DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Note on How the Claims are Patent-Eligible under 35 U.S.C. § 101
The independent claims 1, 15, and 20 are directed to an improvement to technology or technical field. The specification filed 13 March 2023 (“the Specification”) at ¶ [0002] states that the disclosure provides “effective, efficient, scalable, and convenient technical solutions that address and overcome the technical problems associated with validation of ATMs.” Claims 1, 15, and 20 claim an invention that “overcome[s] the issues associated with [the] physical validation process (e.g., poor efficiency, the significant length of time needed to validate, resources needed for the ATM servicer to physically validate the ATM, and/or other issues)” (¶[0017] of the Specification). Claims 2-14 and 16-19 are dependent directly or indirectly on claims 1, 15, and 20 and are also eligible for at least this reason.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-11 and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over TANG (CN 113191880 A to TANG, JIE-CONG et al.) in view of LAVIGNE (US 20160379433 A1 to Lavigne; Matthew O. et al.).
Regarding claim(s) 1, 15, and 20,
TANG discloses:
A computing platform comprising: at least one processor; a communication interface communicatively coupled to the at least one processor; and memory storing computer-readable instructions that, when executed by the at least one processor, (TANG: ¶[0166]: As shown in FIG. 8, the electronic device 600 may include a central processing unit 100 and a memory 140; the memory 140 is coupled to the central processing unit 100. It is worth noting that this figure is exemplary; other types of structures can also be used to supplement or replace this structure to achieve telecommunication functions or other functions; ¶[0043]: At the same time, the present invention also provides a computer device, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, and the processor implements the above method when the computer program is executed.; ¶[0044]: At the same time, the present invention also provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program for executing the above method.)
cause the computing platform to: train, based on historical configuration information, a reconfiguration model, wherein training the reconfiguration model configures the reconfiguration model to output, for an automated teller machine (ATM), sets of configuration instructions (TANG: ¶[0022]: performing machine learning to establish a banknote adding suggestion model based on the historical terminal device banknote adding feature data and historical banknote adding plan data obtained in advance; [0023] Using the pre-acquired historical terminal device banknote adding feature data as an input feature, and the historical banknote adding plan data as a predictive label to train a candidate machine learning model for preset hyperparameters; ¶[0080]: performing machine learning to establish a banknote adding suggestion model based on the historical terminal device banknote adding feature data and historical banknote adding plan data obtained in advance; which includes:[0083] Using the pre-acquired historical terminal device banknote adding feature data as an input feature, and the historical banknote adding plan data as a predictive label to train a candidate machine learning model for preset hyperparameters; [0084] Determining a preferred machine learning model from the candidate machine learning models according to the model training result; [0085] The banknote addition suggestion model is determined according to the preset weight setting and the determined preferred machine learning model.);
receive, from a first ATM comprising a plurality of cassettes, wherein each of the plurality of cassettes comprises a corresponding cassette mode, a first information stream; (TANG: ¶[0012]: Obtain the terminal equipment attribute data of the bank teller terminal, the information of the banknote adding personnel and the preset banknote adding plan data of the bank teller terminal to be added; ¶[0061]: Obtain the terminal device attribute data of the bank teller terminal, the information of the banknote adding personnel, and the preset banknote adding plan data of the bank teller terminal to be added; ¶[0015]: the terminal device attribute data includes: terminal transaction data, weather data at the location of the terminal device, date of adding money, pay day and repayment date data; [0149] The interaction module 701 is used to obtain the terminal device attribute data of the bank teller terminal, the information of the banknote adding personnel, and the preset banknote adding plan data of the bank teller terminal to be added) (TANG teaches the limitations in bold, the remaining limitations are addressed by additional reference(s) in the discussion, below)
