Patent Publication Number: US-9905055-B2

Title: Automated transit validation rule updating

Description:
CROSS-REFERENCES TO RELATED APPLICATIONS 
     The present application claims benefit under 35 USC 119(e) of U.S. Provisional Application No. 62/206,133, filed on Aug. 17, 2015, entitled “Actionable Rejected Ticket Analysis,” which is incorporated by reference herein in their entirety. 
    
    
     BACKGROUND 
     Fare validation is used to determine access to services within a transit system. In general, fare validation involves a check to see whether a particular fare media (e.g., a transit ticket) is valid at a particular fare media validator of the transit system (e.g., to enable a transit user to pass through a turnstile or other access control point within the transit system). This can involve a fare validator reading information from the fare media and using a set of validation rules to determine whether the fare media is valid at a particular location, during a particular time, on a particular date, and the like. When a fare media does not pass validation, it can result in a rejected transaction in which a transit user is denied a ride or other service transit system. 
     In traditional transit systems, it may take a long time to determine that a set of fare validation rules is incorrect. Such systems may require manually changing the validation rules, which may only be prompted in response to complaints by transit user. Such inefficiencies can result in a poor transit user experience, among other problems. 
     BRIEF SUMMARY 
     Techniques are disclosed for automatically determining and implementing fare validation rules based on analysis of rejected transactions from one or more fare validators. In some embodiments, a server or other monitoring system can monitor rejected transactions, determine a common characteristic among all the rejected transactions (e.g., when a threshold number of rejected transactions occurs within a certain period of time), and create a validation rule change that would permit the use of fare media having the common characteristic. In some embodiments, the validation rule change may be reviewed and/or modified by a transit agent or other human supervisor. Accordingly, among other benefits, validation rule changes can be automatically created and quickly implemented where a number of rejected transactions indicate previous validation rules may be incorrect. 
     An example computer server, according to the disclosure, comprises a communication interface configured to obtain a plurality of rejected transactions from one or more fare media validators of a transit system, each rejected transaction of the plurality of rejected transactions indicative of when a fare media was not able to be validated by one of the one or more fare media validators of the transit system, and a processing unit coupled with the communication interface. The processing unit is configured to analyze the plurality of rejected transactions to determine at least one common characteristic among all rejected transactions of the plurality of rejected transactions causing, at least in part, the rejection of each rejected transaction of the plurality of rejected transactions, and determine a validation rule change based on the analysis of the plurality of rejected transactions. The validation rule change is a change in one or more validation rules used by the one or more fare media validators of the transit system. The validation rule change, when implemented by the one or more fare media validators of the transit system, is configured to cause the one or more fare media validators of the transit system to allow future transactions having the at least one common characteristic, resulting in the one or more fare media validators of the transit system validating fare media used in the future transactions. The processing unit is further configured to send, via the communication interface, information indicative of the validation rule change to the one or more fare media validators. 
     An example method of updating one or more validation rules in a transit system, according to the disclosure, comprises obtaining a plurality of rejected transactions from one or more fare media validators of the transit system, each rejected transaction of the plurality of rejected transactions indicative of when a fare media was not able to be validated by one of the one or more fare media validators of the transit system, and analyzing, with a processing unit, the plurality of rejected transactions to determine at least one common characteristic among all rejected transactions of the plurality of rejected transactions causing, at least in part, the rejection of each rejected transaction of the plurality of rejected transactions. The method further includes determining a validation rule change based on the analyzing, where the validation rule change is a change in the one or more validation rules used by the one or more fare media validators of the transit system, and the validation rule change, when implemented by the one or more fare media validators of the transit system, would cause the one or more fare media validators of the transit system to allow future transactions having the at least one common characteristic, resulting in the one or more fare media validators of the transit system validating fare media used in the future transactions. The method also comprises sending, via the communication interface, information indicative of the validation rule change to the one or more fare media validators. 
     An example non-transitory computer-readable medium, according to the disclosure, has instructions embedded thereon for updating one or more validation rules in a transit system. The instructions include computer code for obtaining a plurality of rejected transactions from one or more fare media validators of the transit system. Each rejected transaction of the plurality of rejected transactions is indicative of when a fare media was not able to be validated by one of the one or more fare media validators of the transit system. The instructions also include computer code for analyzing the plurality of rejected transactions to determine at least one common characteristic among all rejected transactions of the plurality of rejected transactions causing, at least in part, the rejection of each rejected transaction of the plurality of rejected transactions. The instructions also include computer code for determining a validation rule change based on the analyzing, where the validation rule change is a change in the one or more validation rules used by the one or more fare media validators of the transit system, and the validation rule change, when implemented by the one or more fare media validators of the transit system, would cause the one or more fare media validators of the transit system to allow future transactions having the at least one common characteristic, resulting in the one or more fare media validators of the transit system validating fare media used in the future transactions. The instructions also include computer code for sending information indicative of the validation rule change to the one or more fare media validators. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of this invention, reference is now made to the following detailed description of the embodiments as illustrated in the accompanying drawing, in which like reference designations represent like features throughout the several views and wherein: 
         FIG. 1  is a block diagram of a traditional transit system, according to one embodiment; 
         FIGS. 2A and 2B  are simplified block diagrams of components of a transit system (such as the transit system of  FIG. 1 ) that can be utilized to automatically update validation rules based on transaction information analysis, according to embodiments; 
         FIG. 3  is a swim-lane diagram indicating the various actions of a user, fare media validator, and a server, according to an embodiment; 
         FIG. 4  is a flow diagram illustrating a method of automatically determining a validation rule change within a transit system, according to one embodiment; and 
         FIG. 5  is a block diagram of an embodiment of a computer system. 
