DETAILED ACTION
This communication is a Non-Final Office Action on the merits in response to communications received on 11/26/2025. Claims 1 and 14 have been amended. Therefore, claims 1-7 and 14-26 are pending and have been addressed below. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/26/2025 has been entered.
Claim Rejections – 35 USC §101
2. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
3. Claims 1-7 and 14-26 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
4. Regarding Step 1, claim 1 recites a process (i.e., an act or step, or a series of acts or steps) and claim 14 recites a machine (i.e., a concrete thing, consisting of parts, or of certain devices and combination of devices). Thus, each of the claims fall within one of the four statutory categories.
5. Regarding Step 2A [prong 1], claims 1 and 14 recite:
“receiving…a first indication…that a user…wants to trade in;”, “receiving…interaction data from a user”, “determining…using the interaction data, when the touch screen is operable, wherein the touch screen is determined to be operable when interaction data was received;”, “in response to receiving the identification number, verifying an identity of the user based on the identification number”, “inputting…the image data, wherein: on a set of training data to determine make, model, and physical condition;” and “the set of training data includes images, each image labeled with the make, the model, and a numerical value representative of the physical condition;”, “receiving…outputs, wherein the outputs represent the make, model, and physical condition, and wherein the physical condition is represented as a percentage between 0% and 100% based on the presence of one or more cracks, scratches, or scuffs;” and “determining…a current condition based on the determination that the touch screen is operable that the touch screen is operable, the verified identity, and the outputs.”
The limitations demonstrate that the claim recites an abstract idea of facilitating a user attempting to trade-in a phone and steps for assessing the physical condition of the phone encompasses fundamental economic practices (i.e., insurance, mitigating risks), a commercial interaction (i.e., sales or marketing activities, business relations), managing personal behavior or interactions between people, (i.e., a user following rules or instructions), and mental processes, (i.e., observations, evaluations, judgements, opinions) which is subject matter that falls within the certain methods of organizing human activity and mental processes groupings of abstract ideas. See MPEP 2106.04 II
The Applicant’s Specification emphasizes in at least [¶ 0013] The disclosed systems and methods enable performance of a reliable, objective, and trustworthy determination of a current condition of an electronic device. For example, a dedicated mobile application on a smartphone can collect data indicative of the condition of the electronic device. This data can include images of the electronic device, which are input into a machine learned model that outputs a make, model, and physical condition of the electronic device. The mobile application can also verify an identity of a user of the electronic device and determine whether a touchscreen of the electronic device is operable. The mobile application uses the outputs, verified identity (or lack thereof), and touchscreen operability to determine a current condition of the electronic device. The current condition indicates the ability of the electronic device to be traded in and given to a new user. The mobile application uses the current condition to assign a trade-in or resale value to the electronic device thereby obviating the need for an unreliable and untrustworthy subjective assessment.
Consistent with the specification, the limitations describe tasks a user must perform or rules the user may follow to request a trade-in of their phone and determine the current physical condition of their phone which relates to subject matter that involves commercial interactions, i.e., marketing or sales activities, business relations and managing personal behavior or interactions between people. Also, the steps for determining the physical condition and data from the images recited in the claim pertain to mental processes for comparing and recognizing known information from images to provide the condition of the phone which are acts that may be performed in the human mind with or without pen and paper. As such, the claim recites an abstract idea.
