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 .
DETAILED ACTION
Summary
This action is in reply to Applicant’s Amendments and Remarks filed on 8/10/2026.
Claims 1-20 are pending.
Response to Arguments
Applicant's arguments with respect to amended claims and originally presented claims have been fully considered but they are moot in view of the new grounds of rejection.
During patent examination, the pending claims must be "given their broadest reasonable interpretation consistent with the specification." Phillips v. AWH Corp., 415 F.3d 1303, at 1316 (Fed. Cir. 2005). See also In re Hyatt, 211 F.3d 1367, 1372, 54 USPQ2d 1664, 1667 (Fed. Cir. 2000).
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) 1-11, 13, 15-16 and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHIN et al (WO 2019214799 A1) in view of Lee et al (US 20190287520 A1).
Regarding claim 1, CHIN discloses a computer-implemented method [e.g. FIG. 2 and 5; the system implemented by a processor or computer] comprising:
a first stored rule for operating a vehicle [e.g. setting/measuring the temperature in the vehicle; FIG. 2-3; 224 and 226; The machine learning offline processing module 224 takes the historical user and vehicle data from the data lake 226 (data storage) and uses machine learning to build a user profile of user preferences, interests, habits, etc.] including:
receiving a set of auditory speech signals [e.g. FIG. 1 and 3; voice request] generated by a user [e.g. user or driver];
determining, from the set of auditory speech signal, an intent [page 8; voice request, such as intent];
mapping a first portion [e.g. FIG. 3-4; page 10-12; “Heat up my car”] in the intent to a first condition [e.g. heat up my car before my next trip], wherein the first condition corresponds to at least one operation of a first component of the vehicle [measuring the temperature in the vehicle];
mapping a second portion of the intent [e.g. before my next trip] to a first action [heating up], wherein the first action identifies at least one action performed by a second component of the vehicle [the heater in the vehicle will be operating];
generating a routine [e.g. pre-heating up for 15 minutes before the nest trip to home] that specifies the first condition for the first action;
comparing the routine to a set of stored rules [e.g. page 12; The context and machine learning system 220 checks to see if there is a rule that may be applied to the voice request (406)], wherein each stored rule in the set of stored rules [e.g. FIG. 2-3; 224 and 226; The machine learning offline processing module 224 takes the historical user and vehicle data from the data lake 226 and uses machine learning to build a user profile of user preferences, interests, habits, etc.] includes at least one condition and at least one action [e.g. heat profile of the user];
upon determining that the routine does not overlap with at least one stored rule in the set of stored rules [e.g. FIG. 3-4; it is determined that there is no rule applicable to the voice request, the spoken dialogue system may execute the request],
subsequent to the determination, comparing one or more values [e.g. temperature values] with the first stored rule to determine that the first condition has been satisfied [e.g. FIG. 2-4; page 12-14; if the current context = [extemal_temp = -5, internal_temp = 15, TTL_before_next_trip = 15 min; satisfy the user’s heat habit]; and
causing, based on the first stored rule, the second component of the vehicle to perform the first action [e.g. e
heating up the car].
Although CHIN discloses the user profile learning module uses machine learning on the historic user and vehicle data to form a user profile )behavior rule/pattern) of user preferences and storing the personal habits, it is noted that CHIN differs to the present invention in that CHIN fails to explicitly disclose the detail of the first condition and storing a routine as a stored rule.
However, Lee teaches the well-known concept of a computer-implemented method [e.g. FIG. 1-2 and ; the processing system implemented by a processors] comprising: registering a first stored rule for operating a vehicle [e.g. FIG. 1-2 and 8; store a rule and dialog template related the rule in the processing system for a vehicle]; generating a routine [e.g. FIG. 14-15; the routing for controlling AC of the vehicle] that specifies a first condition as a prerequisite for a first action [setting the temperature to 24 degree if AC is ON]; and upon determining that the routine does not overlap with at least one stored rule in the set of stored rules [e.g. FIG. 8-9 and 21; 520; if the extracted condition and consequence is new rule after compared with rule stored] storing the routine as the first stored rule [e.g. FIG. 21; 540].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 2, CHIN and Lee further disclose mapping the first portion of intent to the first condition comprises: comparing the first portion of intent to a set of pre-defined conditions, wherein each pre- defined condition in the set of pre-defined conditions identifies at least one of: a state value for a component of the vehicle, or a measured value generated by a component of the vehicle [e.g. CHIN: measuring the current temperature], or a value determined by a component of the vehicle;
determining that the first portion of intent corresponds to at least a first pre-defined condition in the set of pre-defined conditions [e.g. CHIN: e.g. FIG. 3-4; page 10-12; “Heat up my car”] ; and
setting the first condition to match the first pre-defined condition [e.g. CHIN: FIG. 2-4; page if the current context = [extemal_temp = -5, internal_temp = 15, TTL_before_next_trip = 15 min].