     
    
    
     In the appended figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label by a dash and a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any or all of the similar components having the same first reference label irrespective of the second reference label. 
     DETAILED DESCRIPTION OF THE INVENTION 
     The ensuing description provides embodiments only, and is not intended to limit the scope, applicability or configuration of the disclosure. Rather, the ensuing description of the embodiments will provide those skilled in the art with an enabling description for implementing an embodiment. It is understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope. 
     Transit systems use fare validation at fare media validators to determine whether to grant transit users services within the transit system. In general, fare validation involves a check to see whether a particular fare media (e.g., a transit ticket, smart card, virtual ticket/application, transit card, identification card, mobile phone, or other item presented for passage at access control points or for other services within the transit system) is valid at a particular fare media validator of the transit system. This can involve a fare validator reading information from the fare media and using a set of validation rules (also known as “base data”) to determine whether the fare media is valid at a particular location, during a particular time, on a particular date, and the like. When a fare media does not pass validation, it can result in a rejected transaction in which a transit user is denied service (e.g., denied access at a turnstile or other access control point) within the transit system. 
     These fare validation rules can be set by a transit authority managing the transit system and may include rules that permit passage at a fare media validator based on a certain time period, date, location, fare media type, and/or other factors, and can reflect temporary sales, permanent fare types, and/or other rules by which passage at a fare media validator may be accepted or denied. These rules can be stored in a database and propagated throughout the transit system to enable fare media validators to implement the rules when allowing or denying transit users passage through an access control point of the transit system. In traditional transit systems, validation rules are manually created by operators and propagated throughout the transit system. 
     In many cases, there may be errors in one or more of the validation rules. For example, a transit system may run a temporary offer allowing transit users having a particular fare media type valid only at transit stations in “Zone A” (a limited area) within a transit system to use the fare media at transit stations in “Zone B” and “Zone C” as well. (This type of offer can be made, for example, to interest users in a different type of transit fare media product that may be valid in Zones A, B, and C, to enable transit users additional access in emergency situations, or the like.) But, for any of a variety of reasons, it may be that the validation rules implemented by the transit system are not updated to reflect the temporary offer. This may result transit users being denied access to services at stations in Zones B and C by fare media validators within the transit system in cases where they should instead be granted access. 
     Traditional transit systems typically are not equipped to quickly determine that a set of fare validation rules is incorrect. For example, the transit system may be unaware of the error in the validation rules until they receive complaints by transit users. Traditional transit systems may also require manually changing the validation rules, which can further delay the correction of the validation rules and propagation of the correct validation rules throughout the transit system. Such inefficiencies can result in a poor transit user experience, among other problems. 
     As noted previously, techniques disclosed herein enable a transit system to automatically determine and implement fare validation rules based on analysis of rejected transactions from one or more fare validators. In some embodiments, a server or other monitoring system can monitor rejected transactions, determine a common characteristic among all the rejected transactions (e.g., when a threshold number of rejected transactions occurs within a certain period of time), and create a validation rule change that would validate fare media having the common characteristic. In some embodiments, the validation rule change may be reviewed and/or modified by a transit agent or other human supervisor. Accordingly, among other benefits, validation rule changes can be automatically created and quickly implemented where a number of rejected transactions indicate previous validation rules may be incorrect. 
       FIG. 1  is a block diagram of a traditional transit system  100 , according to one embodiment. The transit system can include various forms of transit, including subway, bus, ferry commuter rail, para-transit, etc., or any combination thereof. Here, the transit system  100  can comprise a backend data store  130 , a backend system  120 , the data communication network  110 , a plurality of station servers  140 , and a plurality of fare media validators  150 . A person having ordinary skill in the art will recognize that a traditional transit system  100  may include or omit any of a variety of components.  FIG. 1  is therefore simplification of the actual components used to implement a transit system. 
     The transit system  100  can include a plurality of station servers  140 , each located at different transit stations within the transit system  100 . Among other things, the station server  140  can receive and send data to fare media validators  150  of the transit station. Depending on desired functionality, the station server  140  can implement the validation rules by receiving requests from the fare media validators  150  and performing the validation based on the validation rules. Additionally or alternatively, the station server  140  may propagate the validation rules to each of the fare media validators  150  so that the fare media validators  150  themselves can perform validation by implementing the validation rules. In any case, the station server  140  can be used to propagate validation rules throughout the transit system  100  and to provide transaction information from the fare media validators  150  to the backend system  120 . The backend system  120  can further summarize and/or store transaction information in the backend data store  130 . 
     Fare media validators  150  are generally used at access control points of the transit system that enable transit users to pass between different areas (e.g., open-access areas, restricted-access areas, etc.) within a transit system. Fare media validators can therefore be used with and/or incorporated into access control points that include, for example, turnstiles, faregates, platform validators, para-transit vehicles, buses, conductor handheld units, or fare boxes at an entry, exit, or other location of a transit station. The number of fare media validators  150  at each station in the transit system  100  can vary, depending on the requirements of the station. At some stations, for example, a single fare media validator  150  may be utilized. Other stations may use two or more fare media validators  150 , up to dozens, or even hundreds or more. 
