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 Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“first acquisition unit”, “second acquisition unit” and “learning unit” in claim 1;
“prediction unit” in claim 2;
“control unit: in claim 9;
“first prediction unit” and “second prediction unit” in claim 10.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-10 and 13-18 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. Specifically, Applicant has failed to provide sufficient description for the structures of the recited limitations “first acquisition unit”, “second acquisition unit” and “learning unit” in claim 1; “prediction unit” in claim 2; “first prediction unit” and “second prediction unit” in claim 10. Claims 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 16, 17 and 18 are also rejected for the same reason since they depend on claim 1 and have inherited the same deficiency.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-10 and 13-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim limitations “first acquisition unit”, “second acquisition unit” and “learning unit” in claim 1, “prediction unit” in claim 2, “first prediction unit” and “second prediction unit” in claim 10 invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to sufficiently disclose the corresponding structure for performing the entire claimed function and to clearly link the structure to the function. The lack of sufficient structure description of the limitations makes the metes and bounds of the apparatus claims unclear. Therefore, the claims 1, 2 and 10 are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Claims 3, 4, 5, 6, 7, 8, 9, 13, 14, 15, 16, 17 and 18 are also rejected for the same reason since they depend on claim 1 and have inherited the same deficiency.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 1-3, 9 and 11 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over LIU (CN 109812938 A, hereinafter as “LIU”).
Regarding claim 1, LIU teaches:
A machine learning device comprising:
a first acquisition unit configured to acquire environmental information on a target space ([0036] and [0061]: CO2 sensors acquire indoor CO2 concentration information);
a second acquisition unit configured to acquire number-of-people information indicating a number of people in the target space ([0036] and [0061]: infrared sensors acquire indoor number of people); and
a learning unit configured to learn the environmental information acquired by the first acquisition unit and the number-of-people information acquired by the second acquisition unit in association with each other, the environmental information including an actual carbon dioxide concentration in the target space ([0035] and [0037]: a neural learning unit trains a model based on acquired indoor air quality data and indoor population data).
LIU teaches specifically (underlines are added by Examiner for emphasis):
[0035] As shown in FIG. 1, a neural network-based air purification method includes the following steps:
[0036] S1. Real-time data acquisition step: real-time collection of indoor air quality data and number of people data through a data collection node.
[0037] S2. Data pre-analysis step: Introduce the collected indoor air quality data into the air quality pre-analysis model, further study and train the model, and combine the indoor population data and the current indoor air quality data to conduct analysis on the change the indoor air quality data.
[0061] Further, the data acquisition module includes a carbon dioxide sensor for collecting indoor carbon dioxide concentration, a PM2.5 sensor and a PM10 sensor for collecting indoor dust particles, a humidity sensor for collecting indoor air humidity, and a number of infrared counting sensors for collecting a number of people indoors.
Regarding claim 2, LIU teach(es) all the limitations of its base claim from which the claim depends on.
LIU further teaches:
a prediction unit configured to predict a carbon dioxide concentration in the target space after a certain period of time as a prediction value from the environmental information and the number-of-people information, based on a result of learning by the learning unit ([0043]: “the analysis of the change trend of the indoor air quality data includes analyzing the change of the indoor carbon dioxide concentration data in the next time period according to the current indoor number of people data, and changing the indoor time to the next time period according to the current indoor number of people data. The change in carbon dioxide concentration data was analyzed”. This teaches to predict a CO2 concentration change after a time period based on the model trained/learned based on the acquired CO2 concentration data and number of people data).
Regarding claim 3, LIU teach(es) all the limitations of its base claim from which the claim depends on.
LIU further teaches:
the prediction unit is configured to predict an amount of change in a carbon dioxide concentration in the target space as the prediction value ([0043]: “the analysis of the change trend of the indoor air quality data includes analyzing the change of the indoor carbon dioxide concentration data in the next time period according to the current indoor number of people data, and changing the indoor time to the next time period according to the current indoor number of people data. The change in carbon dioxide concentration data was analyzed”).