Regarding claim 3, CHIN and Lee further disclose determining that a set of conditions included in a second stored rule have been satisfied [e.g. CHIN: IF-THEN rule pattern using a pattern template with a set of conditions; temperature conditions, driving speed; Lee: FIG. 8 and 21],
wherein the set of conditions includes at least a second condition and a third condition [e.g. CHIN: IF-THEN rule pattern using a pattern template with a set of conditions; temperature conditions, driving speed; Lee: FIG. 8 and 21]; and
causing a third component of the vehicle to perform a second action of the second stored rule [e.g. CHIN: controlling the speed or seat position].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 4, CHIN and Lee further disclose comparing the second portion of intent to a set of pre-defined actions, wherein each pre-defined condition in the set of pre-defined actions identifies at least one of:
a vehicle behavior performed by a component of the vehicle [e.g. CHIN: heater to heat up the vehicle], or
an application event executed by a component of the vehicle, or
determining that the second portion of intent corresponds to at least a first pre-defined action in the set of pre-defined actions [CHIN: heat up my car before my next trip], and
setting the first action to match the first pre-defined action [e.g. CHIN: FIG. 2-4; page if the current context = [extemal_temp = -5, internal_temp = 15, TTL_before_next_trip = 15 min].
Regarding claim 5, CHIN and Lee further disclose the second component of the vehicle to perform a set of actions included in the routine [e.g. CHIN: FIG. 2-3; [desired_temp = 24, defrost=true, driver_seat_warm = true, heat_control = 5, ventilation = on],
wherein the set of actions includes at least the first action and a second action [e.g. CHIN: heat control or driver seat warm].
Regarding claim 6, CHIN and Lee further disclose receiving an indication of a change of one or more values associated with the operation of the first component of the vehicle [e.g. CHIN: FIG. 4; heater is on, the temperature is going up], wherein determining that the first condition has been satisfied comprises determining that the change of the one or more values associated with the operation of the first component of the vehicle satisfy the first condition [e.g. CHIN: FIG. 2-4; page if the current context = [extemal_temp = -5, internal_temp = 15, TTL_before_next_trip = 15 min].
Regarding claim 7, CHIN and Lee further disclose the first component of the vehicle or the second component of the vehicle is an infotainment subsystem, a navigation subsystem, an advanced driver assistance system (ADAS), or a temperature control subsystem [e.g. CHIN: FIG. 2-4; heat_control t0 desired temperature=24].
