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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 05/29/2026 has been entered.
Response to Amendments / Arguments
Regarding the rejection(s) of claims under 35 USC 103:
Applicant’s arguments, filed 05/29/2026, in view of the amended claims, have been fully considered and are not persuasive.
Applicant first argues that "Reznik and Cavallini do not disclose 'transmitting, to a network node in a wireless network via a wireless access link, the one or more bits and the liveness indicator,' as recited in amended claim 1," and further that "Cavallini is silent regarding transmitting information (i.e., the alert and/or the parameter scores) with 'network node in a wireless network via a wireless access link,' as recited in amended claim 1."
In response, it is noted that the recited wireless architecture is relied upon from Reznik, not Cavallini. Reznik discloses a wireless transmit/receive unit (WTRU) 502 including a transmit/receive element 522 "configured to transmit signals to, or receive signals from, a base station (e.g., the base station 514 a) over the air interface 515/516/517" ([0089]), where the base stations "may communicate with one or more of the WTRUs 502 a, 502 b, 502 c, 502 d over an air interface 515/516/517, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, infrared (IR), ultraviolet (UV), visible light, etc.)" established "using any suitable radio access technology (RAT)" ([0079]). Base station 514a is a network node of a wireless network as recited, and the air interface is expressly a wireless access link. Reznik further provides that "[u]ser detection and a user's distance to the screen may be provided to be used in adaptive streaming applications to reduce video rate and/or bandwidth usage" ([0031]), such that information related to the liveness determination is communicated to the network.
Secondly, Applicant argues that "even assuming arguendo that the parameter scores of Cavallini disclosed the 'one or more bits' of amended claim 1—which Applicant does not concede to be correct—Cavallini does not describe communicating these scores. At best, Cavallini merely sends an alert to a central post."
In response, Cavallini is relied upon for the contents of the transmitted information, in combination with Reznik's wireless transmission. Cavallini discloses "determining a parameter score relating to a corresponding liveness indicator, and comparing this score with a corresponding threshold to provide a feature evaluation result, which is for example 'TRUE' or 'FALSE' result" ([0063]), each such result being a binary liveness state for a respective input, and discloses that these results are summed and compared to threshold TH to yield an overall liveness determination ([0064]-[0070]). Cavallini further discloses transmitting that liveness determination to a remote node, where "an alert [is] to be sent to a central control post in the case that the presence of a photo in front of camera 112 is detected" via network interface 208, which "may for example provide a wired or wireless connection to a communications network" ([0050]), and where "security personnel may be informed, via the network interface 208 of FIG. 2" ([0069]). Cavallini thus establishes that communicating a liveness determination to a remote node was a known and predictable practice, and one of ordinary skill would transmit Cavallini's binary results and overall determination as the information transmitted over Reznik's existing wireless access link.
Therefore, the identified claim language is considered to be taught by the Reznik-Cavallini combination, and the rejection is maintained. Further, since Applicant has not argued the dependent claims, their rejections are likewise maintained.
DETAILED ACTION
This is a reply to the arguments filed on 05/29/2026, in which, claims 1-7, 9-17 and 19-32 are pending. Claims 1, 11, 21, and 26 are independent. Claims 8 and 18 are cancelled. Claims 31 and 32 are newly added.
When making claim amendments, the applicant is encouraged to consider the references in their entireties, including those portions that have not been cited by the examiner and their equivalents as they may most broadly and appropriately apply to any particular anticipated claim amendments.
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.
Claims 1-7, 10-17, and 20-31 are rejected under 35 U.S.C. 103 as being unpatentable over Reznik et al. (US 20150241962 A1, referred to as Reznik) in further view of Cavallini (US 20150310289 A1, Cavallini).
In reference to claim 1, A method performed by an electronic device, comprising: receiving multiple inputs that each indicate current sensor information related to a liveness state associated with a human user (Reznik: [0030]-[0038] and [0054] Provides for receiving multiple sensor inputs (camera, accelerometer, gyroscope, proximity sensor, etc.) that collectively teach determining whether a user is present and active.)