6. Regarding Step 2A [prong 2], independent claims include the following additional elements which do not amount to a practical application:
“a system”, “a processor;”, a non-transitory computer-readable storage medium storing instructions:”, “at a manager node via a network”, “from a handheld wireless device”, “causing display…via a touch screen of the handheld wireless device of a plurality of touch screen widgets, wherein each touch screen verification widget of the plurality of touch screen verification widgets is associated with a portion of the touch screen”, “at the manager node”, “from the handheld device”, “one or more touch screen verification widgets of the plurality of touch screen verification widgets, wherein the verification widgets include indications of a predetermined sequence of touch locations”, “for each touch screen verification widget of the plurality of touch screen verification widgets according to the predetermined sequence of touch location”, “via the touch screen”, “a machine learned model”, “the machine learned model is trained”, “from the machine learned model”, “an electronic ledger associated with the handheld wireless device, wherein the electronic ledger”– see claims 1 and 14, are all described at a high-level of generality in light of the specification. The specification (i.e., Fig. 4, ¶ 0017) describes the additional elements in general terms without describing any of the particulars such that they may be broadly but reasonably construed as generic computer components that are being used to perform the abstract idea. As such, these additional elements recited in the claim are mere instructions to implement an abstract idea on a computer or merely use a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05 (f)
The other additional elements of: “prompting…input of an identification number;”, “prompting…upload of image data;”, “storing…the current condition…tracks the current condition over time” add insignificant extra-solution activity [ i.e., data gathering, storage, output] to the judicial exception, as discussed in MPEP 2106.05(g)
The additional element of “a method for determining a current condition of a handheld wireless device configured to communicate data over a wireless telecommunications network, the method comprising:” is merely an attempt to limit the claimed invention to a particular technological environment or field of use, as discussed in MPEP 2106.05(h)
Thus, the additional claim elements are not indicative of integration into a practical application, because the claims do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea and the claims are directed to an abstract idea.
7. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional element(s) of: “a system”, “a processor;”, a non-transitory computer-readable storage medium storing instructions:”, “at a manager node via a network”, “from a handheld wireless device”, “causing display…via a touch screen of the handheld wireless device of a plurality of touch screen widgets, wherein each touch screen verification widget of the plurality of touch screen verification widgets is associated with a portion of the touch screen”, “at the manager node”, “from the handheld device”, “one or more touch screen verification widgets of the plurality of touch screen verification widgets, wherein the verification widgets include indications of a predetermined sequence of touch locations”, “for each touch screen verification widget of the plurality of touch screen verification widgets according to the predetermined sequence of touch location”, “via the touch screen”, “a machine learned model”, “the machine learned model is trained”, “from the machine learned model”, “an electronic ledger associated with the handheld wireless device, wherein the electronic ledger”,– see claims 1 and 14 are at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception does not provide an inventive concept at Step 2B.
The additional elements of: “prompting…input of an identification number;”, “prompting…upload of image data;”, “storing…the current condition…tracks the current condition over time” were considered insignificant extra-solution activity under Step 2A Prong Two and have been re-evaluated under Step 2B to determine if the limitations are well-known, routine, and/or conventional.
As discussed in MPEP 2106.05 (d)(II), the Alice, Symantec, TLI Communications, OIP Techs court decisions indicated “receiving or transmitting data over a network”, “electronic recordkeeping”, and “presenting offers and gathering statistics” are computer functions that are well-known, routine, and conventional. Therefore, when viewed individually or in combination with the judicial exception the limitations do not provide an inventive concept.
8. Dependent claims 2-7 and 15-26 recite: claims 2, 15, 25, recite “further comprising: in response to determining the numerical value is greater than a damage threshold, determining that the handheld wireless device is not transferable to a second user.” which serve to narrow how the abstract idea may be performed but does not make the claim any less abstract, claims 3 and 16 recite “further comprising: adding, to an electronic ledger associated with the handheld wireless device, the current condition at a current time and date” which adds insignificant extra-solution activity to the judicial exception, i.e., data storage, as discussed in MPEP 2106.05(g). The electronic ledger is nominally recited in the claim to store or retrieve data which does not integrate the judicial exception, claims 4 and 17 recite “wherein the image data is one or more of images and/or videos” which further describes the data/information recited in the abstract idea but does not make the claim any less abstract, claims 5 and 18 recite “wherein the identification number is an International Mobile Equipment Identity (IMEI)” which further describes the data/information recited in the abstract idea but does not make the claim any less abstract, claims 6 and 19 recite “further comprising: in response to not verifying the identity of the user, establishing communication with an electronic device of an external operator.” which serve to narrow how the abstract idea may be performed but does not make the claim any less abstract, claims 7 and 20 recite “transmitting, for display via the touch screen, a notification of the current condition of the handheld wireless device” which adds insignificant extra-solution activity to the judicial exception, i.e., data transmission, as discussed in MPEP 2106.05(g). The touch screen is nominally recited in the claim and mere used to provide information which does not integrate the judicial exception or provide an inventive concept, claims 21 and 24 recite “wherein the outputs from the machine learned model include a numerical value representative of the physical condition of the handheld wireless device” serves to further describe the data or information recited in the abstract idea. The machine learning model is being used in its ordinary capacity to output results which does not integrate the judicial exception or provide an inventive concept, claim 22 recites “determining that the numerical value is below a damage threshold and determining that the handheld wireless device is transferable to a second user” serves to narrow how the abstract idea may be performed, but does not make the claim any less abstract, claims 23 and 26 recite “determining a trade-in value of the handheld wireless device and transmitting the trade-in value to the handheld wireless device for display on the touch screen of the handheld wireless device” serves to narrow how the abstract idea may be performed, but does not make the claim any less abstract. Accordingly, the dependent claims fail to impose any meaningful limits on integrating the abstract idea into a practical application. Thus, after considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims are not enough to transform the abstract idea into a patent-eligible invention since the claim limitations do not amount to a practical application or significantly more than an abstract idea.
