, a different division of functionality may be implemented between the meter  112  and the central facility  114 . For example, the meter  112  may include voice cue detector  306  and the speech analyzer  308  but omit the functionality of the audio code analyzer  310  and the location determiner  312 , which are then implemented by the central facility  114 . In this manner, the processing power and/or complexity of either the meter  112  or the central facility  114  may be adjusted to meet the needs of the particular circumstance. 
     In some examples, the meter  112  is provided with the time stamper  314  to time stamp the in-vehicle audio data and/or each navigational voice cue as it is collected by the microphone  304  and/or detected by the voice cue detector  306 . In this manner, the timing of the navigational voice cues  110  can be analyzed to assist in approximating the location of the vehicle  104  and/or in generating the travel path of the vehicle  104 . 
     In the illustrated example of  FIG. 3 , the meter  112  is provided with the communication interface  316  to meter data to the central facility  114  of the data collection entity  116  shown in  FIG. 1 . In some examples, the meter data includes the in-vehicle audio data (or navigation information if determined by the meter  112 ), the vehicle occupant data, and/or other data (e.g., the user designated city, time stamps, etc.) collected by the meter  112 . 
     While an example manner of implementing the meter  112  of  FIG. 1  is illustrated in  FIG. 3 , one or more of the elements, processes and/or devices illustrated in  FIG. 3  may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, the example user interface  302 , the example microphone  304 , the example voice cue detector  306 , the example speech analyzer  308 , the example audio code analyzer  310 , the example location determiner  312 , the example time stamper  314 , the example communication interface  316 , and/or, more generally, the example meter  112  of  FIG. 3  may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of the example user interface  302 , the example microphone  304 , the example voice cue detector  306 , the example speech analyzer  308 , the example audio code analyzer  310 , the example location determiner  312 , the example time stamper  314 , the example communication interface  316 , and/or, more generally, the example meter  112  could be implemented by one or more analog or digital circuit(s), logic circuits, programmable processor(s), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to cover a purely software and/or firmware implementation, at least one of the example user interface  302 , the example microphone  304 , the example voice cue detector  306 , the example speech analyzer  308 , the example audio code analyzer  310 , the example location determiner  312 , the example time stamper  314 , and/or the example communication interface  316  is/are hereby expressly defined to include a tangible computer readable storage device or storage disk such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc. storing the software and/or firmware. Further still, the example meter  112  of  FIG. 1  may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated in  FIG. 3 , and/or may include more than one of any or all of the illustrated elements, processes and devices. 
     Flowcharts representative of example machine readable instructions for implementing the central facility  114  of  FIG. 2  is shown in  FIGS. 4 and 5 . In these examples, the machine readable instructions comprise a program for execution by a processor such as the processor  612  shown in the example processor platform  600  discussed below in connection with  FIG. 6 . The program may be embodied in software stored on a tangible computer readable storage medium such as a CD-ROM, a floppy disk, a hard drive, a digital versatile disk (DVD), a Blu-ray disk, or a memory associated with the processor  612 , but the entire program and/or parts thereof could alternatively be executed by a device other than the processor  612  and/or embodied in firmware or dedicated hardware. Further, although the example program is described with reference to the flowcharts illustrated in  FIGS. 4 and 5 , many other methods of implementing the example central facility  114  may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined. 
     As mentioned above, the example processes of  FIGS. 4 and 5  may be implemented using coded instructions (e.g., computer and/or machine readable instructions) stored on a tangible computer readable storage medium such as a hard disk drive, a flash memory, a read-only memory (ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, a random-access memory (RAM) and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term tangible computer readable storage medium is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media. As used herein, “tangible computer readable storage medium” and “tangible machine readable storage medium” are used interchangeably. Additionally or alternatively, the example processes of  FIGS. 4 and 5  may be implemented using coded instructions (e.g., computer and/or machine readable instructions) stored on a non-transitory computer and/or machine readable medium such as a hard disk drive, a flash memory, a read-only memory, a compact disk, a digital versatile disk, a cache, a random-access memory and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media. As used herein, when the phrase “at least” is used as the transition term in a preamble of a claim, it is open-ended in the same manner as the term “comprising” is open ended. 
