DETAILED CORRESPONDENCE
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 .
Status of Claims
Claims 1-14 have been canceled.
Claims 15-28 are new.
Claims 15-28 are pending.
Claim Interpretation
The claim elements do not invoke 35 U.S.C. § 112(f).
References
D1: EP3671272 ELSNER et al. June 24, 2020
Claim Rejections - 35 U.S.C. § 101
The following is a quotation of 35 U.S.C. 101 that 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 15-28 are rejected under 35 U.S.C. § 101.
Step 2A Prong 1: The claims recite the following limitation which is considered to be an abstract idea:
-method for fusion of classification results of a plurality of classification models in order to classify environment objects;
The above limitation, under its broadest reasonable interpretation, fall within the category of a mental process concepts performed in the human mind (including an observation, evaluation, judgment, opinion); 2106.04a2 III. Which when given its BRI is interpreted to be a judgement or observation as to whether or not sensor measurements are the same or different than what is considered to be a normal signal measurement.
Step 2a-Prong 2- The recitation of the additional element(s) of "using ultrasonic sensor devices in a mobile devices;" which merely adds insignificant extra-solution activity, i.e., data gathering, to the abstract idea. See MPEP 2106.05(g) - selecting a particular data source (Electric Power Group).
Therefore, when considered both individually and as a whole, the limitations of claim 15 are not indicative of integration into a practical application. See MPEP 2106.04(d).
Step 2B: The recitation of the additional element(s) is acknowledged, as identified above with respect to Prong 2 of Step 2A. The additional element does not add significantly more to the abstract idea for the same reason as addressed above with respect to Prong 2 of Step 2A. Additionally, the "using ultrasonic sensor devices in a mobile device" step is indicative of well-understood, routine and conventional activity found by the courts as set forth in MPEP 2106.05(d) II, particularly "[r]eceiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Even when considered as an ordered combination, the additional element of claim 15 does not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in the claim that transform the judicial exception into a patent eligible application such that the claim amounts to significantly more than the judicial exception itself. See MPEP 2106.05.
Therefore, the claims are found to be directed to nonstatutory subject matter.
Claim Rejections - 35 U.S.C. § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. § 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 15-28 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by D1.
With regards to claim 15, the D1 reference discloses the utilization of a method for combining classification results of a plurality of classification models (61a, 61b) in order to classify environment objects (U) by means of ultrasound sensor devices (3a, 3b) in a mobile device, the method having the steps of (in D1, too, different classification modules for the classification and tracking of environment objects are implicitly applied in the various ultrasound sensors 111 and 112 in [0028, 0037] with figure 1 due to their different positions on the motor vehicle (see Dl, [0040], different parametrizing of the tracks from the first and second sensor, with the description of the present application page 4, 3rd paragraph to page 5, 4th paragraph and box VIII, point 1 below); the corresponding combination also takes place in D1; see [0009, 0040, 0085]): - detecting (S1, S11) sensor signals of ultrasonic transducers (5) of the ultrasound sensor devices (3a, 3b) (D1, [0028, 0037]); - tracking a position[= tracking in D1] of detected environment objects (U) by the ultrasound sensor devices (3a, 3b) and classifying an objects type of the environment objects (U) by one of the classification models (61a, 61b) associated with each of the ultrasound sensor devices(3a, 3b) in order to obtain a respective classification result (Dl, [0011, 0031, 0040-0048, 0067]); - in the event that it is established that a specific environment object (U) has entered a detection range of one of the ultrasound sensor device (3a, 3b) and was previously located in a detection region of a further of the ultrasound sensor devices (3a. 3b)(S3, S4), selecting (S7) one of the classification results [such as 'moving object' or 'reliable detection/track' in D1] for the specific environment object (U) depending on a classification quality (sigma_class) [ = range reliability in D1, 0070] based on the classification model (61a, 61b) and depending on the newness of the classification result (Dl, [0067, 0081, 0082], see also [0011, 0031, 0042, 0047,0048]).
With regards to claim 27, the D1 reference discloses a device for carrying out the method (Dl, [0054, 0085], figures 1, 3).
With regards to claim 28, the D1 reference discloses a machine-readable storage medium (Dl, [0054, 0085], figures 1, 3).
With regards to claim 16, the D1 reference discloses the classification result of that classification model (61a, 61b) is selected whose newness indicates a more recent classification, when the corresponding overall quality exceeds a predefined threshold value (since the overall quality is not defined in more detail, and in Dl, a further 'reliability' or quality or weighting or 'trust value' to obtain the classification result, the range reliability (medium ranges more reliable), which can also be an angular reliability etc.; see [0009, 0011, 0085], is used in addition to the newness of the classification/categorization/detection, the comparison of this quality with a threshold value is considered to be disclosed in light of D1; see the rating in 3 ranges in [0070] "medium range compared to a track associated with a shorter range and/or a longer range" the rating of which implies a respective threshold value).
