DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Applicant’s election without traverse of Group II in the reply filed on April 16, 2026 is acknowledged.
Claim Rejections - 35 USC § 101
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.
Claims 9-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed a judicial exception (i.e., an abstract idea) without significantly more.
Step 1 – Statutory Categories
As indicated in the preamble of the claim, the examiner finds the claim is directed to a process, machine, manufacture, or composition of matter.(Claims 9-14 and 21-25 are processes and Claims 15-20 and 26-28 are machines). Accordingly, step 1 is satisfied.
Step 2A – Prong 1: was there a Judicial Exception Recited
Claim 1 (and similarly Claims 15) recites the following abstract concepts that are found to include “abstract idea.” Any additional elements will be analyzed under Step 2A-Prong 2 and Step 2B:
receiving, by a reader device of the inventory system, data from a plurality of tags coupled to a plurality of items moving along a conveyor belt in the warehouse, wherein the data includes information related to a location of each of the items (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
determining, by an inventory application executing on a computer system of the inventory system and communicatively coupled to the reader device, one or more clusters of items based on the location of each of the items, wherein a cluster of the one or more clusters comprises a subset of the items located within a distance from a centroid location (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
determining, by the inventory application, cluster data describing the cluster and the subset of items in the cluster (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
emitting, by at least one antenna of an antenna system, signals towards the cluster based on the centroid location (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016));
adjusting, by the inventory application, a reader device setting of the reader device based on the cluster data and a predictive model to optimize cluster-focused data received from the tags coupled to the subset of items in the cluster, wherein the reader device setting comprises at least one of a type of the signals, a frequency range of the signals, a position of the reader device, directional settings of the antenna system connected to the reader device, or an output power of the reader device (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016)); and
receiving, by the reader device, the cluster-focused data from the tags coupled to the subset of items in the cluster (See MPEP 2106.04(a)(2)(III) Mental Processes, a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016)).
Claim 1 (and similarly Claim 15) is directed to a series of steps for tracking inventory, which are mental processes. The mere nominal recitation of reader device, tags, computer system, and antenna of an antenna system does not take the claim out of mental processes. Thus, Claim 1 (and similarly Claim 15) recites an abstract idea.
Step 2A – Prong 2: Can the Judicial Exception Recited be integrated into a practical application
Limitations that are indicative of integration into a practical application:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
Limitations that are not indicative of integration into a practical application:
Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f)
Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)
Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
The identified abstract idea of exemplary Claim 1 (and similarly Claim 15) is not integrated into a practical application. The additional elements are: reader device, tags, computer system, and antenna of an antenna system. These additional elements are broadly recited computer elements that do not add a meaningful limitation to the abstract idea because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f).
Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application. Claim 1 (and similarly Claim 15) is directed to an abstract idea.
Step 2B – Significantly More Analysis
Claim 1 (and similarly Claim 15) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and in combination, steps a) receiving data related to a location of each item, b) determining one or more clusters of items based on the location of each of the items, c) determining cluster data describing the cluster and the subset of items in the cluster, d) emitting signals towards the cluster based on the centroid location, e) adjusting a reader device setting to optimize cluster-focused data received from tags coupled to the subset of items in the cluster, and f) receiving the cluster-focused data from the tags coupled to the subset of items in the cluster, etc., do not add significantly more to the exception because they amount to merely using a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Claim 1 (and similarly Claim 15) is ineligible.
Claim 10 recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 11 (and similarly Claim 17) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 12 (and similarly Claim 18) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 13 (and similarly Claim 19) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 14 (and similarly Claim 20) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 16 recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 21 (and similarly Claim 26) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 22 (and similarly Claim 27) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 23 (and similarly Claim 28) recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 24 recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
Claim 25 recites the abstract idea of mental processes. See MPEP 2106.04(a)(2)(III).
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.
Claim(s) 9-28 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pat Pub 2020/0124696 “Hewett”, in view of US Pat Pub 2006/0082444 “Sweeney”.