Wherein the multiple inputs include one or more motion detection inputs, one or more tilt recognition inputs and one or more biometric inputs (Reznik: [0035]-[0038], [0048] and [0064] Provides for motion detection (accelerometer variance), tilt recognition (gyroscope and device orientation/angle detection for viewing posture), and biometric inputs (face detection via camera).)
The one or more biometric inputs comprising a human proximity detection input indicating whether one or more humans are present within a threshold distance of the electronic device (Reznik: [0067]-[0069] Provides for face detection as a biometric input that determines whether a human is present within a defined threshold distance.)
generating, based at least in part on the multiple inputs, liveness information that includes a liveness assessment word (Reznik: [0054]-[0063] Provides for generating a structured output (uad_result_1) based on fused multi-sensor inputs that encodes user presence information.)
a liveness indicator that indicates whether a human user is actively handling the electronic device (Reznik: [0063]-[0065] Provides for detecting and distinguishing whether a user is actively holding/handling the device versus the device being stationary.)
transmitting, to a network node in a wireless network via a wireless access link, information (Reznik: [0031], [0076]-[0079] and [0087]-[0089] Provides for a wireless transmit/receive unit having a transmit/receive element that transmits information to a base station over an air interface expressly described as any suitable wireless communication link established using a radio access technology, and provides for the user detection and face distance determination to be used in adaptive streaming applications to reduce video rate and bandwidth usage, such that information related to that determination is communicated to the network.)
Reznik does not explicitly teach wherein the generating includes one or more bits, wherein each bit of the one or more bits represents the liveness state associated with a respective input of the multiple inputs and wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold. However, Cavallini teaches:
Wherein the generating includes one or more bits, wherein each bit of the one or more bits represents the liveness state associated with a respective input of the multiple inputs (Cavallini: [0063]-[0064] Provides for individual binary (TRUE/FALSE) results for each liveness indicator corresponding to each respective input.)
Wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold (Cavallini: [0064]-[0070] Provides for threshold-based determination that depends on the proportion of liveness indicators returning TRUE out of the total set.)
wherein the transmitted information comprises the one or more bits and the liveness indicator (Cavallini: [0050], [0063]-[0064] and [0069] Provides for individual binary TRUE/FALSE liveness results and an overall liveness determination, and provides for that liveness determination to be transmitted over a network interface to a central control post so that security personnel are informed and manual verification can be performed.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik, which provides a method for receiving multiple sensor inputs including motion, tilt, and biometric data to generate liveness information indicating whether a human user is actively handling an electronic device, with the teachings of Cavallini, which introduces binary bit representation for individual liveness states and ratio-based threshold determination for overall liveness assessment. One of ordinary skill in the art would recognize the ability to incorporate Cavallini's structured binary encoding and statistical threshold approach into Reznik's multi-sensor liveness detection system to provide more robust and quantifiable liveness determination. One of ordinary skill in the art would be motivated to make this modification in order to improve liveness detection accuracy by requiring a statistically significant proportion of sensors to indicate human presence rather than relying on any single input.
In reference to claim 2, The method of claim 1, wherein generating the liveness information includes analyzing the current sensor information associated with one or more of the multiple inputs using a liveness assessment algorithm to determine the liveness state (Reznik: Fig. 6, [0054] and [0066]-[0068] Provides for a defined algorithmic process (fusion logic) that analyzes sensor data.)
In reference to claim 3, The method of claim 1, wherein the liveness information is generated using one or more machine learning models that are trained to detect whether the human user is actively handling the electronic device from the current sensor information (Reznik: [0046] and [0066] Provides for Viola-Jones algorithm, which is a machine-learning-based classifier.)
In reference to claim 4, The method of claim 1, the liveness information associated with the current sensor information is based at least in part on patterns associated with historical sensor information (Reznik: [0053] and [0069]-[0072] Provides for maintaining historical sensor data in circular buffers with timestamps and computing statistics over accumulated samples.)
In reference to claim 5, The method of claim 1, wherein the liveness indicator has a value that is based at least in part on whether a threshold number or a threshold proportion of the multiple inputs indicate that the human user is actively handling the electronic device (Reznik: [0054] and [0065]-[0068] Provides for a fusion logic that requires multiple conditions to be simultaneously satisfied to confirm user presence.)