     Transactions of a transit user (e.g., for passage at an access control point, validation on trains, and/or other services within the transit system) can frequently occur at stations of the transit system  100 , although it will be understood that fare media validators  150  can exist elsewhere, such as on busses or trains. Transaction information can be generated by a fare media validator  150  when a fare media  160  is presented at the fare media validator  150  to allow transit user passage through an access control point. This transaction information can include a variety of data, depending on desired functionality. Transaction information can include, for example, a log, summary, or other indication of when certain types of fare media  160  are denied access by one or more fare media validators  150  of the transit system  100 . The transaction information may be sent from fare media validators to station servers  140  and from station servers  140  to the backend system  120  based on a scheduled time to transmit the transaction information, periodically, and/or based on a triggering event (such as a request from a remote device). Transaction information can be summarized and/or sent in batches, or sent individually, depending on desired functionality. In some configurations, a station server  140  may not be used, in which case (as shown in  FIG. 1 ) one or more fare media validators  150  may communicate with the backend system  120  via the data communication network  110 . In such instances, the one or more fare media validators  150  may perform some or all of the functions described herein performed by the station server  140 . 
     The data communication network  110  can include one or more networks, such as the Internet, which may be public, private, or a combination of both. The data communication network  110  could be packet-switched or circuit-switched connections using telephone lines, coaxial cable, optical fiber, wireless communication, satellite links, and/or other mechanisms for communication. As with communication between other components of the transit system  100 , communication between the station servers  140  and the backend system  120  may be in real time (e.g., as transactions occur), periodic, based on triggering events, and/or the like. Thus, the usage of fare media  160  throughout the transit system  100  can be tracked. 
     It will be understood that embodiments of the transit system  100  can vary, depending on desired functionality. Account-based fare media may be managed, for example, using an account-management server (not shown) that can create, store, and modify user accounts comprise information regarding users of the transit system  100 . Each account can include information regarding a transit user, such as a name, address, phone number, email address, user identification (such as a unique identifier of the user or other user ID), passcode (such as a password and/or personal identification number (PIN)), an identification code associated with a fare media used to identify a user and/or a transit user account, information regarding user preferences and user opt-in or opt-out selections for various services, product(s) associated with the transit user account, a value and/or credit associated with the product(s), information regarding a funding source for the transit user account, and more. The transit user account can further comprise transaction information, such as product information and a payment amount. A transit user may request a transit user account and provide the information listed above by phone (such as a call to a customer service center maintained and/or provided by the transit service provider of the transit system  100 ), on the Internet, at ticket booth, at a ticket vending machine, or by other means. 
     In embodiments in which transit user accounts are used, transactions, such as validation of fare media  160  at fare media validators  150 , can be recorded and/or tracked by the backend system  120  and reconciled with a funding source (not shown) such as a bank or similar entity. The transactions can be reconciled on a per-transaction basis and/or collectively with other transactions, and may be reconciled as transactions are received, on a scheduled or periodic basis, and/or based on a triggering event. 
     It can be noted that fare media  160  may additionally or alternatively include stored value media. In stored value media, a value (e.g., a monetary amount, a number of rides, etc.) is stored on the fare media  160  itself and used for validation by a fare media validator  150 . As the fare media  160  is used within the transit system  100  at various fare media validators  150 , the fare media validators  150  read a stored value from the fare media  160  and rewrite this value, reducing (or otherwise modifying) the value by an amount charged to gain access through the fare media validator  150 . The stored value therefore acts as a type of currency in the transit system  100 . In some embodiments, a transit user may “recharge” the fare media  160 , paying money to the transit authority in exchange for an increase in the value stored on the fare media  160 . 
     The transit system  100  of  FIG. 1 , by itself, may not be equipped to quickly determine that a set of fare validation rules is incorrect in the manner described above. Thus, additional components can be utilized to implement techniques described herein. Embodiments of systems with these components are shown in  FIGS. 2A and 2B . 
       FIG. 2A  is a simplified block diagram of components of a transit system that can be utilized to automatically update validation rules based on transaction information analysis, according to one embodiment. It should be understood that only a subset of the components of a transit system are illustrated in  FIG. 2A . A transit system may further comprise additional components (such as those shown in  FIG. 1 ). Additionally, components the fare media validators  150  may correspond to fare media validators of a traditional transit system (such as the transit system  100  of  FIG. 1 ). Communication between components may be made via a communication network (not shown), such as the data communication network  110  of  FIG. 1 . 
     In the embodiment shown in  FIG. 2A , the transit system components include a rejected transaction store  210 , ticket rejection analysis system  220  that produces a ticket rejection report  230  and suggested validation rule changes  240 . The transit system components include a validation rule delivery component  250  and validation rule store  260 . Optionally, as shown here, the rejected transaction store  210 , ticket rejection analysis system  220 , validation rule delivery component  250 , and validation rule store  260  may be implemented on a backend system  120  (such as the backend system  120  of  FIG. 1 ). Additionally or alternatively, the ticket rejection report  230  and suggested validation rule changes  240  (which may be files, data structures, or other software structures configured to convey information) can be sent to a backend interface  270  for review and/or interaction by a transit operator or other human supervisor. 
     The operation of the transit system components shown in  FIG. 2A  can proceed generally as follows. A transit user can present a fare media  160  at a fare media validator  150 - 1 . Depending on the type of fare media, this may involve positioning the fare media  160  so that a fare media reader of the fare media validator  150 - 1  can access information on the fare media  160  via wireless, optical, magnetic, and/or other means. Information read from the fare media  160  can include ticket type (e.g., an indicator that the transit authority can use to categorize the ticket), validity data (geographical restrictions, time restrictions, date restrictions, etc.), concessions (senior citizen discounts, student discounts, etc.), special rules (group tickets (e.g., only valid if three people travel together), valid only with particular transit authorities, etc.), and the like. In some embodiments, fare media  160  may include additional information. Depending on desired functionality, this additional information may not be read from the fare media  160 . 