Regarding claim 9, LIU teaches:
A ventilation control device including the machine learning device according to claim 2 (see rejection of claim 2), the ventilation control device further comprising:
a control unit configured to control a ventilating device installed in the target space, based on the prediction value of the carbon dioxide concentration in the target space after the certain period of time ([0056-0057]: “S32. If the preset indoor carbon dioxide concentration threshold is reached, the indoor carbon dioxide concentration and the oxygen concentration are decreased by introducing outdoor air or by converting indoor carbon dioxide into oxygen. Further, the method of introducing the outdoor air includes: drawing the outdoor air into the air purifier through the air purifier and purifying it into the room to reduce the indoor carbon dioxide concentration and increasing the oxygen concentration; by converting the indoor carbon dioxide into oxygen. The method includes pumping indoor air into an air purifier through a fan, and generating oxygen by chemical reaction between carbon dioxide and sodium peroxide placed in the air purifier, and then introducing into the room to reduce indoor carbon dioxide concentration and increase oxygen concentration.”)
the prediction value being an output from the prediction unit of the machine learning device ([0055-0056]: “S31. Determine whether the predicted indoor carbon dioxide concentration data in the next time period reaches a preset indoor carbon dioxide concentration threshold; S32. If the preset indoor carbon dioxide concentration threshold is reached, the indoor carbon dioxide concentration and the oxygen concentration are decreased by introducing outdoor air or by converting indoor carbon dioxide into oxygen”).
Claim 11 recites a ventilation control method comprising operation steps conducted by the ventilation control device in claim 9 with patentably the same limitations. Therefore, claim 11 is rejected for the same reason recited in the rejection of claim 9.
Claim Rejections - 35 USC § 103
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.
Claims 4, 6-8 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over LIU in view of SHIKII (JP 2020144628 A, hereinafter as “SHIKII”).
Regarding claim 4, LIU teach(es) all the limitations of its base claim from which the claim depends on, but does not teach the second acquisition unit is further configured to acquire biometric information on the people in the target space, and the learning unit is further configured to learn the biometric information acquired by the second acquisition unit in association.
However, SHIKII teaches in an analogous art:
to acquire biometric information on the people in the target space ([0016]: “it is possible to acquire the person information related to the person and the air conditioning information related to the air conditioning, which can change the indoor carbon dioxide concentration”; And [0021]: “The person information may also include the gender of the person present in the room”), and
to learn the biometric information acquired ([0022]: “based on the gender of the person present in the room, the respiratory volume per unit time can be predicted to be relatively small when the gender is female, and the respiratory volume per unit time can be predicted to be relatively large when the gender is male. Therefore, the carbon dioxide gas concentration prediction device can present a more accurate carbon dioxide gas concentration based on the gender of the person”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified LIU based on the teaching of SHIKII, to make the machine learning device wherein the second acquisition unit is further configured to acquire biometric information on the people in the target space, and the learning unit is further configured to learn the biometric information acquired by the second acquisition unit in association. One of ordinary skill in the art would have been motivated to do this modification since it can help make “carbon dioxide gas concentration prediction device” to “present a more accurate carbon dioxide gas concentration”, as SHIKII teaches in [0022].
Regarding claim 6, LIU-SHIKII teach(es) all the limitations of its base claim from which the claim depends on.
SHIKII further teaches:
the biometric information includes gender ([0021]: “The person information may also include the gender of the person present in the room”), age, physique, or posture of the people in the target space.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified LIU based on the teaching of SHIKII, to make the machine learning device wherein the biometric information includes gender, age, physique, or posture of the people in the target space. One of ordinary skill in the art would have been motivated to do this modification since it can help make “carbon dioxide gas concentration prediction device” to “present a more accurate carbon dioxide gas concentration”, as SHIKII teaches in [0022].
Regarding claim 7, LIU teach(es) all the limitations of its base claim from which the claim depends on, but does not teach the environmental information includes a carbon dioxide concentration of outside air, or opening or closing of a door or a window of the target space.