In reference to claim 6, The method of claim 1, wherein the liveness indicator has a value that indicates a probability that the human user is actively handling the electronic device (Cavallini: [0064]-[0070] Provides for liveness indicator expressed as a numerical score (e.g., 55 out of a possible weighted total) that reflects the degree of confidence in liveness.)
In reference to claim 7,The method of claim 1, wherein the liveness indicator includes a flag that has a first value to indicate that a human user is actively handling the electronic device or a second value to indicate that the electronic device is not being actively handled by a human user (Reznik: [0062]-[0064] Provides for a boolean field “user_detected” that takes one of two values (true/false).)
In reference to claim 10, The method of claim 8, the liveness information is transmitted to the network node in connection with a data campaign to assess usage patterns associated with live human users and simulated human activity (Cavallini: [0050] and [0069]-[0070] Provides for transmitting liveness results to a remote node and for using test data to optimize the system's ability to distinguish live humans from simulated.)
In reference to claim 11, A electronic device for wireless communication, comprising: a memory; and one or more processors, coupled to the memory, configured to: receive multiple inputs that each indicate current sensor information related to a liveness state associated with a human user (Reznik: [0030]-[0038] and [0054] Provides for receiving multiple sensor inputs (camera, accelerometer, gyroscope, proximity sensor, etc.) that collectively teach determining whether a user is present and active.)
Wherein the multiple inputs include one or more motion detection inputs, one or more tilt recognition inputs and one or more biometric inputs (Reznik: [0035]-[0038], [0048] and [0064] Provides for motion detection (accelerometer variance), tilt recognition (gyroscope and device orientation/angle detection for viewing posture), and biometric inputs (face detection via camera).)
The one or more biometric inputs comprising a human proximity detection input indicating whether one or more humans are present within a threshold distance of the electronic device (Reznik: [0067]-[0069] Provides for face detection as a biometric input that determines whether a human is present within a defined threshold distance.)
generating, based at least in part on the multiple inputs, liveness information that includes a liveness assessment word (Reznik: [0054]-[0063] Provides for generating a structured output (uad_result_1) based on fused multi-sensor inputs that encodes user presence information.)
a liveness indicator that indicates whether a human user is actively handling the electronic device (Reznik: [0063]-[0065] Provides for detecting and distinguishing whether a user is actively holding/handling the device versus the device being stationary.)
Reznik does not explicitly teach wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective input of the multiple inputs and wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold. However, Cavallini teaches:
Wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective inpute of the multiple inputs (Cavallini: [0063]-[0064] Provides for individual binary (TRUE/FALSE) results for each liveness indicator corresponding to each respective input.)
Wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold (Cavallini: [0064]-[0070] Provides for threshold-based determination that depends on the proportion of liveness indicators returning TRUE out of the total set.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik, which provides a method for receiving multiple sensor inputs including motion, tilt, and biometric data to generate liveness information indicating whether a human user is actively handling an electronic device, with the teachings of Cavallini, which introduces binary bit representation for individual liveness states and ratio-based threshold determination for overall liveness assessment. One of ordinary skill in the art would recognize the ability to incorporate Cavallini's structured binary encoding and statistical threshold approach into Reznik's multi-sensor liveness detection system to provide more robust and quantifiable liveness determination. One of ordinary skill in the art would be motivated to make this modification in order to improve liveness detection accuracy by requiring a statistically significant proportion of sensors to indicate human presence rather than relying on any single input.
In reference to claim 12, The electronic device of claim 11, the one or more processors, to generate the liveness information, are configured to analyze the current sensor information associated with one or more of the multiple inputs using a liveness assessment algorithm to determine the liveness state (Reznik: Fig. 6, [0054] and [0066]-[0068] Provides for a defined algorithmic process (fusion logic) that analyzes sensor data.)
In reference to claim 13, The electronic device of claim 11, the liveness information is generated using one or more machine learning models that are trained to detect whether the human user is actively handling the electronic device from the current sensor information (Reznik: [0046] and [0066] Provides for Viola-Jones algorithm, which is a machine-learning-based classifier.)
In reference to claim 14, The electronic device of claim 11, the liveness information associated with the current sensor information is based at least in part on patterns associated with historical sensor information (Reznik: [0053] and [0069]-[0072] Provides for maintaining historical sensor data in circular buffers with timestamps and computing statistics over accumulated samples.)