     Turning in detail to  FIG. 4 , the illustrated flowchart is representative of example machine readable instructions that may be executed to implement the example central facility  114  to provide geographically targeted advertisements to potential customers (e.g., the person  102 ). The example program begins at block  402  where the example communication interface  202  receives advertising information from one or more business(es)  118 . In some examples, the advertising information includes advertisements and/or other promotional information as well as target location information indicative of a geographic region where the advertisement is targeted. At block  404 , the example target area determiner  214  determines one or more target area(s) based on the advertising information. In some examples, block  402  may be repeated to enable the business(es)  118  to provide new advertising information and/or to adjust the advertising information previously provided. In such examples, the target area determiner  214  may continuously and/or dynamically determine new target area(s) based on the advertising information (block  404 ). At block  406 , the example communication interface  202  receives meter data from a meter  112  in a vehicle  104 . In some examples, the meter data includes in-vehicle audio data captured by a microphone  304  of the meter  112 , vehicle occupant data entered by and/or otherwise collected from occupants (e.g., the person  102 ) via the user interface  302  of the meter  112 , and/or other forms of information collected by the meter  112 . In some examples, the in-vehicle audio data includes navigational voice cues  110  emitted from a navigation system  106  in the vehicle  104 . In some examples, the meter  112  processes and/or analyzes the in-vehicle audio data and transmits the resulting navigation information as part of the meter data. 
     At block  408 , the example voice cue detector  204  determines whether there is a navigational voice cue  110  captured from the navigation system  106  in the vehicle  104 . For example, the voice cue detector  204  analyzes in-vehicle audio data captured by the microphone  304  of the meter  112  and transmitted by the communication interface  316  of the meter  112  to detect the navigational voice cues  110 . If the example voice cue detector  204  does not detect a navigational voice cue, control returns to block  406  to receive additional meter data. Once the example voice cue detector  204  determines that there is a navigational voice cue (block  408 ), control advances to block  410 . In some examples, the navigational voice cues  110  are detected by the voice cue detector  306  of the meter  112 , which is then transmitted to the central facility  114  for further processing and analysis. In such examples, the example program of  FIG. 4  may omit block  408  as it is implemented by the meter  112  instead of the central facility  114 . In some such examples, block  408  is implemented by the example voice cue detector  306  in  FIG. 3 . 
     At block  410 , the example speech analyzer  206  determines whether the detected voice cue includes identifiable directions (e.g., directions corresponding to an identifiable route point (e.g., road, approaching intersection, etc.)). If the voice cue does not include identifiable directions (e.g., the speech analyzer cannot interpret the voice cue or the voice cue is not giving directions (e.g., a “recalculating” cue)), control returns to block  406 . If the voice cue does include identifiable directions, control advances to block  412  where the example speech analyzer  206  identifies navigation information from the voice cue. That is, the example speech analyzer  206  identifies the name of any roads, intersections, and/or route points specified by the voice cue, any distances specified by the voice cues, and/or any directions specified by the voice cue (e.g., turn right, head south, exit left, etc.). In some examples, the speech analyzer  308  of the meter  112  identifies such navigation information, which is then transmitted to the central facility  114  for further processing and analysis. In such examples, the example program of  FIG. 4  may omit blocks  410  and  412  as they are implemented by the meter  112  instead of the central facility  114 . In some such examples, blocks  410  and  412  are implemented by the example speech analyzer  308  of  FIG. 3 . 
     At block  414 , the example database(s)  222  stores the navigation information. At block  416 , the example location determiner  210  determines whether the city can be determined. In some examples, the city is determined by the audio code analyzer  208  analyzing the in-vehicle audio data associated with the navigational voice cue  110  to detect an audio code that identifies the city. In some examples, the city is determined based on information transmitted from the meter  112  and provided by the person  102  (e.g., by speaking the city name, by typing in the city name, by selecting the city name from a list, etc.). In some examples, the city is determined based on the navigation information. For example, the name of a road identified in the navigational voice cue  110  may be unique to a particular city, thus, enabling the city to be determined. If the location determiner  210  cannot determine the city (e.g., there is no audio code, no user input, and the navigation information is not unique), control returns to block  408  to detect a subsequent voice cue with additional navigation information to narrow the pool of potential cities until the particular city where the vehicle is located is determined via a process of elimination, at which point control advances to block  418 . 
