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 .
Specification
The disclosure is objected to because of the following informalities:
Par. 1 includes multiple citations using hyperlinks that are indefinite.
Appropriate correction is required.
Claim Objections
Claims 10, 19 and 20 are objected to because of the following informalities:
For claim 10, the claim does not end with a period.
Claim 19, line 2, “the energy” lacks antecedent basis. Also, the term “a” should be inserted after “over”.
Claim 20, line 2, “the amount of energy” lacks antecedent basis.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
4, 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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
With regard to claim 1, it is not understood how a physical ventilation device and a first blower assembly can include non-physical elements, such as a first mathematical equation and a current limit. The fact that these non-physical elements are listed with another physical element, such as a blower motor, makes this indefinite.
Further in claim 1, lines 6-8, it states, “wherein the first mathematical equation: (i) was created using a neural network to…” First, since the claim states that the mathematical equation “was” created, the claim is indefinite since it is not known when this was. Second, the sentence is incomplete since it ends with the term “to.” To do what? It appears that these issues can be solved by just stating that “the mathematical equation is created using a neural network to determine an estimated blower air flow….”
With regard to claim 11, it contains similar issues as described in claim 1 above. A physical “circuit” cannot have mathematical equations. Rather, the circuitry therein is possibly designed/configured using mathematical equations.
Claim 17 has similar issues as described above.
All of the dependent claims are rejected due to their dependency of their respective rejected independent claims.
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 (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 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 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Blanchard (2019/0376715), published on December 12, 2019.
With regard to claim 1, Blanchard teaches a ventilation system with air flow modification system derived from a neural network (Abstract, par. 10), the ventilation system comprising:
a ventilation device including: (Par. 10)
a first blower assembly including a blower motor and a first mathematical equation (Par. 10),
and a pre-determined current limit for the blower motor (Par. 49 teaches that there is a limit to the amount of current that can be applied to the blower motor);
wherein the first mathematical equation: (i) was created using a neural network to (Par. 44), and (ii) determines an estimated blower air flow for the first blower assembly (Pars. 44, 48); and
wherein a warning is provided to the user, when an air flow set point is set to a value that requires current supplied to the blower motor is greater than the pre-determined current limit for the blower motor (Par. 49).
With regard to claim 2, Blanchard teaches the ventilation system of claim 1, wherein the estimated blower air flow is within 5% of an air flow generated by the blower motor (Pars. 63, 65).
With regard to claim 3, Blanchard teaches the ventilation system of claim 1, further comprising a first damper operably associated with the first blower assembly and having a plurality of positional settings (Par. 45 teaches that the control circuit can send output signals to a motorized damper taught by Michaud et al. (16/242,498), which is incorporated by reference. Michaud et al. teaches that the damper has a plurality of positional settings (Abstract)); and
wherein the first mathematical equation is further configured to utilize the positional setting of the first damper in determining the estimated blower air flow for the first blower assembly (Pars. 45, 68 teach that multiple mathematical equations and sets of air flow parameters may be used, as well as a damper may be used to increase the internal restriction of the ventilation device to bring the pressure within the flow estimation operating limits).
With regard to claim 4, Blanchard teaches the ventilation system of claim 3, wherein the ventilation system is configured to control the positional setting of the first damper based on the air flow set point (Pars. 45, 68 teach that a damper may be used to increase the internal restriction of the ventilation device to bring the pressure within the flow estimation operating limits).
With regard to claim 5, Blanchard teaches the ventilation system of claim 1, wherein the ventilation device includes a plurality of mathematical equations configured to determine the estimated blower air flow for the first blower assembly (Pars. 67, 68 teach that it may be advantageous to have multiple separate mathematical equations); and
wherein one mathematical equation of the plurality of mathematical equations is selected to be used to control the blower motor based upon a set of operating parameters. (Pars. 67, 68 teach that is may be advantageous to have multiple mathematical equations, because each equation and set of air flow parameters may be used in a specific situation).
With regard to claim 6, Blanchard teaches the ventilation system of claim 5, wherein the set of operating parameters includes density of the air external to the ventilation system (Par. 67).
With regard to claim 7, Blanchard teaches the ventilation system of claim 5, wherein the set of operating parameters includes a temperature of air external to the ventilation system (Par. 67).
With regard to claim 8, Blanchard teaches the ventilation system of claim 5, wherein the set of operating parameters includes a humidity of air external to the ventilation system (Par. 67).
With regard to claim 9, Blanchard teaches the ventilation system of claim 5, wherein the set of operating parameters include: (1) an identification of the type of an air filter installed in the ventilation system, (11) inclusion of a heat recovery core within the ventilation system, (iv) inclusion of an air handler, or (v) inclusion of an HVAC (Par. 68).
With regard to claim 10, Blanchard teaches the ventilation system of claim 1, further includes a communication module that is capable of receiving an updated mathematical equation from a remote location; and
wherein the ventilation device is capable of replacing the first mathematical equation with the updated mathematical equation (Par. 63).