     Once the fare media validator reads the validation information from the fare media  160 , it can use the validation information to validate the fare media  160 . This can include matching the validation information against validation rules to determine whether the fare media  160  is valid for passage through an access control point associated with the fare media validator  150 - 1 . As discussed above, these validation rules can comprise pre-stored business rules defined by the transit authority that are stored locally at the fare media validators  150  and/or at other devices (such as station servers  140 ) that make such rules readily available to the fare media validators  150  for validation. The outcome of the validation determination by the fare media validator  150 - 1  may be binary: the fare media  160  is either valid or not valid. If it is determined that the fare media  160  is not valid, the fare media validator  150 - 1  can send an indication of the rejection of the fare media  160  to the rejected transaction store  210 . The fare media validator  150 - 1  may also send additional information read from the fare media  160  to the rejected transaction store  210 . Additionally, according to some embodiments, the fare media validator  150 - 1  may cause an access control point to physically deny passage of a transit user through the access control point (by not opening a gate, for example). In some embodiments, after a fare media  160  has been rejected, the fare media validator  150 - 1  may additionally direct the transit user to a service agent. In some embodiments, rejected transaction information sent by fare media validators  150  can be collected by the station server (e.g., station server  140  of  FIG. 1 ), which can then send the rejected transaction information, in aggregate, to the rejected transaction store  210 . The transmittal of this information from the station server to the rejected transaction store  210  can be based on a triggering event (e.g., the receipt of a threshold number of rejected transactions, the threshold amount of time passing from when the initial rejected transaction was received, etc.), a schedule, and the like. 
     The rejected transaction store  210  can then provide information regarding the rejected transactions to the ticket rejection analysis system  220 . This information can vary, depending on desired functionality. In some embodiments, for example, the information provided by the rejected transaction store  210  can include a summary of the rejected transactions. In other embodiments, the information may include all of the rejected transaction information provided from various fare media validators  150 . The rejected transaction store  210  can accumulate rejected transaction information from the various fare media validators  150  of the transit system over a period of time, and then send the information to the ticket rejection analysis system  220  periodically, based on a schedule, based on a triggering event (e.g., a request from the ticket rejection analysis system  220 ), and the like. 
     The ticket rejection analysis system  220  can then analyze the information provided by the rejected transaction store  210  to determine whether validation rules may need to be adjusted, based on the information. The ticket rejection analysis system  220 , which can comprise a hardware and/or software module or device, can analyze the information by reviewing the rejected transactions and determining at least one common characteristic among all or a subset of the rejected transactions. This analysis may further include determining that a threshold number of transactions were rejected in a threshold amount of time (e.g., within a certain number of minutes, hours, etc.). From this analysis, the ticket rejection analysis system  220  may then determine a proposed validation rule change in response to the rejected transaction information. The proposed validation rule change can, if implemented by the fare media validators  150  of the transit system, cause fare media validators  150  to validate fare media  160  that would not have been validated without the validation rule change. 
     After the analysis, the ticket rejection analysis system  220  can then generate the ticket rejection report  230  and the suggested validation rule change  240 , which it may then provide to the backend interface  270  for review and/or interaction by a transit operator. The backend interface  270  can comprise a computer or similar device capable of providing information and interacting with a transit operator. In some embodiments, for example, the backend interface  270  can provide information regarding the ticket rejection report  230  and the suggested validation rule changes  240  in a graphical user interface (GUI) presented to the transit operator. The transit operator can then review this information and, based on this information, interact with the backend interface  270  to authorize the suggested validation rule changes, refuse them, or edit the suggested validation rule changes before they are authorized. 
     Validation rules that have been accepted (including those that may have been edited before being accepted) can then be provided to the validation rule delivery component  250 . In some embodiments, the validation rule delivery component  250  may comprise a hardware and/or software component of the backend system  120  capable of receiving the validation rules from the backend interface  270  and ensuring that the validation rules are stored in the validation rules store  260 . 
     The validation rules store  260  can comprise a database or other data structure in which validation rules are stored. As indicated in  FIG. 2A , the validation rules store  260  may be part of the backend system  120 . However, in alternative embodiments, the validation rules store  260  may be distinct and/or remote from the backend system  120 . The validation rules store  260  stores the validation rules to be propagated to fare media validators  150  throughout the transit system. Depending on desired functionality, the propagation of the validation rules in the validation rules store  260  may vary. In some embodiments, for example, the backend system  120  may send the validation rules in the validation rules store  260  to various fare media validators  150  based on a triggering event (such as receiving new validation rules from the validation rule delivery component  250 ). The backend system  120  may additionally or alternatively propagate validation rules in the validation rules store  260  periodically, based on the certain schedule, and the like. Also depending on desired functionality, the backend system  120  may send only the validation rules have changed or been added, or may send an entirely new set of validation rules for fare media validators  150  to implement to validate fare media  160 . 
