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 § 101 35 U.S.C. 101 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 1-1 4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Step 1: According to the first part of the analysis, in the instant case, claims 1- 8 are directed to a method , claim s 9-14 are directed to using an apparatus to perform the method. Thus, each of the claims falls within one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter). Regarding claim 1 : A method for detecting water quality, comprising: classifying a quality of water using a water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water; and utilizing a sequential learning unit for classification of impurities in the water . Step 2A Prong 1 : “ classifying a quality of water using a water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water ” is directed to math because the process transform raw, high frequency signal measurement into actionable, classified data through several mathematical steps: The core measurement relies on sound propagation to calculate flow and detect impurities . To interpret how to mixtures of contaminants alter the ultrasound signal, advanced mathematical techniques to analyze the frequency components of the echo. “ utilizing a sequential learning unit for classification of impurities in the water ” is directed to math because sequential learning models like a type of recurrent neural network are used for water quality classification. These models use matrices and vector operations to process sequences of water quality data (e.g. pH, dissolved oxygen, temperature over time) to predict future contamination, achieving high accuracy in classification tasks . Water quality data is often sequential (e.g. sensor reading taken every hour). Analyzing this requires statistical methods to identify patterns, trends, and correlations in the data over time to distinguish between safe and contaminated water. Each limitation recites in the claim is a process that, under BRI covers performance of the limitation in the mind but for the recitation of a generic “sensor and measurement” which is a mere indication of the field of use. Nothing in the claim elements precludes the steps from practically being performed in the mind. Thus, the claim recites a mental process. Further, the claim recites the step of " classifying a quality of water using a water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water; and utilizing a sequential learning unit for classification of impurities in the water ” which as drafted, under BRI recites a mathematical calculation. The grouping of "mathematical concepts” in the 2019 PED includes "mathematical calculations" as an exemplar of an abstract idea. 2019 PEG Section |, 84 Fed. Reg. at 52. Thus, the recited limitation falls into the "mathematical concept" grouping of abstract ideas. This limitation also falls into the “mental process” group of abstract ideas, because the recited mathematical calculation is simple enough that it can be practically performed in the human mind, e.g., scientists and engineers have been solving the Arrhenius equation in their minds since it was first proposed in 1889. Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited calculation, the use of such physical aid does not negate the mental nature of this limitation. See October Update at Section I(C)( i ) and (iii). Additional Elements: Step 2A Prong 2 : “ classifying a quality of water using a water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). “ utilizing a sequential learning unit for classification of impurities in the water” does not integrate the judicial exception into a practical application. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). The claim is merely selecting data, manipulating or analyzing the data using math and mental process, and displaying the results. This is similar to electric power : MPEP 2106.05(h) vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A ., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016). Whether the claim invokes computers or other machinery merely as a tool to perform an existing process. Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015). In contrast, a claim that purports to improve computer capabilities or to improve an existing technology may integrate a judicial exception into a practical application or provide significantly more. McRO , Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); Enfish , LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). See MPEP §§ 2106.04(d)(1) and 2106.05(a) for a discussion of improvements to the functioning of a computer or to another technology or technical field. Claim *** recites the additional element(s) of using generic AI/ML technology, i.e. *** utilizing a sequential learning unit ***, to perform data evaluations or calculations, as identified under Prong 1 above. The claims do not recite any details regarding how the AI/ML algorithm or model functions or is trained. Instead, the claims are found to utilize the AI/ML algorithm as a tool that provides nothing more than mere instructions to implement the abstract idea on a general purpose computer. See MPEP 2106.05(f). Additionally, the use of the *** utilizing a sequential learning unit *** merely indicates a field of use or technological environment in which the judicial exception is performed. See MPEP 2106.05(h). Therefore, the use of *** utilizing a sequential learning unit *** to perform steps that are otherwise abstract does not integrate the abstract idea into a practical application. See the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence; and Example 47, ineligible claim 2. The claim as a whole does not meet any of the following criteria to integrate the judicial exception into a practical application: An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field; an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim; an additional element effects a