In reference to claim 15, The electronic device of claim 11, the liveness indicator has a value that is based at least in part on whether a threshold number or a threshold proportion of the multiple inputs indicate that the human user is actively handling the electronic device (Reznik: [0054] and [0065]-[0068] Provides for a fusion logic that requires multiple conditions to be simultaneously satisfied to confirm user presence.)
In reference to claim 16, The electronic device of claim 11, the liveness indicator has a value that indicates a probability that the human user is actively handling the electronic device (Cavallini: [0064]-[0070] Provides for liveness indicator expressed as a numerical score (e.g., 55 out of a possible weighted total) that reflects the degree of confidence in liveness.)
In reference to claim 17,The electronic device of claim 11, the liveness indicator includes a flag that has a first value to indicate that the human user is actively handling the electronic device or a second value to indicate that the electronic device is not being actively handled by the human user (Reznik: [0062]-[0064] Provides for a boolean field “user_detected” that takes one of two values (true/false).)
In reference to claim 20,The electronic device of claim 18, the liveness information is transmitted to the network node in connection with a data campaign to assess usage patterns associated with live human users and simulated human activity (Cavallini: [0050] and [0069]-[0070] Provides for transmitting liveness results to a remote node and for using test data to optimize the system's ability to distinguish live humans from simulated.)
In reference to claim 21, A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising: one or more instructions that, when executed by one or more processors of an electronic device, cause the electronic device to: receive multiple inputs that each indicate current sensor information related to a liveness state associated with a human user (Reznik: [0030]-[0038] and [0054] Provides for receiving multiple sensor inputs (camera, accelerometer, gyroscope, proximity sensor, etc.) that collectively teach determining whether a user is present and active.)
Wherein the multiple inputs include one or more motion detection inputs, one or more tilt recognition inputs and one or more biometric inputs (Reznik: [0035]-[0038], [0048] and [0064] Provides for motion detection (accelerometer variance), tilt recognition (gyroscope and device orientation/angle detection for viewing posture), and biometric inputs (face detection via camera).)
The one or more biometric inputs comprising a human proximity detection input indicating whether one or more humans are present within a threshold distance of the electronic device (Reznik: [0067]-[0069] Provides for face detection as a biometric input that determines whether a human is present within a defined threshold distance.)
generating, based at least in part on the multiple inputs, liveness information that includes a liveness assessment word (Reznik: [0054]-[0063] Provides for generating a structured output (uad_result_1) based on fused multi-sensor inputs that encodes user presence information.)
a liveness indicator that indicates whether a human user is actively handling the electronic device (Reznik: [0063]-[0065] Provides for detecting and distinguishing whether a user is actively holding/handling the device versus the device being stationary.)
Reznik does not explicitly teach wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective input of the multiple inputs and wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold. However, Cavallini teaches:
Wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective inpute of the multiple inputs (Cavallini: [0063]-[0064] Provides for individual binary (TRUE/FALSE) results for each liveness indicator corresponding to each respective input.)
Wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold (Cavallini: [0064]-[0070] Provides for threshold-based determination that depends on the proportion of liveness indicators returning TRUE out of the total set.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik, which provides a method for receiving multiple sensor inputs including motion, tilt, and biometric data to generate liveness information indicating whether a human user is actively handling an electronic device, with the teachings of Cavallini, which introduces binary bit representation for individual liveness states and ratio-based threshold determination for overall liveness assessment. One of ordinary skill in the art would recognize the ability to incorporate Cavallini's structured binary encoding and statistical threshold approach into Reznik's multi-sensor liveness detection system to provide more robust and quantifiable liveness determination. One of ordinary skill in the art would be motivated to make this modification in order to improve liveness detection accuracy by requiring a statistically significant proportion of sensors to indicate human presence rather than relying on any single input.
In reference to claim 22, The non-transitory computer-readable medium of claim 21, the one or more instructions, that cause the electronic device to generate the liveness information, cause the electronic device to analyze the current sensor information associated with one or more of the multiple inputs using a liveness assessment algorithm to determine the liveness state (Reznik: Fig. 6, [0054] and [0066]-[0068] Provides for a defined algorithmic process (fusion logic) that analyzes sensor data.)