     Depending on desired functionality and/or the factors of a particular situation, the process of gathering rejected transaction information and implementing the validation rules in response, using the components illustrated in  FIG. 2A , can take a matter of minutes or hours, depending on the particular scenario. (Other scenarios may take a larger or smaller amount of time.) In traditional transit systems (e.g., transit system  100  of  FIG. 1 ), on the other hand, this process can take days or longer (assuming a problem resulting in rejected transactions is identified in the first place). In transit, identifying and alleviating problems resulting in rejected transactions is extremely important because rejected transactions result in transit users not being able to travel and causing increased traffic and potential delays in the transit system. Additionally, the components illustrated in  FIG. 2A  can make it easier to apply business rules for validation among fare media validators  150  of the transit system, streamlining updates of validation rules (base data) to the fare media validators  150 . 
       FIG. 2B  is a simplified block diagram of components of a transit system that can be utilized to automatically update validation rules based on transaction information analysis, according to another embodiment. Most of the components correspond to similarly-labeled components of the embodiment illustrated in  FIG. 2A . Here, however, a backend interface  270  and a ticket rejection report  230  are not provided. Instead, the implementation of validation rule changes is fully automated within the backend system  120 . In other words, according to this embodiment, there does not need to be human oversight by a transit operator to implement the validation rule changes. Accordingly, the components illustrated in  FIG. 2B  operate similar to their counterparts in  FIG. 2A , with the primary difference being that suggested rule changes  240  are not authorized by a human transit operator, but instead are implemented automatically. The ticket rejection analysis system  220  can therefore provide the suggested validation rule changes  240  directly to the validation rule delivery component  250 . 
     Some embodiments could implement the functionality described in both  FIGS. 2A and 2B , depending on the scenario. In certain cases or for certain suggested validation rule changes (e.g., those that would alleviate clear validation rule errors, those implemented in emergencies, etc.) the suggested validation rule changes may be implemented automatically. In other cases, suggested validation rule changes can be approved by a human supervisor. 
       FIG. 3  is a swim-lane diagram indicating the various actions of a user, fare media validator, and a server, according to an embodiment. Here, the user may be a transit user attempting to travel through a transit system, the fare media validator may be one of many fare media validators within the transit system (as described in previous embodiments), and the server may be a computer or other device operated by the transit authority (such as the backend system  120  of  FIG. 1 ). 
     It will be understood that, in alternative embodiments, additional or alternative entities may perform one or more of the functions illustrated in  FIG. 3 . For example, the functions performed by the server may be performed by two or more computers or other devices. Additionally or alternatively, it will be understood that the functions shown in the blocks of  FIG. 3  may be altered depending on desired functionality. For example, functions may be added, omitted, performed simultaneously, and the like. A person of ordinary skill in the art will appreciate that alternative embodiments may include variations such as these. 
     At block  305  the user presents the fare media at the fare media validator. As indicated in previous embodiments this may vary, depending on the type of fare media utilized. For example, a fare media may comprise the card width a magnetic stripe, which is read by a magnetic card reader of the fare media validator. Other fare media may include barcodes or other visible markers, radio frequency (RF) circuits, and the like, and the fare media validator may be equipped with one or more readers to enable reading of the fare media. In some embodiments, barcodes or similar visual markers may be encrypted. 
     At block  310 , the fare media information is read by the fare media validator. Information read by the fare media validator may vary, depending on desired functionality. This information can include, for example, ticket type, validity data, concessions, special rules, and/or other information that can be used by the fare media validator to validate the fare media and grant the transit user passage through an associated access control point. 
     At block  315 , the fare media validator performs validation using validation rules. As previously indicated, validation rules (or base data) our business rules used to determine how to validate a fare media. In some embodiments, for example, ticket information may indicate that the ticket is valid at certain zones or stations, at certain times (peak, off-peak, etc.), on certain days (workdays, weekends, holidays, etc.), and the like. The fare media validator can use the validation rules to determine whether the ticket is being used correctly. 
     At block  320 , the fare media validator determines whether the fare media is valid (being used correctly). If the fare media validator determines that the fare media is valid, the fare media validator validates the fare media at block  325 , and the user passes through an access point associated with the fare media validator at  330 . The granting of passage by the fare media validator may involve causing an associated access control point to move a physical obstacle (such as a gate), enable a physical obstacle (such as a turnstile) to be moved by the user, show the user an indication that the ticket is valid (by flashing a light, displaying a message, etc.), and the like. 
     If the fare media validator determines that the fare media is not valid, the fare media validator does not validate the fare media at  335 , and the user is correspondingly denied entry at the associated access control point block  340 . The fare media validator may cause the access control point to deny the user passage through fare media validator my not moving a physical obstacle (such as a gate), placing a physical obstacle in front of the user to prohibit the user&#39;s passage, locking or otherwise restricting a physical obstacle (such as a turnstile) so that it cannot be moved (or cannot be moved easily) by the user, showing the user an indication that the ticket is not valid (by flashing a light, displaying a message, etc.), and the like. 
     At block  345  the fare media validator further sends rejected transaction information to the server. This rejected transaction information may include an indication of the denial of passage of the user as well as information regarding the fare media (such as information read from the fare media at block  310 ). As noted above, the fare media validator can send the rejected transaction information after each denial of passage of a user, or it can send the rejected transaction information as part of a larger transmission of data that may include information for a plurality of rejected transactions by the fare media validator. The larger transmission may be sent periodically, on a schedule, based on the triggering event (such as receiving a threshold number of rejected transactions), and the like. 
     At block  350 , the server gathers the rejected transaction information from the fare media validator. Here, the server may, over a period of time, gather rejected transaction information from a plurality of fare media validators located throughout the transit system. In so doing, the server is able to determine whether larger trends are occurring within the transit system they can be alleviated through the change of validation rules, or whether a particular fare media validator may be having difficulties validating tickets. 