Regarding claim 8, CHIN and Lee further disclose determining a first speech portion from a first auditory speech signal included in the set of auditory speech signals [e.g. CHIN: FIG. 1 and 3-4; voice request]; wherein the first portion of the intent is determined from the first speech portion [CHIN: page 8; voice request, such as intent]; and determining the second speech portion from the first auditory speech signal [e.g. CHIN: FIG. 2-4; voice commands; 214 includes automatic speech recognition (ASR) for converting the voice request to a text; Lee: FIG. 2 and 8-9; recognize the dialog by the dialog processing system]; wherein the second portion of the intent is determined from the second speech portion [e.g. CHIN: page 8; voice request, such as intent];
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 9, CHIN and Lee further disclose before receiving a first auditory speech signal in the set of auditory speech signals [e.g. CHIN: FIG. 3-4; Lee: FIG. 8 and 21],
providing a first auditory prompt associated with the first condition [e.g. CHIN: Machine learning may learning a user’s habit, interest, preference, or the like from user’s data, and then form a user profile], determining a first speech portion from the first auditory speech signal; wherein the first portion of the intent is determined from the first speech portion [e.g. CHIN: page 8; voice request, such as intent]
upon receiving the first auditory speech signal, providing a second auditory prompt associated with the first action [e.g. CHIN: FIG. 2-4]; and
receiving a second auditory speech signal in the set of auditory speech signals [e.g. CHIN: warm up my car before next trip], wherein the second portion of the intent is determined from the second speech portion [e.g. CHIN: page 8; voice request, such as intent].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 10, CHIN and Lee further disclose parsing a first auditory speech signal included in the set of auditory speech signals to generate a set of speech portions [e.g. CHIN: FIG. 2-3; page 12];
generating, based on the set of speech portions, the intent that specifies (i) a value or state [e.g. CHIN: current temperature], and (ii) a target set of components [e.g. CHIN: measuring the temperature: Lee: FIG. 1-2 and 8];
validating the first intent with at least one of a set of pre-defined conditions or a set of pre-defined actions, wherein the routine is generated in response to validating the first intent [e.g. CHIN: FIG. 2-4; page if the current context = [extemal_temp = -5, internal_temp = 15, TTL_before_next_trip = 15 min].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 11, CHIN and Lee further disclose determining that the routine overlaps with the at least one stored rule when: the routine is a duplicate of the at least one stored rule [e.g. CHIN: FIG. 2-4; Lee: FIG. 8 and 21]; or the routine contradicts at least one action included in the at least one stored rule.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]].
Regarding claim 13 and 15-16, this is a non-transitory computer-readable storage medium that includes same limitation as in claim 1, 6, and 4 above respectively, the rejection of which are incorporated herein.
Regarding claim 18-20, this is an apparatus that includes same limitation as in claim 1 and 6-7 above respectively, the rejection of which are incorporated herein.
Claim(s) 12 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHIN et al (WO 2019214799 A1) in view of Lee et al (US 20190287520 A1) and Penilla et al (US 20180061415 A1).
Regarding claim 12, CHIN and Lee further disclose determining that the routine overlaps with at least one stored rule in the set of stored rules [e.g. CHIN: FIG, 2-4; if there is a rule that may be applied to the voice request (406) like “heat up my car”; providing a prompt [e.g. CHIN: FIG. 4; response to the user based on the voice command] to the user; Lee: FIG. 8 and 14-15], but CHIN and Lee fail to explicitly disclose modifying the routine.
However, Penilla teaches the well-known concept of providing a prompt [e.g. FIG. 23-27; response respond to the user's voice input] to the user [e.g. the driver] to select at least one of (i) replacing the at least one stored rule with the routine, (ii) modifying the routine [e.g. FIG. 11 and 23; [0196-0198]; showing to the user settings that have been learned and provides the user with options to modify learned settings], or (iii) discarding the routine.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee and determining the behavior of a driver technique by Penilla as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]] and improved the safety of the driver [See Penilla; [0338]].
Regarding claim 17, this is a non-transitory computer-readable storage medium that includes same limitation as in claim 12 above, the rejection of which are incorporated herein.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over CHIN et al (WO 2019214799 A1) in view of Lee et al (US 20190287520 A1) and Van Buer et al (US 20050125148 A1).
Regarding claim 14, CHIN and Lee further disclose the one or more non-transitory computer-readable media storing the first stored rule [e.g. CHIN: FIG. 2-4; Lee: FIG. 8 and 21], but CHIN and Lee fail to explicitly disclose a C Language Integrated Production System (CLIPS) rule.
However, Van Buer teaches the well-known concept of comprising a C Language Integrated Production System (CLIPS) for a vehicle operating/control device [e.g. FIG. 1-2; [0022]; such as C Language Integrated Production System (CLIPS) or Java Expert Shell System (JESS)].
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the computer-implemented system disclosed by CHIN to exploit the well-known creating new rules associated with event/routine technique taught by Lee and learning engine technique by Van Buer as above, in order to provide a best service for the user's actual intention or a service needed the most for the user [See Lee; [0266]] and improved driving condition for the operator [See Van Buer; [0018]].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Huang et al (US 20080103779 A1).
Yae (US 20210264911 A1).
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHUBING REN whose telephone number is (571)272-2788. The examiner can normally be reached Monday-Friday 9am-5pm.
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/ZHUBING REN/Primary Examiner, Art Unit 2658
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