     At block  418 , the example location determiner  210  determines the location of the vehicle  104 . In some examples, the location of the vehicle  104  corresponds to an intersection or other route point identified by the voice cues. In some examples, the location of the vehicle  104  corresponds to a distance from a particular route point (e.g., intersection) identified by the voice cues. At block  420 , the example location determiner  210  determines the anticipated location of the vehicle  104 . In some examples, the anticipated location of the vehicle  104  corresponds to an approaching route point identified in a recent (e.g., most recent) navigational voice cue  110 . In some examples, the meter  112  is provided with the audio code analyzer  310  and the location determiner  312  to determine the city and resulting location and/or anticipated location of the vehicle  104 . In such examples, the resulting navigation information determined at the meter  112  may be transmitted to the central facility  114  for further processing and analysis. In some such examples, the example program of  FIG. 4  may omit blocks  410 ,  412 ,  414 ,  416 ,  418 , and  420  as they are implemented by the meter  112  instead of the central facility  114  (e.g., via the speech analyzer  308  and the location determiner  312  of  FIG. 3 ). Further, in some such examples, if the location determiner  312  cannot determine the city (block  416 ), the meter  112  may prompt an occupant of the vehicle to identify the city and wait for a response before returning to block  408 . 
     At block  422 , the example advertisement identifier  216  determines whether either the location or the anticipated location of the vehicle  104  is within one or more target area(s) corresponding to one or more advertisement(s). If the example advertisement identifier  216  determines that either the location or the anticipated location are within target area(s) corresponding to advertisement(s), control advances to block  424  where the example communication interface  202  provides the corresponding advertisement(s) to occupant(s) (e.g., the person  102 ) of the vehicle  104 . In some examples, the communication interface  202  provides the advertisement(s) directly to the occupant(s) via one or more email(s) and/or text message(s). In other examples, the communication interface  202  provides information to the occupant(s) indicating the advertisement(s) are accessible on a website generated by the example website generator  218 . In some examples, the advertisement(s) are provided to the occupant(s) indirectly via the business(es)  118 . For example, once the advertisement identifier  216  determines that either the location or the anticipated location of the vehicle  104  is within one or more target area(s) (block  422 ), the communication interface  202  provides the determined location to the business(es)  118  associated with the corresponding target area(s). In some such examples, the business(es)  118  may then provide the corresponding advertisement(s) to the occupant(s). Once the example advertisement(s) are provided to the occupant(s) (block  424 ), control advances to block  426 . If the example advertisement identifier  216  determines that neither the location nor the anticipated location are within the target area(s) corresponding to the advertisement(s) (block  422 ), control advances directly to block  426 . At block  426 , the example program determines whether to continue. If so, control returns to block  406 , otherwise the example program of  FIG. 4  ends. 
     Although the example program of  FIG. 4  is described with respect to meter data received from the meter  112  in the vehicle  104 , in some examples, multiple instances of the program of  FIG. 4  are executed at one time (e.g., based on meter data received from different meters in different vehicles). 
     Turning now to  FIG. 5 , the illustrated flowchart is representative of example machine readable instructions that may be executed to implement the example central facility  114  of  FIG. 1  to track exposure of potential consumers (e.g., the person  102 ) to outdoor advertisements. The example program begins at block  502  where the example communication interface  202  receives advertising information from one or more business(es)  118 . In some examples, the advertising information includes the location(s) of outdoor advertisement(s) (e.g., billboards) and/or other outdoor media for which the business(es)  118  desire exposure information. In some examples, block  402  may be repeated to enable the business(es)  118  to provide new advertising information and/or to adjust advertising information previously provided. At block  504 , the example communication interface  202  receives meter data from a meter  112  in a vehicle  104 . In some examples, the meter data includes in-vehicle audio data captured by a microphone  304  of the meter  112 , vehicle occupant data entered by occupants (e.g., the person  102 ) via a user interface  302  of the meter  112 , and/or other forms of information collected by the meter  112 . In some examples, the in-vehicle audio data includes navigational voice cues  110  emitted from a navigation system  106  in the vehicle  104 . In some examples, the meter  112  may process and/or analyze the in-vehicle audio data and transmit the resulting navigation information as part of the meter data. In some examples, the example communication interface  202  receives meter data from other meters in different vehicles in addition to the meter data received from the meter data from the meter  112 . 