     At block  355 , the server determines a validation rule change based on the rejected transaction information (which may include a rejected transaction information from a plurality of fare media validators within the transit system). The functionality at block  355  may be triggered by a variety of triggering events. For example, the server may determine to perform the functionality of block  355  after having received a threshold number of rejected transactions. 
     The determination of a validation rule change may be made in accordance with predetermined business rules, depending on desired functionality. This determination may be based on an identifiable common feature among the rejected transactions of the rejected transaction information. For example, the server may, upon receiving a threshold number of rejected transactions, analyze the rejected transaction information to determine that a threshold number of non-peak-time tickets have been rejected at validators during designated peak times within the transit system. After identifying a common feature (the tickets are non-peak-time tickets) among a threshold number of the rejected transactions, the server can use business rules to determine whether to allow these non-peak-timed tickets at validators within the transit system during designated peak times. Depending on the governing business rules, the server may determine a validation rule change based on determining times at which the rejected transactions were made. (If, for example, a threshold number of the rejected transactions were made within a certain window during the designated peak times, the validation rule change could, if implemented, allow these non-peak-time tickets to be validated at fare media validators within the transit system during this window.) Alternatively, the server may determine a validation rule change based on times during which the field tickets are valid. (If, for example, a threshold number of the non-peak-time tickets are valid between 9:00 AM and 4:00 PM, the server may determine a validation rule change that would extend this window so that the rejected tickets would be valid from 8:30 AM to 4:30 PM.) 
     Depending on the various factors used in the determination by the server, the validation rule changes may apply to only a portion of the fare media validators within the transit system. For example, the validation rule change may be applicable only to fare media validators within a certain zone or region of the transit system, or may only impact fare media validators along a particular train line or at a particular station. Accordingly, in some embodiments, the validation rule changes made to be propagated only to those fare media validators that are impacted by the validation rule changes. In other embodiments, the validation rule changes may nonetheless be propagated to all fare media validators within a transit system. However the validation rule changes may identify the fare media validators that are affected, thereby enabling fare media validators that are not affected by the validation rule changes to ignore them. 
     In determining a validation rule change at block  355 , the server can identify any of a variety of common characteristics among the fare media of the rejected transaction information. These characteristics can include, for example, any of the information read from the fare media, ticket type, concessions, special rules, and the like. These characteristics may also include information known by the transit system that may be identified using the information read from the fare media. This can include, for example, an encryption key used in a bar code or similar tickets. In this case, the server may identify the various fare media used in the rejected transactions (and perhaps also determine from the rejected transaction information that transactions were determined to be invalid due to an inaccurate encryption key) and determine that the common encryption key is used to decrypt all of the fare media of the rejected transactions during validation. In these cases, the server me suggest a validation rule change that includes using a different encryption key. 
     Optionally, at block  360 , the server will provide proposed validation rule change information for human review, and receive authorization from the human. As indicated in  FIG. 2A  discussed previously, the proposed validation rule change information can be presented to a transit system operator (or other human overseeing the change of validation rules) using a backend interface  270 . Other information, such as a ticket rejection report  230  may also be presented to help the human operator determine whether suggested validation rule changes should be implemented. Once authorization is received, the process may proceed to block  365 . (If authorization is not received, and the process shown in  FIG. 3  may end at this point.) 
     Authorization can be received in any of a variety of ways, depending on desired functionality. In some embodiments, for example, a human operator may provide an authorization input via a user interface (such as the backend interface  270  of  FIG. 2A ), by pressing a button, selecting an item on a touchscreen, or interacting similarly with the user interface. 
     At block  365 , the server sends the new validation rules to the fare media validators of the transit system. Here, the “new validation rules” may include a set of all validation rules (i.e., “base data”) including the validation rule change determined at block  355 . (Alternatively, according to some embodiments, the “new validation rules” of blocks  365  may include only validation rules impacted (e.g., added or changed) by the validation rule change of blocks  355 .) As noted previously, the propagation of the new validation rules may vary, depending on the desired functionality of the embodiment. In some embodiments, for example, the new validation rules may be sent to all fare media validators within the transit system. In some embodiments, the new validation rules may be sent only to those fare media validators impacted by the validation rule changes embodied by the new validation rules. 
     At block  370  the fare media validator receives and stores a new set of validation rules. As suggested above, the fare media validator may be one of many fare media validators within the transit system that received the new validation rules. Once these validation rules are received and stored by the fare media validator, the fare media validator can then use these new validation rules during the subsequent validation of fare media presented at the fare media validator. 
       FIG. 4  is a flow diagram illustrating a method  400  of automatically determining a validation rule change within a transit system, according to one embodiment. The method may be performed by a server within a transit system, such as the server of  FIG. 3  and/or the backend system  120  of  FIG. 1 . Means for performing the functions illustrated in the method  400  can include hardware and/or software components as illustrated below in  FIG. 5 . 