transformation or reduction of a particular article to a different state or thing; and an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Step 2B : “ classifying a quality of water using a water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). “ utilizing a sequential learning unit for classification of impurities in the water” does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). T he claim is therefore ineligible under 35 USC 101. Claim 9 is similar to claim 1 but recites a n apparatus for detecting water quality . These additional elements fail to integrate the abstract idea into a practical application. These limitations are recited at a high level of generality and do not add significantly more to the judicial exception. These elements are generic computing devices that perform generic functions. Using generic computer elements to perform an abstract idea does not integrate an abstract idea into a practical application. See 2019 Guidance, 84 Fed. Reg. at 55. Moreover, “the mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.” Alice, 573 U.S. at 223; see also FairWarninglP , LLCv . latric SysInc ., 839 F.3d 1089, 1096 (Fed. Cir. 2016) (citation omitted) (“[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter”). On the record before us, we are not persuaded that the hardware of claim 9 integrates the abstract idea into a practical application. Nor are we persuaded that the additional elements are anything more than well-understood, routine, and conventional so as to impart subject matter eligibility to claim 9 . Regarding claim 2, “obtaining the data indicative of ultrasonic time-of-flight change behavior from a plurality of ultrasonic sensors associated with the water meter” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim 3, “ obtaining the data indicative of ultrasonic time-of-flight change behavior from at least two ultrasonic sensors associated with the water meter ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim s 4 and 10 , “ classifying with the sequential learning unit the impurities in the water as water quality parameters including at least one of: TDS (Total Dissolved Solids), ph level, chlorine residual data, turbidity information, and total organic carbon values ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim s 5 and 11 , “ communicating data indicative of the impurities in the water classified with a machine learning algorithm to a user through a radio frequency frame ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim s 6 and 12 , “ classifying with the sequential learning unit the impurities in the water as water quality parameters including at least one of: TDS (Total Dissolved Solids), ph level, chlorine residual data, turbidity information, and total organic carbon values; and communicating the water quality parameters associated with the water to a user through a radio frequency frame ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim s 7 and 13 , “ the sequential learning unit comprises a machine learning algorith m . ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim s 8 and 14 , “ wherein data indicative of the classification of the impurities in the water is based on ToF , Difference in Time-of-flight ( DiffToF ) and temperature information ” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Hence the claims 1-14 are treated as ineligible subject matter under 35 U.S.C. § 101. Claims 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non- statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claims are directed to software per se. Regarding claim 15, Applicant has claimed “[a] system comprising: at least one processor and a memory, the memory storing instructions to cause the at least one processor to perform ...” and the broadest reasonable interpretation of “ the memory storing instructions “ includes a software module comprising a transitory propagating signal for performing the claimed, and thus, these features recite software per se, which is non-statutory subject matter. Further, in the recitation of “ system comprising: at least one processor and a memory, the memory storing instructions to cause the at least one processor to perform .....,” the limitation of “ instructions to cause the at least one processor to perform ...” recited as a condition precedent, wherein the instructions being executed by the computing device is not positively recited as necessarily being performed in the claim, and for this reason, the computing device is outside the scope of the claim. As a result, these claims must be rejected under 35 U.S.C. § 101 as covering non- statutory subject matter. Regarding claim 16, “obtaining the data indicative of ultrasonic time-of-flight change behavior from a plurality of ultrasonic sensors associated with the water meter” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim 17, “obtaining the data indicative of ultrasonic time-of-flight change behavior from at least two ultrasonic sensors associated with the water meter” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim 18, “classifying with the sequential learning unit the impurities in the water as water quality parameters including at least one of: TDS (Total Dissolved Solids), ph level, chlorine residual data, turbidity information, and total organic carbon values” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim 19, “the sequential learning unit comprises a machine learning algorithm.” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Regarding claim 20, “wherein data indicative of the classification of the impurities in the water is based on ToF , Difference in Time-of-flight ( DiffToF ) and temperature information” does not integrate the judicial exception into a practical application. It does not amount to significantly more than the judicial exception in the claim. This additional element is merely using a computer as a tool to perform an abstract idea (see MPEP 2106.05(h)). Hence the claims 1 5 - 20 are treated as ineligible subject matter under 35 U.S.C. § 101. 