As per Claims 9 and 15, Hewett discloses a method and system performed by an inventory system to perform inventory tracking and control in a warehouse, wherein the method comprises:
receiving, by a reader device of the inventory system, data from a plurality of tags coupled to a plurality of items, wherein the data includes information related to a location of each of the items (Hewett: [0035] With this speed and accuracy, it can be used to track RFID-tagged items in real-time, down to the slightest movement. [0036] an RFID tag location system can used multiple RFID tag readers to interrogate reference tags, virtual reference tags, and RFID tags from many angles of arrival and create (multipath) signatures based on the received signals. Such a system can locate the tags in two or three dimensions with respect to each other and/or absolute (known) locations.);
determining, by an inventory application executing on a computer system of the inventory system and communicatively coupled to the reader device, one or more clusters of items based on the location of each of the items, wherein a cluster of the one or more clusters comprises a subset of the items located within a distance from a centroid location (Hewett: [0072] the system may cluster reference tags and unknown tags according to a property (e.g., multipath profile) and define a representative example of that property for use in weighting. [0112] These location estimates may be distributed over an area or volume whose size depends on noise and the measurement uncertainty. As the number of measurements increases, the average location estimate can converge to a smaller area or volume whose size is limited by the fundamental measurement uncertainty. Once the size of the area or volume reaches a predetermined threshold, the processor sets an appropriate tag location (e.g., the centroid of the area or volume) and uses this tag location as a reference for similar tags. The system may repeat this process until a desired number or set of RFID tags have been added to the pool of virtual reference tags. [0113] The system may identify changes in a cohort of RFID tags by looking at the signature of each RFID tag in the cohort with respect to the signatures of its cohort members. The system may also look for changes (or a lack of change) in signatures received at other AOAs from the cohort.);
determining, by the inventory application, cluster data describing the cluster and the subset of items in the cluster (Hewett: [0112] These location estimates may be distributed over an area or volume whose size depends on noise and the measurement uncertainty. As the number of measurements increases, the average location estimate can converge to a smaller area or volume whose size is limited by the fundamental measurement uncertainty. Once the size of the area or volume reaches a predetermined threshold, the processor sets an appropriate tag location (e.g., the centroid of the area or volume) and uses this tag location as a reference for similar tags. The system may repeat this process until a desired number or set of RFID tags have been added to the pool of virtual reference tags. [0113] The system may identify changes in a cohort of RFID tags by looking at the signature of each RFID tag in the cohort with respect to the signatures of its cohort members. The system may also look for changes (or a lack of change) in signatures received at other AOAs from the cohort. [0135] Antennas arrays monitor the location of each tote tag and each item tag. If the distance between one item tag and one tote tag is below a threshold value (e.g., less than the size of the tote), the system determines that the item corresponding to the item tag is in the tote. To improve the reliability of the detection, the system can further monitor the movement of the tote tag and the item tag. If they move together for a distance above a threshold value (e.g., more than 1 meter), the system can determine that the item and the tote are being carried by a customer.);
emitting, by at least one antenna of an antenna system, signals towards the cluster based on the centroid location (Hewett: [0112] These location estimates may be distributed over an area or volume whose size depends on noise and the measurement uncertainty. As the number of measurements increases, the average location estimate can converge to a smaller area or volume whose size is limited by the fundamental measurement uncertainty. Once the size of the area or volume reaches a predetermined threshold, the processor sets an appropriate tag location (e.g., the centroid of the area or volume) and uses this tag location as a reference for similar tags. The system may repeat this process until a desired number or set of RFID tags have been added to the pool of virtual reference tags. [0113] The system may identify changes in a cohort of RFID tags by looking at the signature of each RFID tag in the cohort with respect to the signatures of its cohort members. The system may also look for changes (or a lack of change) in signatures received at other AOAs from the cohort. [0135] Antennas arrays monitor the location of each tote tag and each item tag. If the distance between one item tag and one tote tag is below a threshold value (e.g., less than the size of the tote), the system determines that the item corresponding to the item tag is in the tote. To improve the reliability of the detection, the system can further monitor the movement of the tote tag and the item tag. If they move together for a distance above a threshold value (e.g., more than 1 meter), the system can determine that the item and the tote are being carried by a customer.));