     At block  410 , a plurality of rejected transactions is obtained from one or more fare media validators of a transit system. As indicated previously, fare media validators may be incorporated into access control points (e.g., turnstiles, gates, and the like), handheld validation devices used by transit operators (e.g., to validate fare media on a train), and the like. As indicated in the embodiments discussed above, the server can obtain these rejected transactions from the one or more fare media validators via a data communication network over a period of time. Each rejected transaction of the plurality of rejected transactions can be indicative of when a fare media was not able to be validated by one of the one or more fare media validators of the transit system. Traditional transit systems may not be configured to collect rejected transaction information in this manner (other than, perhaps, collecting a log locally at the fare media validator). Thus, the fare media validators of the system (and, correspondingly, the server and/or other devices performing the functions of the method  400  of  FIG. 4 ) may need to be configured differently than in traditional transit systems to execute embodiments described herein. It will be appreciated by a person of ordinary skill in the art that the techniques described herein can provide for a more efficient manner of identifying and correcting problems and validation rules, thereby increasing the efficiency of one or more devices within the transit system. It can be further appreciated the techniques provided herein are not simply automating previously-known techniques for validation rule changes. The processes of gathering data from fare media validators and conducting the analyses described herein, along with propagating the validation rules in the manner described in the disclosed techniques, are individually and/or collectively unique. 
     At block  420 , the plurality of rejected transactions is analyzed to determine at least one common characteristic among all rejected transactions of the plurality of rejected transactions causing, at least in part, the rejection of each rejected transaction of the plurality of rejected transactions. As noted above, this common characteristic can include any of a variety of different characteristics that caused (at least in part) the rejection of the transactions. This includes information read from the fare media (e.g., ticket type, concession, etc.) and/or information determined separately (e.g., an encryption key), based on the information read from the fare media. 
     At block  430 , a validation rule change is determined based on the analysis. Here, the validation rule change as a change in one or more validation rules used by the one or more fare media validators of the transit system, and the validation rule change, when implemented by the one or more fare media validators of the transit system, would cause the one or more fare media validators of the transit system to allow future transactions having the at least one common characteristic, resulting in the validation of a fare media by one of the one or more fare media validators of the transit system. 
     At block  440  information indicative of the validation rule change is sent to the one or more fare media validators. Here, sending the information may be direct or indirect, depending on desired functionality. In the previously-described in embodiments, for example, a server (e.g., backend server) may send new validation rules indicative of the validation rule change to fare media validators via the data communication network in which information is relayed to the fare media validators by a station server. 
     It will be understood that embodiments may implement additional or alternative features to those shown in the method  400  of  FIG. 4 . Alternative embodiments can, for example, add, omit, combine, and/or separate functions shown in  FIG. 4 , or perform two or more of them simultaneously. A person of ordinary skill in the art will recognize many variations to the method  400  shown in  FIG. 4 . 
     Depending on desired functionality, the method  400  can include additional features. In some embodiments, for example, the method may include generating a report for review by a user, and sending the information indicative of the validation rule based on an authorization input from the user. An authorization input may be received via a backend interface as described in embodiments above. In some embodiments, prior to analyzing the plurality of rejected transactions, the method may further comprise determining that the plurality of rejected transactions comprises at least a threshold number of rejected transactions and/or determining that the plurality of rejected transactions occurred within a threshold period of time. The least one common characteristic can include any of a variety of characteristics as detailed in the previously-described embodiments. These characteristics can include, for example, a time period during which a fare media is valid, a date during which a fare media is valid, a location in which a fare media is valid, an encryption key of a fare media, a concession related to a fare media, a fare media type, or any combination thereof. Obtaining the plurality of rejected transactions may comprise obtaining them from a remote database, such as a rejected transaction store  210  as described in  FIG. 2A . Additionally or alternatively, the plurality of rejected transactions may be obtained from the one or more fare media validators in the transit system over a period of time (either directly or indirectly via the data communication network). 
       FIG. 5  illustrates an embodiment of a computer system  500 , which may be incorporated, at least in part, into a backend system  120  or station server  140  described in  FIG. 1 , a backend interface  270  of  FIG. 2A , a server of  FIG. 3 , other computing devices in the embodiments disclosed herein, and/or a computing device incorporated and/or communicatively connected therewith, as described herein.  FIG. 5  provides a schematic illustration of one embodiment of a computer system  500  that can perform the methods provided by various other embodiments, such as the method described in relation to  FIG. 4 . It should be noted that  FIG. 5  is meant only to provide a generalized illustration of various components, any or all of which may be utilized as appropriate.  FIG. 5 , therefore, broadly illustrates how individual system elements may be implemented in a relatively separated or relatively more integrated manner. In addition, it can be noted that components illustrated by  FIG. 5  can be localized to a single device and/or distributed among various networked devices, which may be disposed at different physical locations. 
     The computer system  500  is shown comprising hardware elements that can be electrically coupled via a bus  505  (or may otherwise be in communication, as appropriate). The hardware elements may include processing unit(s)  510 , which may comprise without limitation one or more general-purpose processors, one or more special-purpose processors (such as digital signal processing chips, graphics acceleration processors, and/or the like), and/or other processing structure, which can be configured to perform one or more of the methods described herein, including the method described in relation to  FIG. 4 . The computer system  500  also may comprise one or more input devices  515 , which may comprise without limitation a mouse, a keyboard, a camera, a microphone, and/or the like; and one or more output devices  520 , which may comprise without limitation a display device, a printer, and/or the like. 
     The computer system  500  may further include (and/or be in communication with) one or more non-transitory storage devices  525 , which can comprise, without limitation, local and/or network accessible storage, and/or may comprise, without limitation, a disk drive, a drive array, an optical storage device, a solid-state storage device, such as a random access memory (“RAM”), and/or a read-only memory (“ROM”), which can be programmable, flash-updateable, and/or the like. Such storage devices may be configured to implement any appropriate data stores, including without limitation, various file systems, database structures, and/or the like. 