Claim Rejections - 35 USC § 103
9. 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.
10. 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.
11. Claim(s) 1-7 and 14-26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zellner (US 2023/0188998 A1) in view of Silva (US 2020/0265487 A1) in further view of Dion (US 2021/0110440 A1)
With respect to claims 1 and 14, Zellner discloses
a method and system for determining a current condition of a handheld wireless device configured to communicate data over a wireless telecommunications network (abstract, ¶ 0001, 0079, 0089, 0114: discloses systems, methods, and apparatuses related to remote verification of a condition of a mobile device.) comprising:
a processor (¶ 0102: discloses processor); and
a non-transitory computer-readable storage medium storing instructions (¶ 0101: discloses computer readable medium) that when executed cause the processor to perform actions comprising:
receiving, at a manager node via a network, a first indication from the handheld wireless device that a user of the handheld wireless device seeks to trade-in the handheld wireless device (¶ 0079, 0120: discloses receiving a request for verification on mobile device condition of a mobile device from a user of the mobile device. The request may be a device-to-device transmission generated at one device and sent via a network or wireless connection to another device. The request may be a transmission within a single device. For example, the user or a third party may initiate a “trade in” or similar function that may require verification of the condition of the mobile device. The request may be sent to the remote verification circuitry 102 within the apparatus or it may be sent to the remote verification system 307.);
causing display, by the manager node at the handheld wireless device via a touch screen of the handheld wireless device, of a plurality of touch screen verification widgets (Fig. 12, ¶ 0158, 0162: discloses a touch screen diagnostic, i.e., a digitizer test, may comprise a GUI 2700 configured to explain the process to the user and request one or more inputs by the user in order to begin the touchscreen diagnostic.),
wherein each touch screen verification widget of the plurality of touch screen verification widgets is associated with a portion of the touch screen (Fig. 12, ¶ 0158, 0162-0163: discloses the touchscreen diagnostic may comprise an indication for the user to tap, select, or swipe one or more grid squares in order to determine that the touchscreen of the mobile device is working in each respective grid square.);
receiving, at the manager node, interaction data from the handheld wireless device, the interaction data indicating touch interaction of a user with one or more touch screen verification widgets of the plurality of touch screen verification widgets (Fig. 12, ¶ 0158, 0162-0163: discloses in response to selection of individual grid squares 2801, portions of an image may be displayed to visually indicate to the user that the respective grid square is functional and has been verified.),
wherein the verification widgets include indications of a predetermined sequence of touch locations (¶ 0158, 0162-0163: discloses one or more grid squares for selection of the user using the touchscreen of the mobile device. The size/number of grid squares may be selected, i.e., preset, by the carrier or provider that is directing or otherwise associated with the remote verification process. The touch screen test includes instructing the user to follow a test pattern on the screen with their finger or instructing the user to color in the screen with their finger to verify the entirety of the touch surface of the screen is operational.);
determining, by the manager node, using the interaction data, when the touch screen is operable (Fig. 12, ¶ 0158, 0162-0163),
wherein the touch screen is determined to be operable when interaction data was received for each touch screen verification widget of the plurality of touch screen verification widgets according to the predetermined sequence of touch locations (Fig. 12, ¶ 0158, 0162-0163: discloses once the user has selected each of the grid squares and each has been verified, the GUI may return an indication that the touchscreen diagnostic has been passed. The touch screen test includes instructing the user to follow a test pattern on the screen with their finger or instructing the user to color in the screen with their finger to verify the entirety of the touch surface of the screen is operational.);
prompting, via the touch screen, input of an identification number of the handheld wireless device (¶ 0110, 0144-0145: discloses the GUI may be configured to request the user to input background data associated with the mobile device, such as an IMEI number);
in response to receiving the identification number at the manager node,