However, SHIKII teaches in an analogous art:
the environmental information includes a carbon dioxide concentration of outside air, or opening or closing of a door or a window ([0030]: “this, when the window of the moving body is open, it is predicted that the carbon dioxide concentration is kept constant at the same concentration as the outside air, and it is possible to predict that the carbon dioxide concentration becomes a concentration closer to the same concentration as the outside air as the opening degree of the window of the moving body increases. Further, when the window of the moving body is closed, the carbon dioxide gas concentration can be predicted based on the person information. Therefore, the carbon dioxide gas concentration prediction device can present a more accurate carbon dioxide gas concentration based on the opening / closing and the opening degree of the window”) of the target space.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified LIU based on the teaching of SHIKII, to make the machine learning device wherein the environmental information includes a carbon dioxide concentration of outside air, or opening or closing of a door or a window of the target space. One of ordinary skill in the art would have been motivated to do this modification so that “the carbon dioxide gas concentration prediction device can present a more accurate carbon dioxide gas concentration based on the opening / closing and the opening degree of the window”, as SHIKII teaches in [0030].
Regarding claim 8, LIU-SHIKII teach(es) all the limitations of its base claim from which the claim depends on.
LIU further teaches:
the environmental information further includes a ventilation volume of the target space or a volume of the target space ([0046]: “S212, calculating a change trend of indoor carbon dioxide concentration per unit time according to the total amount of carbon dioxide generated indoors in a unit time combined with the volume of the indoor space”).
Claim 14 recites limitations similar to claim 4. Therefore, claim 14 is rejected for the same reason recited in the rejection of claim 4.
Claim 15 recites limitations similar to claim 7. Therefore, claim 15 is rejected for the same reason recited in the rejection of claim 7.
Claim 16 recites limitations similar to claim 4. Therefore, claim 16 is rejected for the same reason recited in the rejection of claim 4.
Claim 17 recites limitations similar to claim 7. Therefore, claim 17 is rejected for the same reason recited in the rejection of claim 7.
Claim 18 recites limitations similar to claim 7. Therefore, claim 18 is rejected for the same reason recited in the rejection of claim 7.
Claims 10 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over LIU in view of Reeder (US 9182751 B1, hereinafter as “Reeder”).
Regarding claim 10, LIU teaches:
A ventilation control device including the machine learning device according to claim 1 (see rejection of claim 1), the ventilation control device further comprising:
a first prediction unit configured to predict a carbon dioxide concentration in a first target space after a certain period of time as a prediction value from the environmental information and the number-of-people information of the first target space, based on a result of learning by the learning unit of the machine learning device ([0043]: “the analysis of the change trend of the indoor air quality data includes analyzing the change of the indoor carbon dioxide concentration data in the next time period according to the current indoor number of people data, and changing the indoor time to the next time period according to the current indoor number of people data. The change in carbon dioxide concentration data was analyzed”. This teaches to predict a CO2 concentration change after a time period based on the model trained/learned based on the acquired CO2 concentration data and number of people data);and
a control unit configured to control
a ventilation device installed in the first target space, based on the prediction value of the carbon dioxide concentration in the first targe space after the certain period of time ([0056-0057]: “S32. If the preset indoor carbon dioxide concentration threshold is reached, the indoor carbon dioxide concentration and the oxygen concentration are decreased by introducing outdoor air or by converting indoor carbon dioxide into oxygen. Further, the method of introducing the outdoor air includes: drawing the outdoor air into the air purifier through the air purifier and purifying it into the room to reduce the indoor carbon dioxide concentration and increasing the oxygen concentration; by converting the indoor carbon dioxide into oxygen. The method includes pumping indoor air into an air purifier through a fan, and generating oxygen by chemical reaction between carbon dioxide and sodium peroxide placed in the air purifier, and then introducing into the room to reduce indoor carbon dioxide concentration and increase oxygen concentration”), the prediction value being an output from the first prediction unit ([0055-0056]: “S31. Determine whether the predicted indoor carbon dioxide concentration data in the next time period reaches a preset indoor carbon dioxide concentration threshold; S32. If the preset indoor carbon dioxide concentration threshold is reached, the indoor carbon dioxide concentration and the oxygen concentration are decreased by introducing outdoor air or by converting indoor carbon dioxide into oxygen”).