adjusting, by the inventory application, a reader device setting of the reader device based on the cluster data and a predictive model to optimize cluster-focused data received from the tags coupled to the subset of items in the cluster, wherein the reader device setting comprises at least one of a type of the signals, a frequency range of the signals, a position of the reader device, directional settings of the antenna system connected to the reader device, or an output power of the reader device (Hewett: [0037] Each antenna in the antenna array is also digitally controlled to change its relative phase difference with respect to the other antennas in the antenna array. Each distinct phase setting of the antenna array corresponds to a distinct angle of arrival (AOA) measured by the antenna array. As long as the array comprises three or more antennas, this enables the antenna array to be digitally steered across elevation AOAs between 0 and π (i.e., between 0 and 180 degrees) and azimuth AOAs between 0 and 2 π (i.e., between 0 and 360 degrees). [0123] The RFID tag readers 410 may vary the interrogation rate based on signals received from the RFID tag 410. If the RFID tag's response signals indicate that the RFID tag is moving at high speed, changing speed, or changing direction, the RFID tag readers 410 may increase their interrogation rates to provide finer spatiotemporal resolution of the RFID tag's motion. Conversely, if the RFID tag's response signals indicate that the RFID tag is stationary or moving slowly, then the RFID tag readers 410 may decrease their interrogation rates to conserve energy. The RFID tag readers 410 may increase or decrease their interrogation rates together or independently depending on the relative motion of the RFID tag 402.); and
receiving, by the reader device, the cluster-focused data from the tags coupled to the subset of items in the cluster (Hewett: [0112] These location estimates may be distributed over an area or volume whose size depends on noise and the measurement uncertainty. As the number of measurements increases, the average location estimate can converge to a smaller area or volume whose size is limited by the fundamental measurement uncertainty. Once the size of the area or volume reaches a predetermined threshold, the processor sets an appropriate tag location (e.g., the centroid of the area or volume) and uses this tag location as a reference for similar tags. The system may repeat this process until a desired number or set of RFID tags have been added to the pool of virtual reference tags. [0113] The system may identify changes in a cohort of RFID tags by looking at the signature of each RFID tag in the cohort with respect to the signatures of its cohort members. The system may also look for changes (or a lack of change) in signatures received at other AOAs from the cohort. [0123] FIG. 4 illustrates how the RFID systems and processes described above can be used to track an RFID tag 402 moving in an environment filled with obstructions, such as a store, stockroom, or warehouse. In this example, a pair of RFID tag readers 410a and 410b (collectively, RFID tag readers 410) interrogate the RFID tag 402 by transmitting RFID interrogation signals at regular intervals, e.g., at a rate of about 0.01 Hz to about 1.0 Hz. The RFID tag readers 410 may vary the interrogation rate based on signals received from the RFID tag 410. If the RFID tag's response signals indicate that the RFID tag is moving at high speed, changing speed, or changing direction, the RFID tag readers 410 may increase their interrogation rates to provide finer spatiotemporal resolution of the RFID tag's motion. Conversely, if the RFID tag's response signals indicate that the RFID tag is stationary or moving slowly, then the RFID tag readers 410 may decrease their interrogation rates to conserve energy. The RFID tag readers 410 may increase or decrease their interrogation rates together or independently depending on the relative motion of the RFID tag 402.).
Hewett fails to disclose a method and system performed by an inventory system to perform inventory tracking and control in a warehouse, wherein the method comprises:
moving along a conveyor belt in the warehouse;
adjusting, by the inventory application, a reader device setting of the reader device based on a predictive model.
Sweeney teaches a method and system performed by an inventory system to perform inventory tracking and control in a warehouse, wherein the method comprises:
moving along a conveyor belt in the warehouse (Sweeney: [0033] Objects to monitor may therefore include not only RFID interrogators, but also containers, trucks, conveyor belts, doors, and palette storage areas and [0062] The monitor reflects the activity of a set of interrogators at a particular warehouse.);
adjusting, by the inventory application, a reader device setting of the reader device based on a predictive model (Sweeney: [0032] The system 105 may also send signals to RFID interrogators 107-109 and RFID tags 110-112 for testing, for gathering data to build statistical models and to adjust operating parameters of these devices to improve their performance or to compensate for equipment failures. [0041] This embodiment uses a predictive model based on linear regression techniques to evaluate the direction, magnitude, and rate of change in a variable.).
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 Hewett to include items moving along a conveyor in a warehouse as taught by Sweeney, with the inventory monitoring as taught by Hewett with the motivation to examine the stream of data passing through a system of RFIDs to detect failures and partial failures, to compensate for failures and to optimize performance (Sweeney: [0006]).
As per Claim 10, Hewett discloses a method, wherein the signals and the cluster-focused data are radio frequency identification (RFID) signals (Hewett: [0072]).
As per Claims 11 and 16, Hewett discloses a method and system, wherein determining, by the inventory application, the one or more clusters of items based on the location of each of the items comprises:
determining, by the inventory application using the predictive model, one or more centroids based on the location of each of the items moving along the conveyor belt, wherein each of the one or more centroids represents a center point of the one or more clusters of items (Hewett: [0112], [0113], and [0135]); and
determining, by the inventory application, the one or more clusters of items based on the one or more centroids and the subset of items positioned within a range of the one or more centroids (Hewett: [0112], [0113], and [0135]),
wherein the predictive model is a k-means algorithm (Hewett: [0050]-[0069]).