     The computer system  500  might also include a communications subsystem  530 , which may comprise wireless communication technologies managed and controlled by a wireless communication interface  533 , as well as wired technologies. As such, the communications subsystem may comprise a modem, a network card (wireless or wired), an infrared communication device, a wireless communication device, and/or a chipset (such as a Bluetooth™ device, an IEEE 802.11 device, an IEEE 802.15.4 device, a WiFi device, a WiMax device, cellular communication facilities, etc.), and/or the like. The communications subsystem  530  may include one or more input and/or output communication interfaces, such as the wireless communication interface  533 , to permit data to be exchanged with a network, other computer systems, and/or any other electronic devices described herein. 
     In many embodiments, the computer system  500  will further comprise a working memory  535 , which may comprise a RAM or ROM device, as described above. Software elements, shown as being located within the working memory  535 , may comprise an operating system  540 , device drivers, executable libraries, and/or other code, such as one or more applications  545 , which may comprise computer programs provided by various embodiments, and/or may be designed to implement methods, and/or configure systems, provided by other embodiments, as described herein. Merely by way of example, one or more procedures described with respect to the method(s) discussed above, such as the method described in relation to  FIG. 4 , might be implemented as code and/or instructions executable by a computer (and/or a processing unit within a computer); in an aspect, then, such code and/or instructions can be used to configure and/or adapt a general purpose computer (or other device) to perform one or more operations in accordance with the described methods. For example, the computer system  500  and software elements can be used to gather rejected transaction information and determine a validation rule change (or a new set of base data) as described herein. A fare media validator may also incorporate one or more components of the computer system  500  and software elements to be able to read fare media information, perform validation, and/or implement validation rules, as described herein. 
     A set of these instructions and/or code might be stored on a non-transitory computer-readable storage medium, such as the storage device(s)  525  described above. In some cases, the storage medium might be incorporated within a computer system, such as computer system  500 . In other embodiments, the storage medium might be separate from a computer system (e.g., a removable medium, such as an optical disc), and/or provided in an installation package, such that the storage medium can be used to program, configure, and/or adapt a general purpose computer with the instructions/code stored thereon. These instructions might take the form of executable code, which is executable by the computer system  500  and/or might take the form of source and/or installable code, which, upon compilation and/or installation on the computer system  500  (e.g., using any of a variety of generally available compilers, installation programs, compression/decompression utilities, etc.), then takes the form of executable code. 
     It will be apparent to those skilled in the art that substantial variations may be made in accordance with specific requirements. For example, customized hardware might also be used, and/or particular elements might be implemented in hardware, software (including portable software, such as applets, etc.), or both. Further, connection to other computing devices such as network input/output devices may be employed. 
     With reference to the appended figures, components that may comprise memory may comprise non-transitory machine-readable media. The term “machine-readable medium” and “computer-readable medium” as used herein, refer to any storage medium that participates in providing data that causes a machine to operate in a specific fashion. In embodiments provided hereinabove, various machine-readable media might be involved in providing instructions/code to processing units and/or other device(s) for execution. Additionally or alternatively, the machine-readable media might be used to store and/or carry such instructions/code. In many implementations, a computer-readable medium is a physical and/or tangible storage medium. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Common forms of computer-readable media include, for example, magnetic and/or optical media, any other physical medium used for storing data, a RAM, a PROM, EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read instructions and/or code. 
     The methods, systems, and devices discussed herein are examples. Various embodiments may omit, substitute, or add various procedures or components as appropriate. For instance, features described with respect to certain embodiments may be combined in various other embodiments. Different aspects and elements of the embodiments may be combined in a similar manner. The various components of the figures provided herein can be embodied in hardware and/or software. Also, technology evolves and, thus, many of the elements are examples that do not limit the scope of the disclosure to those specific examples. 
     It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, information, values, elements, symbols, characters, variables, terms, numbers, numerals, or the like. It should be understood, however, that all of these or similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as is apparent from the discussion above, it is appreciated that throughout this Specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” “ascertaining,” “identifying,” “associating,” “measuring,” “performing,” or the like refer to actions or processes of a specific apparatus, such as a special purpose computer or a similar special purpose electronic computing device. In the context of this Specification, therefore, a special purpose computer or a similar special purpose electronic computing device is capable of manipulating or transforming signals, typically represented as physical electronic, electrical, or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the special purpose computer or similar special purpose electronic computing device. 
     Various components may be described herein as being “configured” to perform various operations. Those skilled in the art will recognize that, depending on implementation, such configuration can be accomplished through design, setup, placement, interconnection, and/or programming of the particular components and that, again depending on implementation, a configured component might or might not be reconfigurable for a different operation. 
     Terms, “and” and “or” as used herein, may include a variety of meanings that also is expected to depend at least in part upon the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B, or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B, or C, here used in the exclusive sense. In addition, the term “one or more” as used herein may be used to describe any feature, structure, or characteristic in the singular or may be used to describe some combination of features, structures, or characteristics. However, it should be noted that this is merely an illustrative example and claimed subject matter is not limited to this example. Furthermore, the term “at least one of” if used to associate a list, such as A, B, or C, can be interpreted to mean any combination of A, B, and/or C, such as A, AB, AA, AAB, AABBCCC, etc. 
     While the principles of the disclosure have been described above in connection with specific embodiments, it is to be clearly understood that this description is made only by way of example and not as limitation on the scope of the disclosure. Additional implementations and embodiments are contemplated. For example, the techniques described herein can be applied to various forms of optical devices, which may comprise a smaller portion of a larger optical system. Yet further implementations can fall under the spirit and scope of this disclosure.