In reference to claim 23, The non-transitory computer-readable medium of claim 21, the liveness information is generated using one or more machine learning models that are trained to detect whether the human user is actively handling the electronic device from the current sensor information (Reznik: [0046] and [0066] Provides for Viola-Jones algorithm, which is a machine-learning-based classifier.)
In reference to claim 24, The non-transitory computer-readable medium of claim 21, the liveness indicator has a value that is based at least in part on whether a threshold number or a threshold proportion of the multiple inputs indicate that the human user is actively handling the electronic device (Reznik: [0054] and [0065]-[0068] Provides for a fusion logic that requires multiple conditions to be simultaneously satisfied to confirm user presence.)
In reference to claim 25, The non-transitory computer-readable medium of claim 21, the liveness indicator has a value that indicates a probability that the human user is actively handling the electronic device (Cavallini: [0064]-[0070] Provides for liveness indicator expressed as a numerical score (e.g., 55 out of a possible weighted total) that reflects the degree of confidence in liveness.)
In reference to claim 26, An apparatus for wireless communication, comprising: means for receiving multiple inputs that each indicate current sensor information related to a liveness state associated with a human user (Reznik: [0030]-[0038] and [0054] Provides for receiving multiple sensor inputs (camera, accelerometer, gyroscope, proximity sensor, etc.) that collectively teach determining whether a user is present and active.)
Wherein the multiple inputs include one or more motion detection inputs, one or more tilt recognition inputs and one or more biometric inputs (Reznik: [0035]-[0038], [0048] and [0064] Provides for motion detection (accelerometer variance), tilt recognition (gyroscope and device orientation/angle detection for viewing posture), and biometric inputs (face detection via camera).)
The one or more biometric inputs comprising a human proximity detection input indicating whether one or more humans are present within a threshold distance of the electronic device (Reznik: [0067]-[0069] Provides for face detection as a biometric input that determines whether a human is present within a defined threshold distance.)
Means for generating, based at least in part on the multiple inputs, liveness information that includes a liveness assessment word (Reznik: [0054]-[0063] Provides for generating a structured output (uad_result_1) based on fused multi-sensor inputs that encodes user presence information.)
a liveness indicator that indicates whether a human user is actively handling the electronic device (Reznik: [0063]-[0065] Provides for detecting and distinguishing whether a user is actively holding/handling the device versus the device being stationary.)
Reznik does not explicitly teach wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective input of the multiple inputs and wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold. However, Cavallini teaches:
Wherein the generating includes one or more bits, wherein each bit of the one ore more bits represents the liveness state associated with a respective inpute of the multiple inputs (Cavallini: [0063]-[0064] Provides for individual binary (TRUE/FALSE) results for each liveness indicator corresponding to each respective input.)
Wherein the liveness indicator is based at least in part on a ratio of inputs of the multiple inputs, that indicate liveness satisfying a threshold (Cavallini: [0064]-[0070] Provides for threshold-based determination that depends on the proportion of liveness indicators returning TRUE out of the total set.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik, which provides a method for receiving multiple sensor inputs including motion, tilt, and biometric data to generate liveness information indicating whether a human user is actively handling an electronic device, with the teachings of Cavallini, which introduces binary bit representation for individual liveness states and ratio-based threshold determination for overall liveness assessment. One of ordinary skill in the art would recognize the ability to incorporate Cavallini's structured binary encoding and statistical threshold approach into Reznik's multi-sensor liveness detection system to provide more robust and quantifiable liveness determination. One of ordinary skill in the art would be motivated to make this modification in order to improve liveness detection accuracy by requiring a statistically significant proportion of sensors to indicate human presence rather than relying on any single input.
In reference to claim 27, The apparatus of claim 26, the means for generating the liveness information includes means for analyzing the current sensor information associated with one or more of the multiple inputs using a liveness assessment algorithm to determine the liveness state (Reznik: Fig. 6, [0054] and [0066]-[0068] Provides for a defined algorithmic process (fusion logic) that analyzes sensor data.)
In reference to claim 28, The apparatus of claim 26, the liveness information is generated using one or more machine learning models that are trained to detect whether the human user is actively handling the apparatus from the current sensor information (Reznik: [0046] and [0066] Provides for Viola-Jones algorithm, which is a machine-learning-based classifier.)