With regards to claim 17, the D1 reference discloses the newness is assigned using an assignment function of a newness quality. (sigma_new), which indicates a quality which is higher the more recently the underlying sensor data were detected (as in Dl, [0067, 0081, 0082]), wherein an overall quality (sigma_tot) is determined from the classification quality (sigma_class) (can be the range of the angular reliability in D1; see [0011, 0031, 0085]) and the newness quality (sigma_new) (as in Dl, [0067, 0081, 0082]), wherein the classification result is selected depending on the overall qualities (sigma_tot) of the classification results of the classification models (61a, 61b) ( this can also be read to D1, [0011, 0031, 0085]: "obtaining track reliability data for each track, wherein the reliability data comprises track life time [=newness quality, 0067, 0081, 0082], track detection history, track range and track angle [=classification qualities]; a determining module Sx3 for determining a track reliability weight for each track based on the track reliability data, wherein the determining comprises quantifying grades of membership into a plurality of predetermined fuzzy sets").
With regards to claim 18, the D1 reference discloses the overall quality (sigma_tot) is determined by forming weighted average values from the classification quality (sigma_class) (Dl, [0031] "For instance, track reliability may relate to a measure of error in the position estimates associated with the track. A reliably estimated object track is associated with a smaller position error than a less reliably estimated object track. Position error may be measured, e.g., in terms of mean-squared error (MSE) or average error, or maximum error over a limited time period.") and the newness quality (sigma_new) (Dl, [0067, 0081, 0082]) (see Dl, [0011, 0031, 0085]).
With regards to claim 19, the D1 reference discloses the classification models are data-based, wherein the classification qualities (sigma_class) are determined as values of an element of an output vector of the classification models(61 a, 61 b) with the highest value (if you take the "maximum error" of the object position as "range reliability" in D 1, [0031], it is obvious that this can be in the form of an output vector of the respective classification model).
With regards to claim 20, the D1 reference discloses the newness is assigned using an assignment function to a newness quality (sigma_new), which indicates a quality which is higher the more recently the underlying sensor data were detected (as in Dl, [0067, 0081, 0082]), wherein an overall quality (sigma_tot) is determined from individual qualities (can be the range of the angular reliability in D1; see [0011, 0031, 0085]) and the newness quality (sigma_new) (as in Dl, [0067, 0081, 0082]), wherein the classification result is selected depending on the overall qualities (sigma_tot) of the classification results of the classification models (61a, 61b) (this can also be read to Dl, [0011, 0031, 0085]: "obtaining track reliability data for each track, wherein the reliability data comprises track life time [=newness quality, 0067, 0081, 0082], track detection history, track range and track angle [=classification qualities]; a determining module Sx3 for determining a track reliability weight for each track based on the track reliability data, wherein the determining comprises quantifying grades of membership into a plurality of pre-determined fuzzy sets").
With regards to claim 21, the D1 reference discloses the classification qualities (sigma_class) are determined by forming a weighted average value of the individual qualities (Dl, [ 0020, 0031, 0084, 0091] "According to aspects, the fusing comprises fusing the first and the second track based on a weighted average of fuzzy set membership degrees and respective trust functions." or "A reliably estimated object track is associated with a smaller position error than a less reliably estimated object track. Position error may be measured, e.g., in terms of mean-squared error (MSE) or average error, or maximum error over a limited time period."), wherein the individual qualities comprise at least one of the following: a detection quality a feature quality (sigma_det) and a model quality (sigma_mod) (this general nomenclature can be read to any 'reliability' features in Dl, [0067, 0081, 0082], for example to" track detection history, track range and track angle").
With regards to claim 22, the D1 reference discloses the detection quality (sigma_det) is ascertained dependent on a quotient from the number of correct classifications{how is 'correct' defined and checked or established?] of the specific environment object (U) and the total number of classifications of the specific environment object (U) (D1 also considers the frequency of the object detections; see [0048]).
With regards to claim 23, the D1 reference discloses the characteristic quality (sigma_char is determined dependent on the contributions of signal characteristics, which result from the sensor signals, for ascertaining the classification result for classifying the specific environment object (U) (see Dl, [0011, 0031, 0067, 0081, 0082, 0085], this can be any signal parameters) and on a detection feature ( this can also be any signal parameters; see D1, [0011, 0031, 0067, 0081, 0082, 0085], a relative position (see D1, [0011, 0031, 0037, 0085]) of the specific environment object to the ultrasonic transducer (5) which is assigned to the signal feature.
With regards to claim 24, the D1 reference discloses the model quality (sigma_mod) is determined by selecting the classification model (61a, 61b) (according to the description of the present application, page 4, 3rd paragraph to page 5, 4th paragraph; the classification model is inherent to the respective sensor due to its position and orientation; "selecting the classification model" therefore appears possible only within the framework of sensor calibration, if selecting one of the "classification results" of a specific sensor (as in claim 15) this is also the case in D1; see Dl, [0011, 0031, 0042, 0047, 0048, 0067, 0073, 0081, 0082], as outlined above in relation to claim 15).
With regards to claim 25, the D1 reference discloses the overall qualities (sigma_tot) are determined by a weighted average value of the individual qualities (Dl, [0020, 0031, 0084, 0091]).
With regards to claim 26, the D1 reference discloses the overall qualities (sigma_tot) are determined by a weighted average value of the individual qualities (Dl, [0020, 0031, 0084, 0091]) and the newness quality (Dl, [0067, 0081, 0082] with [0011, 0031, 0042, 0047, 0048]).
Examiner Note
Examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the Applicant. However, any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Applicant, in preparing the response, should consider fully the entire reference as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dan Pihulic whose telephone number is 571-272-6977. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Helal Algahaim, can be reached on 571-270-5227.
/Daniel Pihulic/
Primary Examiner
Art Unit 3645