DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/22/2025 has been entered.
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 .
Disposition of Claims
Claims 1-20 are pending in the instant application. No claims have been cancelled. No claims have been added. Claims 1, 11, and 13 have been amended. The rejection of the pending claims is hereby made non-final.
Response to Remarks
103
Due to Applicant’s arguments and amendments the previous office action is now moot and the claims have been given further searching and consideration. Consequently, please find a new rejection below addressing the amended claims.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1-20 are rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-20 of United States Patent No 12,039,395. Although the claims at issue are not identical, they are not patentably distinct from each other because both applications are directed to systems and methods for detecting a skimming device, as outlined below:
US Patent Number 12,039,395
Application number 17/876796
1. A computer-implemented method for detecting mounting of an object at a terminal device, the method comprising the steps of: receiving detection data from one or more sensors; generating a wavelet matrix based on the detection data; generating an ambient environment alert based on the wavelet matrix; and determining based on the detection data a sequence of an approach state during one predetermined time period and an object mounting state during a subsequent predetermined time period.
2. A method as claimed in claim 1 wherein the ambient environment alert comprises an ambient weather alert.
3. A method as claimed in claim 2 wherein the ambient weather alert comprises a rain alert.
4. A method as claimed in claim 1 wherein the detection data is converted from the time domain to the frequency domain using a wavelet transform to generate the wavelet matrix.
5. A method as claimed in claim 1 wherein the method comprises the step of identifying one or more features in the wavelet matrix, the ambient environment alert being generated based on the one or more identified features.
6. A method as claimed in claim 5 wherein the one or more features are identified using a first machine learning model.
7. A method as claimed in claim 6 wherein the first machine learning model comprises a convolutional neural network model.
8. A method as claimed in claim 1 wherein the terminal device comprises an automated teller machine device.
9. A method as claimed in claim 1 wherein the object comprises a card skimmer device.
10. A method as claimed in claim 1 wherein the method comprises the steps of: generating a set of training data; and training at least one of the first machine learning model and the second machine learning model based on the set of training data.
11. A computer-implemented method for detecting mounting of an object at a terminal device, the method comprising the steps of: receiving detection data from one or more sensors; generating a wavelet matrix based on the detection data; generating an ambient environment alert based on the wavelet matrix; and determining based on the detection data a sequence of (i) an idle state during a first time period, (ii) an approach state during a second time period, and (iii) an object mounting state during a third time period.
12. A method as claimed in claim 11 wherein the method comprises the step of generating a tamper alert based on the sequence determination.
13. A method as claimed in claim 11 wherein the detection data has a substantially constant amplitude at a first level during the first time period.
14. A method as claimed in claim 11 wherein the detection data has a negative peak amplitude during the second time period, the negative peak being substantially lower than the first level.
15. A method as claimed in claim 11 wherein the detection data has a substantially constant amplitude at a third level during the third time period, the third level being substantially higher than the first level.
16. A method as claimed in claim 11 wherein the sequence is determined using a second machine learning model.
17. A method as claimed in claim 16 wherein the second machine learning model comprises a deep learning model.
18. A method as claimed in claim 17 wherein the deep learning model comprises a long short-term memory recurrent neural network model.
19. A data processing system for detecting mounting of an object at a terminal device, the system comprising a processor configured to: receive detection data from one or more sensors; generate a wavelet matrix based on the detection data; generate an ambient environment alert based on the wavelet matrix; and determining based on the detection data a sequence of an approach state during one predetermined time period and an object mounting state during a subsequent predetermined time period.
20. A computer program product comprising instructions capable of causing a computer system to perform a method as claimed in claim 1 when the computer program product is executed on the computer system.
1. (Currently Amended) A method for detecting a skimmer located proximate a card reader of a self-service terminal (SST), the method comprising: obtaining a baseline measurement for a plurality of sensors located proximate the card reader, wherein the baseline measurement comprises a default baseline and an active baseline, wherein the active baseline is set equal to the default baseline, and wherein the active baseline is updated continuously to account for environmental changes; activating a subset of the plurality of sensors; receiving a signal from each of the subset of the plurality of sensors that were activated; determining that the skimmer is located proximate the card reader when the signal from each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth, wherein the active baseline is tracked so long as there is no skimmer detected, rain compensation is not activated, and the signal is below a fixed rain stability; wherein each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth; and disabling the self-service terminal in response to determining that the skimmer is located proximate the card reader.
2. (Original) The method of claim 1, wherein obtaining the baseline measurement comprises receiving the baseline measurement from a memory of the self-service terminal.