receive, from one or more sources associated with the first ATM, one or more additional information streams (TANG: ¶[0012]: Obtain the terminal equipment attribute data of the bank teller terminal, the information of the banknote adding personnel and the preset banknote adding plan data of the bank teller terminal to be added; ¶[0061]: Obtain the terminal device attribute data of the bank teller terminal, the information of the banknote adding personnel, and the preset banknote adding plan data of the bank teller terminal to be added; ¶[0015]: the terminal device attribute data includes: terminal transaction data, weather data at the location of the terminal device, date of adding money, pay day and repayment date data; [0149] The interaction module 701 is used to obtain the terminal device attribute data of the bank teller terminal, the information of the banknote adding personnel, and the preset banknote adding plan data of the bank teller terminal to be added; ¶[0104]: The preprocessing module 2, the data entry of the intelligent model of the ATM equipment banknote adding design assistance system, will provide formatted data for the cluster analysis module 3 and the prediction algorithm module 4. The data required by the ATM equipment banknote design assistance system is diverse, including not only ATM transaction data, weather, holidays, payday repayment dates, and other basic characteristics of ATM that affect ATM cash usage, but also the manpower of business personnel The basic characteristic data of the personnel such as resource number, working life, professional, etc., and the amount of money added by the business personnel.);
generate, based on inputting the first information stream and the one or more additional information streams into the reconfiguration model, a first set of configuration instructions for the first ATM (TANG: ¶[0014]: According to the terminal device banknote adding feature data, the preset banknote adding plan data and the pre-trained banknote adding suggestion model, the terminal banknote adding plan suggestion data is determined; wherein, the banknote adding suggestion model is based on the terminal characteristic data obtained in advance A model established by machine learning with the characteristic data of the banknote adding personnel.; ¶[0105]: the banknote adding plan suggestion data processing is performed to generate banknote adding plan data for a certain ATM machine, and the banknote adding designer chooses to add 100,000 banknotes tomorrow. Through the input data model analysis and forecast, it may output the suggestion "recommendation to increase the amount by 50,000" and so on. Suggestions on the adjustment of the amount of banknotes, and guide the designers of banknotes to add banknotes; ¶[0141]: The plan suggestion generating unit 44 will interact with the preprocessing module 2 and the cluster analysis module 3 to obtain ATM basic characteristic data, high-level characteristic data, and expert characteristic data according to the ATM device number, and finally call the model to predict the banknote addition plan suggestion);
cause, based on the first set of configuration instructions, reconfiguration of the first ATM, wherein the reconfiguration of the first ATM comprises one or more of: setting, for one or more of the plurality of cassettes, one or more cassette thresholds, wherein each of the one or more cassette thresholds corresponds to a particular type of bill, or modifying, for one or more of the plurality of cassettes, the corresponding cassette mode (TANG: ¶[0045]: provides the business personnel in the design process of the banknote replenishment plan. Provide auxiliary equipment management evaluation suggestions, guide business personnel to optimize ATM banknote addition plan, improve the accuracy of banknote addition plan, and directly improve the equipment management level of business personnel.; ¶[0064]: automatically provides equipment management evaluation suggestions, directly improves the equipment management level of business personnel; ¶[0105]: Through the input data model analysis and forecast, it may output the suggestion "recommendation to increase the amount by 50,000" and so on. Suggestions on the adjustment of the amount of banknotes, and guide the designers of banknotes to add banknotes) (TANG teaches the limitations in bold, the remaining limitations are addressed by additional reference(s) in the discussion, below);
and refine the reconfiguration model based on the first set of configuration instructions (TANG ¶[0092]: the prediction result of the single algorithm model continuously has abnormal deviations exceeding the preset number of days, then the single algorithm model is removed from the preferred machine Excluded from the learning model; ¶[0093]: if the error between the predicted value and the true value is higher than 150 of the average error in the training data %, the model is kicked out of the preferred model list, and the single-algorithm model is retrained; ¶[0142]: The self-updating module 5 will trigger the retraining of the intelligent model according to certain rules to achieve the effect of automatic model update; ¶[0146]: the self-updating module will adjust the weight parameters of the combined model, that is, retrain the linear regression model.).