In reference to claim 29, The apparatus of claim 26, the liveness indicator has a value that is based at least in part on whether a threshold number or a threshold proportion of the multiple inputs indicate that the human user is actively handling the apparatus (Reznik: [0054] and [0065]-[0068] Provides for a fusion logic that requires multiple conditions to be simultaneously satisfied to confirm user presence.)
In reference to claim 30, The apparatus of claim 26, the liveness indicator has a value that indicates a probability that the human user is actively handling the apparatus (Cavallini: [0064]-[0070] Provides for liveness indicator expressed as a numerical score (e.g., 55 out of a possible weighted total) that reflects the degree of confidence in liveness.)
In reference to claim 31, The apparatus of claim 26, wherein the liveness indicator includes a flag that has a first value to indicate that the human user is actively handling the apparatus or a second value to indicate that the apparatus is not being actively handled by the human user (Reznik: [0034] and [0062]-[0068] Provides for a data field having exactly two values, those values to the recited states by distinguishing the user holding the phone in hand from the device being at rest on a table or in a pocket.)
Claims 9, 19 and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Reznik et al. (US 20150241962 A1, referred to as Reznik) in further view of Cavallini (US 20150310289 A1, Cavallini) in further view of Hanna et al. (US 20140270404 A1, referred to as Hanna).
In reference to claim 9, Reznik in view of Cavallini teaches the method of claim 8. However they do not explicitly disclose information being in connection with a short message service (SMS). However, Hanna discloses:
The method of claim 8, wherein the liveness information is transmitted to the network node in connection with a short message service (Hanna: [0133]-[0135] Provides for liveness detection information being sent and in connection with a short message service (SMS).)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik in view of Cavallini, which provides a system for liveness detection using multiple sensor inputs and composite assessments, with the teachings of Hanna, which introduces transmitting liveness information via SMS. One of ordinary skill in the art would recognize the ability to incorporate SMS transmission into the existing liveness detection system to enable more flexible communication options. One of ordinary skill in the art would be motivated to make this modification in order to leverage widely available SMS infrastructure, ensure delivery of liveness information
In reference to claim 19, Reznik in view of Cavallini teaches the method of claim 8. However they do not explicitly disclose information being in connection with a short message service (SMS). However, Hanna discloses:
The electronic device of claim 18, wherein the liveness information is transmitted to the network node in connection with a short message service. (Hanna: [0133]-[0135] Provides for liveness detection information being sent and in connection with a short message service (SMS).)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik in view of Cavallini, which provides a system for liveness detection using multiple sensor inputs and composite assessments, with the teachings of Hanna, which introduces transmitting liveness information via SMS. One of ordinary skill in the art would recognize the ability to incorporate SMS transmission into the existing liveness detection system to enable more flexible communication options. One of ordinary skill in the art would be motivated to make this modification in order to leverage widely available SMS infrastructure, ensure delivery of liveness information.
In reference to claim 32, Reznik in view of Cavallini teaches the method of claim 8. However they do not explicitly disclose information being in connection with a short message service (SMS). However, Hanna discloses:
The apparatus of claim 26, wherein the liveness information is transmitted to the network node in connection with a short message service. (Hanna: [0133]-[0135] Provides for liveness detection information being sent and in connection with a short message service (SMS).)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Reznik in view of Cavallini, which provides a system for liveness detection using multiple sensor inputs and composite assessments, with the teachings of Hanna, which introduces transmitting liveness information via SMS. One of ordinary skill in the art would recognize the ability to incorporate SMS transmission into the existing liveness detection system to enable more flexible communication options. One of ordinary skill in the art would be motivated to make this modification in order to leverage widely available SMS infrastructure, ensure delivery of liveness information.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AIDAN EDWARD SHAUGHNESSY whose telephone number is (703)756-1423. The examiner can normally be reached on Monday-Friday from 7:30am to 5pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jeffrey Nickerson, can be reached at telephone number (469) 295-9235. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A.E.S./Examiner, Art Unit 2432
/Jeffrey Nickerson/Supervisory Patent Examiner, Art Unit 2432
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