verifying, by the manager node, that the handheld wireless device is available for trade-in or verifying an identity of the user of the handheld wireless device based on the identification number (¶ 0110, 0127, 0144-0145: discloses the remote verification system 307 may use the identification data object, i.e., IMEI number associated with the mobile device to identify and match the current mobile device and/or current remote verification process using the correct identification data object with stored historical and current data of the mobile device within the verification system. The identification data object may be associated with both the device and the user.);
prompting, via the touch screen, upload of image data depicting the handheld wireless device (¶ 0018, 0153-0155: discloses directing a user of a mobile device to orient a front-facing camera and capturing an image of the mobile device.);
inputting, by the manager node, the image data to a machine learned model (¶ 0155: discloses a neural network or machine learning model is used to determine if the image contains damage.), wherein:
the machine learned model is trained on a set of training data to determine physical condition of handheld wireless devices (¶ 0155-0156: discloses a neural network or machine learning model may be trained to determine if one or more parts of the image(s) show damage.); and
the set of training data includes images of handheld wireless devices (¶ 0154-0156: discloses one or more images may be captured for analysis.), and a numerical value representative of the physical condition of the respective handheld wireless device (¶ 0156: discloses the neural networks and/or machine learning models determine patterns amongst the plurality of parameters, values, and data points defined by the screen crack detection data and screen crack predictions.);
receiving, by the manager node, outputs from the machine learned model (¶ 0155-0157: discloses the images of the mobile device may be transmitted to remote verification system for image analysis.), wherein the outputs represent the physical condition of the handheld wireless device; and
determining, by the manager node, the current condition of the handheld wireless device (Fig. 16, ¶ 0196: discloses indicating the acceptable condition 1600) based on the determination that the touch screen is operable that the touch screen of the handheld wireless device is operable (Fig. 16, ¶ 0196: discloses results of the screen crack detection routine, i.e., touchscreen), the verification based on the identification number (¶ 0193), and the outputs of the machine learned model (¶ 0155-0156: discloses the neural networks and/or machine learning models may be configured to determine a correlation or pattern associated with the image data of a mobile device.)
and storing, by the manager node, the current condition to an electronic ledger associated with the handheld wireless device (¶ 0106, 0116, 0127, 0141: discloses the remote verification system 307 may store and otherwise use and keep track of datasets received from mobile devices, diagnostic indicators, screen crack detection results, etc. The memories 103 and 203 may be any suitable networked storage devices configured to store some or all of the information. The memories may include one or more database systems, backend data servers, network databases, cloud storage devices, etc. The remote verification of the condition of the mobile device process may store externally via transmission of data over a network to an external storage subsystem analytics of the mobile device based on one or more historical and current diagnostics.),
wherein the electronic ledger tracks the current condition over time. (¶ 0106, 0116, 0127: discloses the remote verification of the condition of the mobile device process may store externally via transmission of data over a network to an external storage subsystem historical and current data of the mobile device based on diagnostics run.)
The Zellner reference does not explicitly disclose the following limitations. In the same field of endeavor, the Silva reference is related to evaluating the condition of mobile phones based on machine learning techniques. (¶ 0002)
the machine learned model is trained on a set of training data to determine make, model (Fig. 5, ¶ 0066-0069: discloses training a neural network for evaluating the cosmetic condition of electronic devices. The training set can include information about the devices, i.e., brand, model, release date, so that the model can be trained to identify damages that are specific to a particular set of devices. The method includes training at least a portion of the neural network based on the training set.),
each image labeled with the make of a respective handheld wireless device, the model of the respective handheld wireless device (¶ 0062, 0068: discloses the neural networks can be trained using pre-collected images which have been labeled by inspectors.),
wherein the outputs represent the make and model of the handheld wireless device (¶ 0059: discloses the output of the neural networks includes an integer 0 or 1. Zero can represent “cosmetically good” and 1 can represent “cosmetically bad. The output of the neural networks can be a score of a range of values that indicate the severity of the damages on the consumer device. The output of the neural networks can further include a brand, model, and/or type of electronic device shown in the input image.)