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. Claim (s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Silverman (US 2022/0065824 A1) in view of Michael et al. (US 2018/0217102 ) . Regarding claim s 1 , 9, and 15 , Silverman disclose an apparatus and method for detecting water quality (para. [0011], [0023]: fluid, water quality) , comprising: an ultrasonic sensor (104a, 104b) , wherein a quality of water (fluid quality) is classified (para. [0027]) using a water meter (computer 110) (see Figs. 1, 2, para. [0030]) ; and a sequential learning unit that classifies the impurities in the water ( abstract: Machine learning algorithms are used to identify, measure, and classify the unique frequency response signatures associated with a wide range of fluids , para. [0030] : A feature of the invention is the use of machine learning algorithms for the identification, measurement, and classification of the unique composition of a fluid including the detection and quantification of contaminants. The results of the signature classification results can occur in real time in order to control valves and pumps typically found within a range of process-control industries ) . Silverman fail s to disclose using water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water, wherein the data indicative of the ultrasonic ToF change behavior is obtained from the ultrasonic sensor associated with the water meter . Michael et al. teach using water meter with respect to data indicative of ultrasonic time-of-flight ( ToF ) change behavior due to a mixed or combination of impurities in the water, wherein the data indicative of the ultrasonic ToF change behavior is obtained from the ultrasonic sensor associated with the water meter (para. [0048] Ultrasonic flow meters utilize an ultrasonic signal pulsed through a fluid traveling within a pipe. When the fluid is flowing the reflected ultrasonic signal is reflected with a Doppler effect (phase shift) that can be correlated to a fluid speed. The speed is multiplied by the cross sectional area of the pipe to derive a fluid flowrate. [0049] The Doppler effect can also be measured as a change in the pulsed time of flight required for the ultrasonic signal to be sent and received. The pulsed time of flight can be affected by fluid temperature (which affects the fluid density), type of fluid, speed (or flowrate) of the fluid, and fluid impurities. [0051]: T he Ultrasonic flow meter logs temperature and time of flight (TOF) to a data logging device with large memory ) . Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Michael et al. with the teaching of Silverman in order to provide a n ultrasonic flowmeter configured to detect impurities in a fluid, such as impurities in water ( Michael et al. , abstract) Regrading claim s 2 and 16 , Michael et al. in view of Silverman teach obtaining the data indicative of ultrasonic time-of-flight change behavior from a plurality of ultrasonic sensors associated with the water meter (para. [0049]: The Doppler effect can also be measured as a change in the pulsed time of flight required for the ultrasonic signal to be sent and received. The pulsed time of flight can be affected by fluid temperature (which affects the fluid density), type of fluid, speed (or flowrate) of the fluid, and fluid impurities ) . Regrading claim s 3 and 17 , Michael et al. in view of Silverman teach obtaining the data indicative of ultrasonic time-of-flight change behavior from at least two ultrasonic sensors associated with the water meter (para. [0051]: two transducers A and B) . Regrading claim s 4 -6 , 10-12, and 18, Silverman teach classifying with the sequential learning unit the impurities in the water as water quality parameters; and communicating the water quality parameters associated with the water to a user through a radio frequency frame ( para. [0018], [0027] , [0030]) . Si lverman fails to disclose water quality parameters including at least one of: TDS (Total Dissolved Solids), ph level, chlorine residual data, turbidity information, and total organic carbon values . Michael et al. teach water quality parameters including at least one of: TDS (Total Dissolved Solids), chlorine residual data ( para. [0056]). Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Michael et al. with the teaching of Silverman in order to provide a n ultrasonic flowmeter configured to detect impurities in a fluid, such as impurities in water ( Michael et al., abstract) Regrading claim s 7 , 13, and 19, Silverman teach the sequential learning unit comprises a machine learning algorithm (para. [0030]) . Regrading claim s 8 , 14, and 20, Silverman teach wherein data indicative of the classification of the impurities in the water (para. 0027]) is based on temperature information (para. [0051] -[ 0052]) . Silverman fail to disclose classification of the impurities in the water is based on ToF , Difference in Time-of-flight ( DiffToF ) . Michael et al. teach classification of the impurities in the water is based on ToF , Difference in Time-of-flight ( DiffToF ) (para. [0049]: The pulsed time of flight can be affected by fluid temperature (which affects the fluid density), type of fluid, speed (or flowrate) of the fluid, and fluid impurities ) . T herefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Michael et al. with the teaching of Silverman in order to provide a n ultrasonic flowmeter configured to detect impurities in a fluid, such as impurities in water ( Michael et al., abstract) . Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN H LE whose telephone number is (571)272-2275 . The examiner can normally be reached on Monday-Friday from 7:00am – 3:30pm Eastern Time. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A. Turner can be reached on (571) 272-6334. 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. /JOHN H LE/ Primary Examiner, Art Unit 2857