With regard to claim 11, Blanchard teaches a ventilation system with air flow modification system derived from a neural network, the ventilation system (Abstract, par. 10) comprising:
a first blower assembly including a blower motor and a control circuit, said control circuit having a plurality of mathematical equations configured to determine an estimated blower air flow for the first blower assembly (Pars. 10, 67, 68);
wherein each of the plurality of mathematical equations include a set of air path parameters of the blower motor that are derived from the use of a neural network (Pars. 44, 67, 68); and
wherein one mathematical equation of the plurality of mathematical equations is selected to be used to control the blower motor based upon a set of installation parameters (Par. 68 teaches that it may be advantageous to have at least twenty mathematical equations and sets of air flow parameters, where one set of parameters can account whether an air handler or HVAC unit is installed).
With regard to claim 12, Blanchard teaches the ventilation system of claim 11, wherein the estimated blower air flow is within 5% of an air flow generated by the blower motor (Pars. 63, 65).
With regard to claim 13, Blanchard teaches the ventilation system of claim 11, further comprising a first damper operably associated with the first blower assembly and having a plurality of positional settings(Par. 45 teaches that the control circuit can send output signals to a motorized damper taught by Michaud et al. (16/242,498), which is incorporated by reference. Michaud et al. teaches that the damper has a plurality of positional settings (Abstract)); and
wherein the first mathematical equation is further configured to utilize the positional setting of the first damper in determining the estimated blower air flow for the first blower assembly (Pars. 45, 68 teach that multiple mathematical equations and sets of air flow parameters may be used, as well as a damper may be used to increase the internal restriction of the ventilation device to bring the pressure within the flow estimation operating limits).
With regard to claim 14, Blanchard teaches the ventilation system of claim 13, wherein the ventilation system is configured to control the positional setting of the first damper based on an air flow set point (Pars. 45, 68 teach that a damper may be used to increase the internal restriction of the ventilation device to bring the pressure within the flow estimation operating limits).
With regard to claim 15, Blanchard teaches the ventilation system of claim 11, wherein the control circuit further includes a current limit for the blower motor (Par. 49 teaches that there is a limit to the amount of current that can be applied to the blower motor); and wherein a warning is provided to the user when an air flow set point is set to a value that requires the current supplied to the blower motor to be greater than the current limit (Par. 49).
With regard to claim 16, Blanchard teaches the ventilation system of claim 11, further includes a communication module that is capable of receiving an updated mathematical equation from a remote location; wherein the control circuit is capable of replacing the first mathematical equation with the updated mathematical equation (Par. 63); and wherein the updated mathematical equation determines the estimated blower air flow for the first blower assembly based upon the following inputs: (i) updated air path parameters of the blower motor that are derived from the use of a neural network and (ii) blower motor current (Pars. 44, 48, 49, 63).
With regard to claim 17, Blanchard teaches a ventilation system with air flow modification system derived from a neural network (Abstract, par. 10), the ventilation system comprising: a first blower assembly including: (i) a blower motor, (i1) a control circuit, and (iii) communication module, said control circuit having a first mathematical equation derived from the use of a neural network (Pars. 10, 44, 63); wherein the communication module is capable of receiving an updated mathematical equation derived from the use of the neural network from a remote location; wherein the control circuit is capable of replacing the first mathematical equation with the updated mathematical equation (Par. 63).
With regard to claim 18, Blanchard teaches the ventilation system of 17, further comprising a first damper operably associated with the first blower assembly and having a plurality of positional settings (Par. 45 teaches that the control circuit can send output signals to a motorized damper taught by Michaud et al. (16/242,498), which is incorporated by reference. Michaud et al. teaches that the damper has a plurality of positional settings (Abstract)); and wherein the first mathematical equation is further configured to utilize the positional setting of the first damper in determining the estimated blower air flow for the first blower assembly (Pars. 45, 68 teach that multiple mathematical equations and sets of air flow parameters may be used, as well as a damper may be used to increase the internal restriction of the ventilation device to bring the pressure within the flow estimation operating limits).
With regard to claim 19, Blanchard teaches the ventilation system of claim 17, wherein the control circuit is configured to calculate the energy utilized by the ventilation system over pre-determined amount of time (Pars. 47-49 teach that the air flow can be regulated by regulating the current supplied by the blower. The current dictates the speed at which the blower motor turns the fan blades. If a set point is set higher, then an increase in current will be needed. It is interpreted that regulating/determining the current needed, is similar to calculating the energy utilized by the ventilation system. Also, since the set point is set by a user (Par. 45), the set point can change over different periods of time throughout the year, such as the change of seasons.
With regard to claim 20, Blanchard teaches the ventilation system of claim 17, wherein the control circuit is configured to calculate a projection for the amount of energy over a pre-determined amount of time (See claim 19 above. Further, par. 48 teaches that the mathematical equations used provide an estimated blower air flow. An estimation is similar to a projection).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SCOTT T BADERMAN whose telephone number is (571) 272-3644. The examiner can normally be reached 8-5 M-F, every other Friday off.
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, John Cottingham, can be reached at 571-272-1400. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SCOTT T BADERMAN/Supervisory Patent Examiner, Art Unit 2118