TANG does not expressly disclose cassettes or the following limitations, which are taught by LAVIGNE:
from a first ATM comprising a plurality of cassettes (LAVIGNE: [0004]: Banknote recyclers are typically used in retail, banking, automated teller machines and other cash-based operations where banknotes of various denominations are validated, counted and sorted for subsequent use. For example, a retail or banking cashier at the beginning of a shift requires an amount of bills in various denominations to use in a cash till drawer for dispensing change to customers. A typical banknote recycler has provisions for accepting banknotes of mixed denomination and then separating, validating, counting and sorting the banknotes. The accepted notes of each denomination are then placed into various recycling cassettes configured to receive that specific denomination. These recycling cassettes are capable of dispensing stored notes for use by the store in its operation, which is why they are called recycling cassettes. Low-quality notes and notes of denominations with no recycler cassette configured to accept that denomination are placed into one or more deposit cassettes, where they remain until picked up by a cash-in-transit courier or by the responsible party of the recycler who removes the bills for deposit.),
wherein each of the plurality of cassettes comprises a corresponding cassette mode (LAVIGNE ¶[0017]: Banknote recycler 10 shown here has five cassettes (14, 16). In this typical setup, four of the cassettes are configured as recycling cassettes 16 and one is configured as deposit cassette 14. Recycling cassettes 16 are configured to receive banknotes of specific denominations. Typically in this four recycling cassette setup, one recycling cassette 16 will store $1 bills, another $5 bills, another $10 bills and the last $20 bills. Recycling cassettes 16 are capable of dispensing the stored banknotes for re-use by the operator of banknote recycler 10. Deposit cassette 14 houses bills of multiple denominations that are either of low-quality or when there is no recycling cassette configured to accept that denomination (e.g., $100 bill in the above example). Additionally, the operator can control banknote recycler 10 to have recycling cassettes 16 dispense banknotes into deposit cassette 14 to a desired monetary value for subsequent retrieval by the cash-in-transit courier.),
wherein the reconfiguration of the first ATM comprises one or more of: setting, for one or more of the plurality of cassettes, one or more cassette thresholds, wherein each of the one or more cassette thresholds corresponds to a particular type of bill, or modifying, for one or more of the plurality of cassettes, the corresponding cassette mode (LAVIGNE: ¶[0002]: temporarily converting the deposit cassette into a recycling cassette and validating and counting the contents from an additional recycling cassette as it is moved into the converted deposit cassette (i.e., temporary recycling cassette), storing this information in the software and then moving the contents back to the original recycling cassette; ¶[0008]: Next, the software commands the banknote recycler to move the contents of the desired recycling cassette into the empty deposit cassette. The banknote recycler carries out this move, and the contents of the recycling cassette are validated and counted as it is emptied. The count of banknotes is recorded by the operating software. Then, the operating software commands the banknote recycler to temporarily re-configure the recycling and deposit cassettes to allow the banknotes to be moved back from the deposit cassette into the original recycling cassette.; ¶[0004]: The banknote recyclers also have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval by the cash-in-transit courier; ¶[0017]: Additionally, the operator can control banknote recycler 10 to have recycling cassettes 16 dispense banknotes into deposit cassette 14 to a desired monetary value for subsequent retrieval by the cash-in-transit courier.)
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 2 and 16,
As shown, herein, TANG and LAVIGNE teach the limitations of claims 1 and 15.
TANG further discloses:
wherein the one or more sources associated with the first ATM comprise one or more additional ATMs located within a predetermined proximity to the first ATM (TANG: ¶[0127]: In terms of ATM geographic location, ATM equipment can also be divided into urban areas, suburbs, residential areas, commercial areas, etc.; ¶[0130]: The data clustering unit 31 performs clustering processing on ATM category data to reduce the number of categories. The clustering algorithms used by the data clustering unit 31 in this embodiment include but are not limited to common clustering algorithms such as K-Means, EM, DBSCAN, etc. . In this embodiment, through the K-Means algorithm, the basic characteristics of ATM devices are used as input to reduce the category of ATM devices; ¶[0020]: Perform clustering processing on the basic characteristic data of the terminal equipment and the basic characteristic data of the banknote adding personnel to generate clustering characteristic data ).