3. (Original) The method of claim 1, wherein obtaining the baseline measurement comprises receiving a signal from each of the sensors, the signal from each of the sensors representing the baseline measurement.
4. (Original) The method of claim 1, wherein the baseline measurement comprises a capacitance value for each of the plurality of sensors.
5. (Previously Presented) The method of claim 1, wherein the predetermined threshold comprises a change in a capacitance measure over the predetermined time.
6. (Previously Presented) The method of claim 1, wherein activating the subset of the plurality of sensors comprises activating the subset of the plurality of sensors in a round robin manner.
7. (Original) The method of claim 1, wherein disabling the self-service terminal comprise disabling the card reader.
8. (Original) The method of claim 1, further comprising transmitting an alert message.
9. (Original) The method of claim 1, further comprising filtering noise from the signal received from each of the subset of the plurality of sensors.
10. (Original) The method of claim 1, wherein the subset of the plurality of sensors is one of a plurality of subsets of the sensors, each of the plurality of subsets of corresponding to a different test pattern.
11. (Currently Amended) A skimmer detection system comprising: a processor; and a memory storing instructions that, when executed by the processor, causes the processor to perform actions comprising: obtaining a baseline measurement for a plurality of sensors located proximate a card reader of a self-service terminal, wherein the baseline measurement comprises a default baseline and an active baseline, wherein the active baseline is set equal to the default baseline, and wherein the active baseline is updated continuously to account for environmental changes; activating a subset of the plurality of sensors; receiving a signal from each of the subset of the plurality of sensors that were activated; determining that a skimmer is located proximate the card reader when the signal from each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth, wherein the active baseline is tracked so long as there is no skimmer detected, rain compensation is not activated, and the signal is below a fixed rain stability; wherein each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth; and disabling the self-service terminal in response to determining that the skimmer is located proximate the card reader.
12. (Original) The skimmer detection system of claim 11, wherein the baseline measurement comprises a capacitance value for each of the plurality of sensors.
13. (Previously Presented) The skimmer detection system of claim 11, wherein the predetermined threshold comprises a change in a capacitance measure over the predetermined time.
14. (Previously Presented) The skimmer detection system of claim 11, wherein activating the subset of the plurality of sensors comprises activating the subset of the plurality of sensors in a round robin manner.
15. (Original) The skimmer detection system of claim 11, further comprising transmitting an alert message.
16. (Original) The skimmer detection system of claim 11, further comprising filtering noise from the signal received from each of the subset of the plurality of sensors.
17. (Currently Amended) A self-service terminal (SST) comprising: a card reader; a plurality of sensors located proximate the card reader; a processor in electrical communication with the plurality of sensors; and a memory storing instructions that, when executed by the processor, causes the processor to perform actions comprising: receive a baseline measurement for the plurality of sensors from the memory, wherein the baseline measurement comprises a default baseline and an active baseline, wherein the active baseline is set equal to the default baseline, and wherein the active baseline is updated continuously to account for environmental changes; activating a subset of the plurality of sensors; receiving a signal from each of the subset of the plurality of sensors that were activated; determining that a skimmer is located proximate the card reader when the signal from each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth, wherein the active baseline is tracked so long as there is no skimmer detected, rain compensation is not activated, and the signal is below a fixed rain stability; wherein each of the subset of the plurality of sensors deviates from the baseline measurement by a predetermined threshold over a predetermined time for a number of successive rounds, wherein the number of successive rounds comprises a preset depth; and disabling the self-service terminal and transmitting an alert message in response to determining that the skimmer is located proximate the card reader.
18. (Original) The self-service terminal of claim 17, wherein the plurality of sensors comprises a plurality of capacitance sensors and the baseline measurement comprises a capacitance value for each of the plurality of capacitance sensors.
19. (Previously Presented) The self-service terminal of claim 17, wherein activating the subset of the plurality of sensors comprises activating the subset of the plurality of sensors in a round robin manner.
20. (Original) The self-service terminal of claim 17, further comprising filtering noise from the signal received from each of the subset of the plurality of sensors.
The examiner submits that the language as recited in the pending application is similar to that as recited in US Patent number 12,039,395 as shown in the table above, which shows exemplary claims 1-20 of the pending application in view of claims 1-20 of United States Patent Number 12,039,395. For at least the reasoning provided above, a Terminal Disclaimer is required herein.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
The examiner has considered all references listed on the Notice of References Cited, PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TALIA F CRAWLEY whose telephone number is (571)270-5397. The examiner can normally be reached on Monday thru Thursday; 8:30 AM-4:30 PM EST.
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/TALIA F CRAWLEY/Primary Examiner, Art Unit 3627