As can be seen from the cited passages above and [¶ 0003-0007] of Silva, using machine learning techniques, i.e., neural networks, to evaluate images and output the brand, model, and condition of electronic devices were known in the state of the art as there was a need for more efficient technologies for evaluating the physical and/or cosmetic condition of electronic devices in the industry.
Therefore, 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 system and methods of Zellner for verifying the condition of mobile device, in include the techniques for evaluating the cosmetic and/or physical condition of electronic devices using a neural network model, as disclosed by Silva to achieve the claimed invention. As disclosed by Silva, the motivation for the combination would have been to leverage brand and model information from the image so that the model can be trained to identify damages that are specific to a particular set of devices as expressly suggested by Silva (¶ 0003-0007, 0068)
The combination of Zellner and Silva does not explicitly disclose the following limitations. In the same field of endeavor, the Dion reference is related to systems and methods related to the evaluation of pre-owned electronic devices. (¶ 0002)
wherein the physical condition is represented as a percentage between 0% and 100% based on the presence of one or more of cracks, scratches, or scuffs
(¶ 0327, 0331, 0355-0357, 0370-0373: discloses the evaluation 814 results in information 802 associated with the POD and the evaluation of the POD. The information 802 may include POD identification information 801, attributes 804 and conditions 810. Some attributes 804, may include lists of attributes 806. For example, a defect attribute for a scratch may include a list of two scratches. For each attribute in the list, meta-attributes 808 may be specified. For example, for each scratch attribute in a list of scratches, meta-attributes can be specified for location of scratch, dimension of scratch, image of scratch (digital assets), and timestamp of when scratch was observed. Use of a percentage-based grading method, applying weighting factors to attributes, meta-attributes or conditions. The grading functions could return a weighted notation giving 50% to the inner-working conditions of the pre-owned device, 30% to the touch-screen conditions and 20% for the body condition. Provide an evaluation score (e.g. “your score” in the customer report shown in FIG. 9F) that is computed using programmatic or machine-learning algorithms that provide a numerical, alphanumerical or grading score for a device which may be presented to the end user. Such an evaluation score can, for example, be calculated using any one or more of: deterioration information; weighted physical defect information, for example, a small nick may have weight less than a crack; and/or weighted health information or defect, for example a malfunctioning, lesser used feature, such as the accelerometer, may have weight less than a malfunctioning network interface. The weights may be configured according to rules in a rules database or in context information. The evaluation score may be complemented by evaluation summary information, such as graded information about physical and internal condition. For example, a device could have a score of 80 and a summary information stating “Good physical condition” and “Good working condition”. Combined they can become an evaluation summary. The evaluation score, information or summary may become useful for “summarizing” an evaluation report or customer report about a device, much like a credit score provides a summary information about a person's credit habits. Such evaluation score, information or summary, may provide, for example the ability for a protection company (insurance, warranty provider, manufacturer, reseller) to offer protection plans that will replace a device deemed “as good or better”, and such entity could rely either on detailed evaluation information with detailed defect information, or in a preferred embodiment, on evaluation score, information or summary in order to broaden the quantity of substitute devices available.)
Therefore, 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 combined system and methods of Zellner and Silva for verifying the condition of mobile devices, to include wherein the physical condition is represented as a percentage between 0% and 100% based on the presence of one or more of cracks, scratches, or scuffs, as disclosed by Dion to achieve the claimed invention. As disclosed by Dion, the motivation for the combination would have been to provide advantages for buyers including more accurate grading of pre-owned devices so that buyers can make a clear agreement when trading in graded devices. (¶ 0355-0356)
With respect to claims 2, 15, and 25, the combination of Zellner, Silva, and Dion discloses the method and system, further comprising:
in response to determining the numerical value is greater than a damage threshold (¶ 0084: Zellner discloses the processor analyzes one or more images and returns an indication of an unacceptable condition.),
determining that the handheld wireless device is not transferable to a second user. (¶ 0096: Zellner discloses an unacceptable condition may trigger a failsafe to prevent the device from being sold, shipped to, used, or accepted by third parties.)