LIU teaches all the limitations except a second prediction unit configured to predict a carbon dioxide concentration in a second target space after a certain period of time as a prediction value from the environmental information and the number-of-people information of the second target space, based on a result of learning by the learning unit of the machine learning device; and the control unit is configured to control a ventilating device installed in the second target space, based on the prediction value of the carbon dioxide concentration in the second target space after the certain period of time, the prediction value being an output from the second prediction unit.
However, Reeder teaches in an analogous art that CO2 concentrations in different zones are monitored and controlled independently ([Col. 7 Lines 19-25]: “CO2 sensors associated with the monitoring system can sample CO2 concentration levels in different zones of a property at regular time intervals such as every minute and can transmit the data identifying the CO2 concentrations to the CO2 monitoring control unit 110. In some implementations, zones can be defined by rooms of a property”; And [Col. 19 Lines 55-66]: “human activity information can be used by the monitoring system to control CO2 concentrations within a property. For example, a target CO2 concentration for a property may be 600 PPM, and various rooms of a property may have slightly varying CO2 concentrations. For example, a kitchen may have a CO2 concentration of 1000 PPM, a bedroom a concentration of 500 PPM, and a laundry room a concentration of 800 PPM. Based on determining that a user is in the kitchen, the monitoring system can control appliances and/or HVAC components of the property to reduce the CO2 concentration at the property”).
Reeder’s teaching can be incorporated into LIU to monitor and control CO2 concentration in different spaces independently. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified LIU based on the teaching of Reeder, to make the ventilation control device to further comprise a second prediction unit configured to predict a carbon dioxide concentration in a second target space after a certain period of time as a prediction value from the environmental information and the number-of-people information of the second target space, based on a result of learning by the learning unit of the machine learning device, and the control unit to further control a ventilating device installed in the second target space, based on the prediction value of the carbon dioxide concentration in the second target space after the certain period of time, the prediction value being an output from the second prediction unit. One of ordinary skill in the art would have been motivated to do this modification in order to “improve property monitoring and automation technology”, as Reeder teaches in [Col. 1 Line 37].
Claim 12 recites a ventilation control method comprising operational steps conducted by the ventilation control device of claim 10 with patentably the same limitations. Therefore, claim 12 is rejected for the same reason recited in the rejection of claim 10.
Claims 5 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over LIU in view of SHIKII, and in further view of FURUHASHI (JP 2021046983 A, hereinafter as “FURUHASHI”).
Regarding claim 5, LIU-SHIKII teach(es) all the limitations of its base claim from which the claim depends on, but do not teach the biometric information includes a conversation amount or a body temperature of the people in the target space.
However, FURUHASHI teaches in an analogous art:
the biometric information includes a conversation amount or a body temperature ([0080]: “Since it can be determined that the activity amount of the person 50 is larger as the body temperature of the person 50 is higher, it is considered that the amount of carbon dioxide emission from the person 50 is larger”) of the people in the target space.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified LIU-SHIKII based on the teaching of FURUHASHI, to make the machine learning device wherein the biometric information includes a conversation amount or a body temperature of the people in the target space. One of ordinary skill in the art would have been motivated to do this modification so “an increase in the carbon dioxide concentration in the room can be more reliably prevented”, as FURUHASHI teaches in [0080].
Regarding claim 13, LIU-SHIKII-FURUHASHI teach(es) all the limitations of its base claim from which the claim depends on.
SHIKII further teaches:
the biometric information includes gender ([0021]: “The person information may also include the gender of the person present in the room”), age, physique, or posture of the people in the target space.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified LIU-FURUHASHI based on the teaching of SHIKII, to make the machine learning device wherein the biometric information includes gender, age, physique, or posture of the people in the target space. One of ordinary skill in the art would have been motivated to do this modification since it can help make “carbon dioxide gas concentration prediction device” to “present a more accurate carbon dioxide gas concentration”, as SHIKII teaches in [0022].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES CAI whose telephone number is (571)272-7192. The examiner can normally be reached on M-F 8-5 EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached on 571-272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CHARLES CAI/Primary Patent Examiner, Art Unit 2115