     At block  506 , the example voice cue detector  204  identifies a navigational voice cue  110 . For example, the voice cue detector  204  analyzes the in-vehicle audio data captured by the microphone  304  of the meter  112  to detect the navigational voice cues  110 . At block  508 , the example speech analyzer  206  determines whether the detected voice cue(s) include identifiable directions (e.g., directions corresponding to an identifiable road or approaching intersection). If the voice cue(s) do not include identifiable directions (e.g., the speech analyzer cannot interpret the voice cue or the voice cue is not giving directions (e.g., a “recalculating” cue)), control returns to block  506 . In some examples, the meter data associated with an entire trip by the vehicle  104  is received (block  504 ) in advance of block  506 . In such examples, the voice cue detector  204  analyzes the in-vehicle audio data in chronological order such that the first navigational voice cue identified by the voice cue detector  204  is first in time. Thus, if control returns to block  506  because the example speech analyzer  206  determined that the first navigational voice cue did not include identifiable directions (block  508 ), the example voice cue detector  204  may identify the next voice cue from the in-vehicle audio data. In some examples, the program of  FIG. 5  may be implemented in substantially real time such that the voice cue detector  204  identifies successive navigational voice cues as they are collected by the meter  112  and transmitted to the central facility  114 . In some examples, the navigational voice cues  110  are detected by the voice cue detector  306  of the meter  112 , which is then transmitted to the central facility  114  for further processing and analysis. In such examples, the example program of  FIG. 5  to implement the central facility  114  may omit blocks  506  and  508  as they are implemented by the meter  112 . 
     If the voice cue detector  204  of the illustrated example determines that the voice cue(s) include identifiable directions (block  508 ), control advances to block  510  where the example speech analyzer identifies navigation information from the voice cue. That is, the example speech analyzer  206  identifies the name of any roads, intersections, and/or route points specified by the voice cue, any distances specified by the voice cues, and any directions specified by the voice cue (e.g., turn right, head south, exit left, etc.). In some examples, the speech analyzer  308  of the meter  112  identifies such navigation information, which is then transmitted to the central facility  114  for further processing and/or analysis. In such examples, the example program of  FIG. 5  may omit block  510  as it is implemented by the meter  112 . 
     At block  512 , the example database  222  stores the navigation information. At block  514 , the example travel path determiner  212  generates a travel path. In some examples, the travel path is based on the navigation information identified from the navigational voice cues. At block  516 , the example voice cue detector  204  determines whether there are more navigational voice cues. If there are more voice cues, control advances to block  518  where the example speech analyzer  206  determines whether the next voice cue recalculates the directions. That is, the example speech analyzer  206  determines whether the next voice cue is a “recalculating” cue, which is indicative of the vehicle  104  departing from the route indicated by the previous voice cue. If the example speech analyzer  206  determines that the next cue does recalculate directions, control advances to block  520  where the example travel path determiner  212  updates the travel path. For example, the travel path determiner  212  may remove or disregard the route point (e.g., road and/or intersection) identified in the previous voice cue from the travel path of the vehicle  104  being generated. In some examples, the previously identified route point (e.g., road and/or intersection) is merely flagged as potentially off route to be determined once subsequent navigational voice cues have been collected and analyzed. Control then returns to block  516  to determine if there are any more navigational voice cues. If the example speech analyzer  206  determines that the next cue does not recalculate directions (block  518 ), control advances to block  522  where the example speech analyzer  206  determines whether the next cue includes new identifiable directions. If the next voice cue does include new identifiable directions, control returns to block  508  to identify the navigation information associated with the voice cue to continue developing the travel path. If the example speech analyzer  206  determines that the next voice cue does not include new identifiable directions, control returns to block  516  to determine whether there are more navigational voice cues. 
     If the example voice cue detector  204  determines that there are no more navigational voice cues (block  516 ), control advances to block  524  where the example travel path determiner  212  determines whether the city can be determined. In some examples, the city is determined based on the audio code analyzer  208  analyzing the in-vehicle audio data associated with the navigational voice cue  110  to detect an audio code that identifies the city. In some examples, the city is determined based on information transmitted from the meter  112  provided by the person  102 . In some examples, the city is determined based on the collected navigation information. If the travel path determiner  212  cannot determine the city (e.g., there is no audio code, no user input, and the navigation information is not unique to a particular city), the example program of  FIG. 5  ends because there are no additional voice cues (block  516 ) with which the particular city may be identified. However, if the travel path determiner  212  can determine the city, control advances to block  526  where the example exposure analyzer  220  compares the travel path to the locations of the advertisement(s) provided by the business(es)  118 . At block  528 , the example exposure analyzer  220  generates an advertising exposure report. In some examples, the advertising exposure report indicates whether the vehicle  104  passed by the outdoor advertisement(s) to determine an exposure of the person  102  to the advertisement(s). In some examples, exposure data associated with individuals from multiple vehicles are aggregated to provide an indication of reach of the advertisements as part of the advertising exposure report. After block  528 , the example program of  FIG. 5  ends. 