As per Claims 12 and 18, Hewett discloses a method and system, wherein determining, by the inventory application, the cluster data comprises determining, by the inventory application, a quantity of the subset of items, and wherein the method further comprises determining, by the inventory application, whether the quantity of the subset of items included in the cluster is correct based on a known quantity of items that should be included in the cluster (Hewett: [0171]).
As per Claims 13 and 19, Hewett fails to disclose but Sweeney teaches a method and system, wherein determining, by the inventory application, the cluster data comprises determining, by the inventory application, a material of each item in the subset of items, and wherein adjusting, by the inventory application, the reader device setting of the reader device based on the cluster data, the predictive model, and the position on the conveyor belt comprises increasing a transmit power of the reader device when the material is metal (Sweeney: [0012]).
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 Hewett to include items moving along a conveyor in a warehouse as taught by Sweeney, with the inventory monitoring as taught by Hewett with the motivation to examine the stream of data passing through a system of RFIDs to detect failures and partial failures, to compensate for failures and to optimize performance (Sweeney: [0006]).
As per Claims 14 and 20, Hewett discloses a method and system, wherein, before emitting the signals towards the cluster, the method further comprises adjusting, by the inventory application, an antenna setting of at least one antenna in the antenna system based on the cluster data and the predictive model to emit cluster-focused signals towards the cluster (Hewett: [0112], [0113], and [0135]).
As per Claim 16, Hewett discloses a system, wherein the signals are WiFi signals (Hewett: [0041]).
As per Claims 21 and 26, Hewett fails to disclose but Sweeney teaches a method and system, wherein the predictive model is trained based on known items within each of the one or more clusters (Sweeney: Claim 22).
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 Hewett to include items moving along a conveyor in a warehouse as taught by Sweeney, with the inventory monitoring as taught by Hewett with the motivation to examine the stream of data passing through a system of RFIDs to detect failures and partial failures, to compensate for failures and to optimize performance (Sweeney: [0006]).
As per Claims 22 and 27, Hewett discloses a method and system, wherein, before emitting the signals towards the cluster, the method further comprises adjusting, by the inventory application, an antenna setting of at least one antenna in the antenna system based on the cluster data and the predictive model to emit cluster-focused signals towards the cluster, wherein the antenna setting comprises at least one of a type of the cluster-focused signals, a frequency range of the cluster-focused signals, a position of the at least one antenna, an orientation of the at least one antenna, an antenna gain of the at least one antenna, or a transmit power of the at least one antenna (Hewett: [0112], [0113], and [0135]).
As per Claims 23 and 28, Hewett discloses a method and system, further comprising determining, by the inventory application using the predictive model, at least one of: whether the subset of items included in the cluster is correct; whether the subset of items included in the cluster includes an incorrect item; or whether the subset of items included in the cluster is missing an item that should be in the cluster (Hewett: [0112], [0113], [0135], and [0171]).
As per Claim 24, Hewett discloses a method, further comprising determining, by the inventory application, that the cluster of items is moving along the conveyor belt at a speed and in a direction towards an area of the warehouse, wherein, before emitting the signals towards the cluster, the method further comprises adjusting, by the inventory application, an antenna setting of at least one antenna in the antenna system based on the speed and the direction of movement of the cluster of items, wherein the antenna setting is at least one of an orientation of the at least one antenna or a position of the at least one antenna (Hewett: [0112], [0113], [0135], and [0171]).
As per Claim 25, Hewett discloses a method, further comprising determining, by the inventory application, that the cluster of items is moving along the conveyor belt at a speed and in a direction towards an area of the warehouse, wherein adjusting, by the inventory application, the reader device setting of the reader device based on the cluster data and the predictive model comprises adjusting, by the inventory application, the reader device setting of the reader device based on the speed and the direction of movement of the cluster of items, wherein the reader device setting is at least one of a directional setting of the antenna system connected to the reader device or a position of the reader device (Hewett: [0112], [0113], [0135], and [0171]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REVA R MOORE whose telephone number is (571)270-7942. The examiner can normally be reached M-Th: 9:00-6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fahd Obeid can be reached at 571-270-3324. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/REVA R MOORE/ Examiner, Art Unit 3627
/FAHD A OBEID/ Supervisory Patent Examiner, Art Unit 3627
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