With respect to claims 3 and 16, the combination of Zellner, Silva, and Dion discloses the method and system, further comprising:
adding, to an electronic ledger associated with the handheld wireless device,
the current condition at a current time and date. (¶ 0106, 0116, 0127: Zellner discloses memories 103 include one or more database systems, network databases, cloud storage devices, etc. The remote verification system 307 may store the historical data associated with the mobile device comprising one or more previous diagnostics run on the mobile device and/or current diagnostics run on the mobile device during the current process of the remote verification of the condition of the mobile device process)
With respect to claims 4 and 17, the combination of Zellner, Silva, and Dion discloses the method and system,
wherein the image data is one or more of images and/or videos. (¶ 0154-0156: Zellner discloses images of the mobile device are used for image analysis.)
With respect to claims 5 and 18, the combination of Zellner, Silva, and Dion discloses the method and system,
wherein the identification number is an International Mobile Equipment Identity (IMEI). (¶ 0110, 0127, 0138, 0144: Zellner discloses the GUI may be configured to request the user to input background data associated with mobile device such as an IMEI number.)
With respect to claims 6 and 19, the combination of Zellner, Silva, and Dion discloses the method and system, further comprising:
in response to not verifying the identity of the user (¶ 0111: Zellner discloses stored identification data object data may be stored within a policy linked to at least one of the user and mobile device which may be used for offering one or more services associated with the verification.),
establishing communication with an electronic device of an external operator. (¶ 0111: Zellner discloses information related to the mobile device to be sent to one or more third party computing devices in which verification of a condition of the mobile device is requested.)
With respect to claims 7 and 20, the combination of Zellner, Silva, and Dion discloses the method and system, further comprising:
transmitting, for display via the touch screen, a notification of the current condition of the handheld wireless device. (¶ 0116, 0148, 0194-0196: Zellner discloses GUI of the mobile device may be configured to show an acceptable condition of the mobile device based on the remote verification of the condition of the mobile device.)
With respect to claims 21 and 24, the combination of Zellner, Silva, and Dion discloses the method and system,
wherein the outputs from the machine learned model include a numerical value representative of the physical condition of the handheld wireless device. (¶ 0059: Silva discloses the output of the neural networks includes an integer 0 or 1. Zero can represent “cosmetically good” and 1 can represent “cosmetically bad. The output of the neural networks can be a score of a range of values that indicate the severity of the damages on the consumer device. The output of the neural networks can further include a brand, model, and/or type of electronic device shown in the input image.)
With respect to claim 22, the combination of Zellner, Silva, and Dion discloses the method of claim 21, further comprising:
determining that the numerical value is below a damage threshold (¶ 00042, 0059: Silva discloses the output of the neural networks can be a score of a range of values that indicate the severity of the damages on the consumer device.) and
determining that the handheld wireless device is transferable to a second user. (¶ 0042, 0050 - Silva)
With respect to claims 23 and 26, the combination of Zellner, Silva, and Dion discloses the method and system, further comprising:
determining a trade-in value of the handheld wireless device (¶ 0195-0198 - Zellner); and
transmitting the trade-in value to the handheld wireless device for display on the touch screen of the handheld wireless device. (Fig. 16, ¶ 0195-0198: Zellner discloses an example GUI 4100 configured to give a user a trade-in amount. The trade-in amount may comprise the value associated with the mobile device after the acceptable condition is determined)
Response to Arguments
Applicant's arguments filed 26 November 2025 have been fully considered but they are not persuasive.
With Respect to Rejections Under 35 USC 101
Applicant argues “In the Office Action, the Examiner states with respect to Prong One of Step 2A that the steps recited in the previously-pending claims "cover fundamental economic practices and managing the personal behavior or interactions because they require a user to request a trade-in and input information related to the mobile device." Further, the Office Action states, "The series of steps are also performing a commercial interaction, i.e., facilitating a trade-in for a user, which is subject matter that may be reasonably characterized as falling within certain methods of organizing human activity grouping." Applicant respectfully disagrees and submits that merely because there is human involvement in some fashion does not mean that the claims are directed to managing personal behavior or interactions, nor does the technical solution being used within the context of trade-ins mean that the claims themselves are merely directed to economic practices.” The Examiner respectfully disagrees.
Contrary to the remarks, the claims remain ineligible under Step 2A Prong One of the two-part analysis. For example, MPEP 2106.04(a)(2)(II) indicates the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping.