       FIG. 6  is a block diagram of an example processor platform  1000  capable of executing the instructions of  FIGS. 4 and 5  to implement the central facility  114  of  FIG. 2 . The processor platform  1000  can be, for example, a server, a personal computer, a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPad™), a personal digital assistant (PDA), an Internet appliance, a DVD player, a CD player, a digital video recorder, a Blu-ray player, a gaming console, a personal video recorder, a set top box, or any other type of computing device. 
     The processor platform  600  of the illustrated example includes a processor  612 . The processor  612  of the illustrated example is hardware. For example, the processor  612  can be implemented by one or more integrated circuits, logic circuits, microprocessors or controllers from any desired family or manufacturer. 
     The processor  612  of the illustrated example includes a local memory  613  (e.g., a cache). The processor  612  of the illustrated example is in communication with a main memory including a volatile memory  614  and a non-volatile memory  616  via a bus  618 . The volatile memory  614  may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM) and/or any other type of random access memory device. The non-volatile memory  616  may be implemented by flash memory and/or any other desired type of memory device. Access to the main memory  614 ,  616  is controlled by a memory controller. 
     The processor platform  600  of the illustrated example also includes an interface circuit  620 . The interface circuit  620  may be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB), and/or a PCI express interface. 
     In the illustrated example, one or more input devices  622  are connected to the interface circuit  620 . The input device(s)  622  permit(s) a user to enter data and commands into the processor  612 . The input device(s) can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a track-pad, a trackball, isopoint and/or a voice recognition system. 
     One or more output devices  624  are also connected to the interface circuit  620  of the illustrated example. The output devices  624  can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display, a cathode ray tube display (CRT), a touchscreen, a tactile output device, a light emitting diode (LED), a printer and/or speakers). The interface circuit  620  of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip or a graphics driver processor. 
     The interface circuit  620  of the illustrated example also includes a communication device such as a transmitter, a receiver, a transceiver, a modem and/or network interface card to facilitate exchange of data with external machines (e.g., computing devices of any kind) via a network  626  (e.g., an Ethernet connection, a digital subscriber line (DSL), a telephone line, coaxial cable, a cellular telephone system, etc.). 
     The processor platform  600  of the illustrated example also includes one or more mass storage devices  628  for storing software and/or data. Examples of such mass storage devices  628  include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, RAID systems, and digital versatile disk (DVD) drives. 
     The coded instructions  632  of  FIGS. 4 and 5  may be stored in the mass storage device  628 , in the volatile memory  614 , in the non-volatile memory  616 , and/or on a removable tangible computer readable storage medium such as a CD or DVD. 
     From the foregoing, it will be appreciated that the above disclosed methods, apparatus and articles of manufacture provide a technique to track and/or determine the location of users in a vehicle. More particularly, this is accomplished by monitoring navigational voice cues output by a navigation system directing an operator of the vehicle. While GPS navigation systems are known and can be used to determine the location of a user, the examples disclosed herein improve upon such technology by being less intrusive in that the example methods and systems disclosed herein cannot pinpoint the exact location of the user at each moment. As a result, there is an increased likelihood that people may be willing to consent to be panelists and be monitored in this manner. Furthermore, the location tracking described herein has multiple beneficial applications. As described above, the determined location information can be used to determine the location of users in substantially real time to then provide advertisements, discounts, coupons, or other promotional offers associated with business(es) near the location of the users. Additionally or alternatively, in some examples, the location information can be provided to the business(es) to then target the users directly with advertisements. Further, the location information can be used to measure the exposure of users to outdoor advertisements based on the travel path followed by the users. 
     Although certain example methods, apparatus and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all methods, apparatus and articles of manufacture fairly falling within the scope of the claims of this patent.