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 .
Claim Rejections - 35 USC § 102
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 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 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 1-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bhogal et al. (20200400317).
With respect to Independent claim 1 Bhogal teaches a cooking apparatus, comprising:
a cooking chamber configured to accommodate an object (par. 0032)
a sensor module (par. 0058) configured to measure a plurality of cooking state determination factors (par. 0094; par. 0143, 0146) of the object during cooking of the object in the cooking chamber (par. 0143, 0144);
a display (par. 0072, 0146); and
a controller (par. 0054) configured to perform control to:
obtain cooking state probability data (par. 0143, 0066, 0086) for each cooking stage of a plurality of cooking stages (par. 0143, 0066, 0086) of the object from the measured plurality of cooking state determination factors (par. 0143, 0066, 0086), and
output (par. 0146), via the display (par. 0146), information about a cooking state of the object corresponding to a highest cooking state probability (par. 0143 comparison of real time food parameter value and target food parameter) of the obtained cooking state probability data (par. 0146; ready to eat; error notification, probability specific actual, in real time; alternatively highest probability relative correct, incorrect).
With respect to Independent claim 8, a method of controlling a cooking apparatus including a cooking chamber configured to accommodate an object (par. 0032)
a sensor module (par. 0058) configured to measure a plurality of cooking state determination factors (par. 0094; par. 0143, 0146) of the object during cooking of the object in the cooking chamber (par. 0143, 0144);
a display (par. 0072, 0146); and
the method comprising:
obtaining cooking state probability data (par. 0143, 0066, 0086) for each cooking stage of a plurality of cooking stages (par. 0143, 0066, 0086) of the object from the measured plurality of cooking state determination factors (par. 0143, 0066, 0086), and
outputting (par. 0146), via the display (par. 0146), information about a cooking state of the object corresponding to a highest cooking state probability (par. 0143 comparison of real time food parameter value and target food parameter) of the obtained cooking state probability data (par. 0146; ready to eat; error notification, probability specific actual, in real time; alternatively highest probability relative correct, incorrect).
With respect to Independent claim 15, Bhogal teaches a cooking apparatus, comprising:
a cooking chamber configured to accommodate an object (par. 0032)
a sensor module (par. 0058) configured to measure a plurality of cooking state determination factors (par. 0094; par. 0143, 0146) of the object during cooking of the object in the cooking chamber (par. 0143, 0144);
a display (par. 0072, 0146); and
communication circuitry (par. 0057) configured to communicate with an external server (par. 0040 server = remote system; par. 0143 remote system)
a controller (par. 0054) configured to perform control to:
transmit (par. 0035; par. 0147 send measurements to remote system; par. 0131; par. 0122), to the external server via the communication circuitry (par. 0035; par. 0147; par. 0131 streamed from oven to remote system), cooking state probability data (par. 0035; par. 0131 current food parameter; 0143, 0066, 0086) for each cooking stage of a plurality of cooking stages (par. 0035, par. 0143, 0066, 0086) of the object from the measured plurality of cooking state determination factors (par. 0035; par. 0131, 0143, 0066, 0086), and
receive (par. 0032 received from remote system; par. 0119; par. 0146), from the external server via the communication circuitry (par. 0032; 0119 par. 0146), information about a cooking state of the object corresponding to a highest cooking state probability (par. 0143 comparison of real time food parameter value and target food parameter) of the transmitted cooking state probability data (par. 0146; ready to eat; error notification, probability specific actual, in real time; alternatively highest probability relative correct, incorrect) and
output (par. 0146), via the display (par. 0146), the information about the cooking state of the object (par. 0146; ready to eat; error notification).
With respect to claims 2 and 9, wherein the controller is configured to perform control to convert a cooking state (par. 0146 cooking parameter), obtained from each of the plurality of cooking state determination factors (par. 0143, 0144), into probability data for each cooking stage to obtain the cooking state probability data (par. 0119, 0146).
Claims 3 and 10, wherein the controller is configured to perform control to apply a preset weight (par. 0119 source of truth; par. 0143 real time, actual compared to target 1:1; par. 0089-0090 learning module) to the probability data for each cooking stage to obtain the cooking state probability data.
Claims 4 and 11, wherein the controller is configured to perform control to input the probability data for each cooking stage into a machine learning model (par. 0089-0090) trained from cooking state result data to obtain the cooking state probability data (par. 0091).
Claims 5 and 12, wherein the controller is configured to perform control to obtain the cooking state probability data, based on a regression learning model (par. 0090) using the cooking state result data and the probability data for each cooking stage as an input value (par. 0091).
Claims 6 and 13, wherein the controller is configured to perform control to input the probability data for each cooking stage into the machine learning model (par. 0091), based on the probability data for each cooking stage having at least one valid value (par. 0143 current/actual measurement).
Claims 7 and 14, wherein the plurality of cooking state determination factors of the object include gas data (par. 0058 gas analyzer), temperature data (par. 0058), and color data (par. 0103) of the object during a cooking time.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. 20210400778, 20200018551, 20170290095 directed to machine learning cooking sessions.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Steven Leff whose telephone number is (571) 272-6527. The examiner can normally be reached on Mon-Fri 8:30 - 5:00.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erik Kashnikow can be reached at (571) 270-3475. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/STEVEN N LEFF/Primary Examiner, Art Unit 1792