The Applicant’s Specification describes [¶ 0001-0003] conventional business practices related to how interactions between a customer and technician typically flow when physically assessing a mobile phone for trade-in and a need for a more accurate assessment of a mobile phone’s condition. Thus, the support from the Speciation emphasizes the focus of the claims is for facilitating a trade-in for a user and techniques for assessing the condition of the trade-in which is subject matter related to mitigating risks for the user, sales/marketing activities, and business relations that may be reasonably characterized as falling withing the certain methods of organizing human activity grouping. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “Rather, the claims as amended herein recite specific technical approaches for evaluating physical and electronic condition and functioning of a handheld electronic device. The claims to not recite actions carried out by a user, but rather recite specific limitations carried out by a manager node via a network, including causing display of touch screen verification widgets on a handheld wireless device, receiving interaction data from the handheld wireless device, evaluating the interaction data to determine if the touch screen is operable, verifying user identity based on an identification number of the handheld wireless device, and using a trained machine learning model to evaluate physical condition of the handheld wireless device.
The Office Action states that the claims "do not ... purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field." Applicant respectfully disagrees. The claims recite a specific improvement for evaluating handheld wireless devices and determining trade in eligibility. As discussed in the application, the claims "enable performance of a reliable, objective, and trustworthy determination of a current condition of an electronic device."(0013) More specifically, this the reliable, objective, and trustworthy evaluation is performed over a network, for example as illustrated in Figure 1 of the application as filed. As described in the application as filed, trustworthy evaluation is a significant problem in the field, as "a customer is inclined to report a higher value while a carrier is motivated to find a lower value." Further, the application as filed describes limitations on human inspection, as such inspections are "subjective" and technicians "may only be able to see cracks in the mobile device's screen larger than a certain size and/or may only be able to conduct a qualitative assessment of operability of the mobile device's touchscreen."(0002)” The Examiner respectfully disagrees.
Contrary to the remarks, the claims remain ineligible under Step 2A Prong Two of the two-part analysis. In the instant case, the techniques being performed by the manager node with the combination additional elements were addressed above under Prong Two of the analysis. The combination of additional elements are discussed in the Specification at a high-level of generality and at best represent generic computer components and machine learning technology to aid in performing the abstract. The remarks and Specification do not clearly explain how the ordered combination of limitations involve any technological improvements. At best, the remarks provided by Applicant emphasize improvements in a conclusory manner, without any improvements to the functioning of the computer itself or any other computing technology to be considered. See MPEP 2106.05(a) The improvements are within the abstract idea itself for determining a more accurate or reliable assessment of a customer’s trade-in, not any improvements related to the computer equipment or machine learning technology being used to perform the abstract idea. For these reasons, the rejections under 101 are being maintained.
Applicant further argues “while Applicant disagrees that the previously-pending claims are ineligible under Section 101, Applicant has nevertheless amended the claims as indicated above to provide additional detail regarding the verification widgets and touch sequence, representation of the physical condition, and to include limitations related to tracking conditions of a device over time in a ledger. For the foregoing reasons, independent claim 1 complies with Section 101. Independent claim 14 has been amended to contain similar limitations and also complies with Section 101 for at least the reasons indicated above with respect to claim 1.” The Examiner respectfully disagrees.
Contrary to the remarks, the claims remain ineligible under Step 2A Prong Two of the two-part analysis. In the instant case, adding the additional elements of “one or more verification widgets” and “an electronic ledger” to the claim, does not automatically integrate the judicial exception into a practical application or provide an inventive concept. See also TLI Communications LLC v. AV Automotive LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept)
At best, these additional elements including “one or more verification widgets” and “an electronic ledger” are merely being used as a tool in their ordinary capacity to store and/or retrieve data from the user and the assessment results regarding the condition of the trade-in. Merely adding generic computer components or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014). See In re Alappat, 33 F.3d 1526, 1545, 31 USPQ2d 1545, 1558 (Fed. Cir. 1994); In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008) For these reasons, the rejections under 101 are being maintained.
With Respect to Rejections Under 35 USC 103
Applicant’s arguments with respect to claim(s) 1-7 and 14-26 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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/EHRIN L PRATT/Examiner, Art Unit 3629 /LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629