Regarding claim(s) 3 and 17,
As shown, herein, TANG and LAVIGNE teach the limitations of claims 1 and 15.
TANG further discloses:
wherein the one or more sources associated with the first ATM comprise one or more of: weather reporting services, ATM servicing providers, financial institutions, event notification services, or community notification services (TANG: ¶[0015]: the terminal device attribute data includes: terminal transaction data, weather data at the location of the terminal device, date of adding money, pay day and repayment date data; ¶[0104]: . The data required by the ATM equipment banknote design assistance system is diverse, including not only ATM transaction data, weather, holidays, payday repayment dates, and other basic characteristics of ATM that affect ATM cash usage).
Regarding claim(s) 4,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
wherein the modifying of the corresponding cassette mode comprises, for one or more of the plurality of cassettes, changing the corresponding cassette mode to one of the following: a recycle mode, a deposit mode, a withdrawal mode, or a reject mode (LAVIGNE: ¶[0008]: Then, the operating software commands the banknote recycler to temporarily re-configure the recycling and deposit cassettes to allow the banknotes to be moved back from the deposit cassette into the original recycling cassette; ¶[0004]: These recycling cassettes are capable of dispensing stored notes for use by the store in its operation, which is why they are called recycling cassettes. Low-quality notes and notes of denominations with no recycler cassette configured to accept that denomination are placed into one or more deposit cassettes, where they remain until picked up by a cash-in-transit courier or by the responsible party of the recycler who removes the bills for deposit; ¶[0019]: have the operating software reconfigure the deposit cassette as a temporary recycling cassette because under normal operation, the deposit cassette does not dispense banknotes as is done by the recycling cassettes. Next, the now-empty recycling cassette is reconfigured as a temporary deposit cassette to allow it to accept banknotes from another cassette.).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 5 and 18,
As shown, herein, TANG and LAVIGNE teach the limitations of claims 1 and 15.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
wherein the first information stream comprises one or more of: one or more current bill counts, wherein each of the one or more current bill counts corresponds to a particular cassette of the plurality of cassettes, one or more current bill thresholds, wherein each of the one or more current bill thresholds corresponds to a particular cassette of the plurality of cassettes, or one or more current cassette modes, wherein each of the one or more current cassette modes corresponds to a particular cassette of the plurality of cassettes (LAVIGNE: ¶[0004]: Banknote recyclers are typically used in retail, banking, automated teller machines and other cash-based operations where banknotes of various denominations are validated, counted and sorted for subsequent use; A typical banknote recycler has provisions for accepting banknotes of mixed denomination and then separating, validating, counting and sorting the banknotes; The banknote recyclers also have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval by the cash-in-transit courier. ¶[0018]: Every banknote in the selected recycling cassette is transported from the recycling cassette into the deposit cassette. In the preferred embodiment, as the banknotes are dispensed from the recycling cassette, they are counted as they are moved into the deposit cassette. This count is recorded by the operating software; At this point in the process, the deposit cassette is now storing the contents of the selected recycling cassette, which is now empty and the operating software has recorded the number of banknotes that were housed in the recycling cassette.; ¶[0019]: Because the notes were counted as they were being transported in the first portion of the self-audit in the preferred embodiment, there is no need to count the bills again as they are being moved back. However, in an alternative embodiment, the notes can be again counted, and the count is again recorded by the operating software. In a further alternative embodiment, the notes could be transported in the first portion without counting and only be counted as they are being transported back in the second portion of the self-audit. Once the contents of the original recycling cassette are back in the original recycling cassette, the operating software reconfigures it back from the temporary deposit cassette into the original recycling cassette).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 6 and 19,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG further discloses:
wherein the one or more additional information streams comprises one or more: one or more current bill thresholds corresponding to one or more additional ATMs, one or more current cassette modes corresponding to one or more additional ATMs, current weather information, servicing information corresponding to the first ATM, current event information for a geographical region corresponding to the first ATM, configuration preferences corresponding to a financial institution associated with the first ATM, or community information for a geographical region corresponding to the first ATM (TANG: ¶[0015]: the terminal device attribute data includes: terminal transaction data, weather data at the location of the terminal device, date of adding money, pay day and repayment date data; ¶[0134]: If a certain type of ATM machine is a machine with a large amount of cash withdrawal on weekdays, but the geographic location is next to the software science and technology park, in the embodiment of the present invention, a higher value will be set for the magnitude of the holiday influence of this type of machine according to the transaction flow; ¶[0127]: the ATM device has many unique data attributes. In terms of the amount of ATM transactions, ATM devices can be divided into large deposits, larger deposits, smaller deposits, and almost no deposits based on the amount of deposits. In the same way, ATMs can also be classified from the perspective of the amount of withdrawals and the amount of netting of deposits and withdrawals. In terms of ATM geographic location, ATM equipment can also be divided into urban areas, suburbs, residential areas, commercial areas, etc ).
Regarding claim(s) 7,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: receive, from an enterprise user device corresponding to an enterprise associated with the first ATM, a request to validate the first ATM; and request, based on the request to validate the first ATM, the first information stream from the first ATM (LAVIGNE: ¶[0008]: The desire to perform a self-audit is either entered by the operator of the banknote recycler (locally at the machine or remotely via an internet connection); ¶[0018]: Once the deposit cassette is empty, the operating software begins the self-audit process for the selected recycling cassette. Every banknote in the selected recycling cassette is transported from the recycling cassette into the deposit cassette. In the preferred embodiment, as the banknotes are dispensed from the recycling cassette, they are counted as they are moved into the deposit cassette. This count is recorded by the operating software. Additionally, the notes can be validated as they are transported from the recycling cassette into the deposit cassette).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 8,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: identify, based on an updated information stream received from the first ATM, a reconfiguration result, wherein the reconfiguration result indicates whether or not the first ATM is validated (LAVIGNE: ¶[0018]: , as the banknotes are dispensed from the recycling cassette, they are counted as they are moved into the deposit cassette. This count is recorded by the operating software. Additionally, the notes can be validated as they are transported from the recycling cassette into the deposit cassette.; ¶[0019]: the operating software reconfigures it back from the temporary deposit cassette into the original recycling cassette. Likewise, once the original deposit cassette is empty, the operating software reconfigures it back from the temporary recycling cassette into the original deposit cassette; ¶[0002]: banknote recycler self-audit[s] to determine the contents of the banknote recycler.; ¶[0005]: performing a self-audit wherein the current contents of each recycling cassette can be validated and counted automatically).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 9,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1 and 8.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
herein the causing the reconfiguration of the first ATM is based on identifying that the reconfiguration result indicates that the first ATM is validated (LAVIGNE: [0002]: a banknote recycler to self-audit to determine the contents of the banknote recycler; [0008]: The desire to perform a self-audit is either entered by the operator of the banknote recycler (locally at the machine or remotely via an internet connection) or automatically triggered by an event such as removal of a recycle cassette, accounting discrepancy or other security event. Once the deposit cassette is emptied, it can then be used as a temporary recycling cassette and the self-audit of the requested recycling cassettes can begin; [0018]: as the banknotes are dispensed from the recycling cassette, they are counted as they are moved into the deposit cassette. This count is recorded by the operating software. .; [0019]: the second portion of the self-auditing method for banknote recycler 10 of the present invention is shown. The first step of the second portion of the self-auditing method is to have the operating software reconfigure the deposit cassette as a temporary recycling cassette because under normal operation, the deposit cassette does not dispense banknotes as is done by the recycling cassettes. [...] Once the contents of the original recycling cassette are back in the original recycling cassette, the operating software reconfigures it back from the temporary deposit cassette into the original recycling cassette.).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 10,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG further discloses:
wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to automatically request, based on identifying that a predetermined period of time has elapsed, the first information stream from the first ATM (TANG: ¶[0093]: If the last training time of the single-algorithm model reaches the preset maximum value […] the model is kicked out of the preferred model list, and the single-algorithm model is retrained; the single-algorithm model can be is self-updating and the linear regression model retrained. ¶[0027]: It is determined that the training time of the single model in the preferred machine learning model is greater than the preset time threshold or the prediction result of the single algorithm model continuously has abnormal deviations exceeding the preset number of days, then the single algorithm model is removed from the preferred machine/Excluded from the learning model; [0014] the banknote adding suggestion model is based on the terminal characteristic data obtained in advance; [0015] In the embodiment of the present invention, the terminal device attribute data includes: terminal transaction data, weather data at the location of the terminal device, date of adding money, pay day and repayment date data).
Regarding claim(s) 11,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG further discloses:
wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, (TANG: ¶[0166]: As shown in FIG. 8, the electronic device 600 may include a central processing unit 100 and a memory 140; the memory 140 is coupled to the central processing unit 100. It is worth noting that this figure is exemplary); cause the computing platform to:
cause, based on the first set of configuration instructions, a service device associated with the first ATM to update a service schedule corresponding to the first ATM (TANG: ¶[0012]: Obtain the preset banknote adding plan data; ¶[0014]: the terminal banknote adding plan suggestion data is determined according to the “the preset banknote adding plan data and the pre-trained banknote adding suggestion model”);
and send, to the service device, one or more display commands, wherein the one or more display commands cause the service device to display a user interface comprising information of the first ATM and the updated service schedule (TANG: ¶[0147]: According to the historical difference between the ATM banknote replenishment plan designed by the business staff and the actual amount consumed, during the design process of the banknote replenishment plan, the business personnel are provided with auxiliary equipment management evaluation suggestions to guide the business personnel to optimize the ATM banknote replenishment plan; ¶[0175]: The display 160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but it is not limited thereto.; figure 8 item 160 display; ¶[0105]: Through the input data model analysis and forecast, it may output the suggestion "recommendation to increase the amount by 50,000" and so on. Suggestions on the adjustment of the amount of banknotes, and guide the designers of banknotes to add banknotes.)
Regarding claim(s) 13,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
wherein the causing the reconfiguration of the first ATM comprises automatically reconfiguring the first ATM (LAVIGNE: ¶[0006]: performing [without] involve[ing] the assistance by a human operator of the banknote recycler; ¶[0007]: perform […] without the assistance of a human operator; ¶[0019]: operating software reconfigures the deposit cassette; recycling cassette is reconfigured).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Regarding claim(s) 14,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG further discloses:
wherein the causing the reconfiguration of the first ATM comprises: sending, to an enterprise user device associated with the first ATM, one or more commands to display a user interface, wherein the user interface comprises the first set of configuration instructions and an updated information stream (TANG: ¶[0147]: According to the historical difference between the ATM banknote replenishment plan designed by the business staff and the actual amount consumed, during the design process of the banknote replenishment plan, the business personnel are provided with auxiliary equipment management evaluation suggestions to guide the business personnel to optimize the ATM banknote replenishment plan; ¶[0175]: The display 160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but it is not limited thereto.; figure 8 item 160 display; ¶[0105]: Through the input data model analysis and forecast, it may output the suggestion "recommendation to increase the amount by 50,000" and so on. Suggestions on the adjustment of the amount of banknotes, and guide the designers of banknotes to add banknotes.;
receiving, from the enterprise user device, an updated set of configuration instructions (TANG: ¶[0172]: the electronic device 600 may further include: a communication module 110, an input unit 120; ¶[0067]: The banknote plan design error provides automatic evaluation and optimization suggestions for the banknote replenishment plan designed by the business personnel, and guides the business personnel to optimize the ATM banknote replenishment plan; ¶[0103]: interactive entrance between user and atm device banknote adding design assistance system, embedded with interactive function of the ATM banknote adding plan design page; […], Obtain quasi-real-time ATM banknote replenishment plan design suggestions for assisting business personnel; ¶[0105]: banknote adding plan suggestion data processing is performed to generate banknote adding plan data for a certain ATM machine, and the banknote adding designer chooses);
TANG does not explicitly teach the following limitations which LAVIGNE teaches:
and reconfiguring, based on the updated set of configuration instructions, the first ATM (LAVIGNE: ¶[0006]: performing [without] involv[ing] the assistance by a human operator of the banknote recycler; ¶[0007]: perform […] without the assistance of a human operator; ¶[0019]: operating software reconfigures the deposit cassette; recycling cassette is reconfigured).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of LAVIGNE, which teaches that banknote cassette recyclers have the capability to move notes from the recycling cassettes to the deposit cassette to raise the content of the deposit cassette to the desired monetary value for subsequent retrieval (LAVIGNE ¶[0004]) and control by an operator of the recycling cassettes to have recycling cassettes dispense banknotes into deposit cassettes to a desired monetary value for subsequent retrieval (LAVIGNE ¶[0017]), in order to save time and labor while managing ATMs (LAVIGNE ¶[0005]) and eliminate the need for human assistance by human operators (LAVIGNE ¶[0006]).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over TANG (CN 113191880 A to TANG, JIE-CONG et al.) in view of LAVIGNE (US 20160379433 A1 to Lavigne; Matthew O. et al.) in further view of KOLLS (US 20220051209 A1 to Kolls; H. Brock et al.).
Regarding claim(s) 12,
As shown, herein, TANG and LAVIGNE teach the limitations of claim 1.
TANG and LAVIGNE do not explicitly teach the following limitations which KOLLS, however, teaches:
wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to cause, based on the first set of configuration instructions, an autonomous vehicle associated with a service provider corresponding to the first ATM to modify a service route corresponding to a plurality of ATMs (KOLLS: ¶[0027]: In accordance with some examples, the route taken by the autonomous vehicle 100 is determined or altered in real time, based on the amount of cash contained in the ATM 130. For instance, the amount of cash contained in the ATM 130 may be compared to a desired cash supply range for the ATM 130, and based on the comparison, subsequent transaction location(s) are determined; ¶[0039]: Additionally, by determining or adjusting the transaction location route in real time based on the amount of cash contained in the ATM, the number of customer stops could be maximized while minimizing trips back to the bank add or remove cash from the ATM 130. This allows fewer autonomous vehicles/ATMs service more customers in a timely manner.); ¶[0039]: “fewer autonomous vehicles/ATMs service more customers” (plurality of ATMs)).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of TANG, which discloses retrieval of cash balances from ATMs (TANG ¶[0096]), systems and methods of determining ATM management suggestions (TANG ¶[0006] and ¶[0009]), using intelligent algorithms to evaluate the priority of ATM equipment replenishment and provide ATM equipment operations for business personnel (TANG ¶[0009]), and using Machine learning to guide addition of banknotes via specific suggestions for adjustments (TANG ¶[0105]) with the technique of KOLLS, in order to save trips and labor and reduce risk while managing cash supplies (KOLLS ¶[0013).
Conclusion
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BOLKO HAMERSKI
Examiner
Art Unit 3694
/BOLKO M HAMERSKI/Examiner, Art Unit 3694
/BENNETT M SIGMOND/Supervisory Patent Examiner, Art Unit 3694