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 .
Foreign Priority
Acknowledgment is made of applicant's claim for foreign priority based on an application filed in People’s Republic of China on 8/16/2021. It is noted, however, that applicant has not filed a certified copy of the CN202110939056.3 application as required by 37 CFR 1.55.
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 1-12 are rejected under 35 U.S.C. 101. The claimed invention is directed to the abstract concept of performing mental steps without significantly more. The claim(s) recite(s) the following abstract concepts in BOLD of
Specifically, Claim 1 recites:
“A method for determining a contribution rate of pollution load in a water quality assessment section of an annular river network system based on water quantity constitute, comprising the following steps of:
i) determining water quantity components in a research region, comprising a plurality of rainfall runoffs, wastewater discharge and water diversion;
ii) constructing a river network water quantity constitute model, regarding the all water quantity components as conservative substances, and calculating water quantity ratios of the water quantity components in each water quality assessment section, wherein a construction method of the river network water quantity constitute model comprises: based on a water quality model, regarding the all water quantity components as the conservative substances, regardless of transformation and fate, and representing model results as volume ratios of all water quantity components, wherein n rivers are set, corresponding flow rates of rivers L1, L2, …, Ln-1 are q1, q2, …, qn-1 respectively, and the n-1 rivers all flow to the river Ln, which means that a water quantity of the river Ln is composed of water quantity of the rivers L1, L2, …, Ln-1, so that a flow rate of Ln is that q= q1+q2+, …, +qn-1, and ratios of the water quantity are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively; and assuming that concentrations of the conservative substances entering the river with the water flow are all 1.0, concentrations of the all conservative substances in the river Ln are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively;
and determining the water quantity ratios of the all water quantity components according to the concentrations of the conservative substances in the river;
iii) collecting pollution loads and wastewater quantity of all wastewater discharges, and calculating a weighted average concentration of all wastewater discharge pollutants; using a hydrological model and a pollution load model to calculate a pollution load, a wastewater quantity and a water yield of land use types of all rainfall runoffs, and calculate a weighted average concentration of rainfall runoff pollutants; and acquiring a weighted average concentration of water diversion pollutants;
iv) according to the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants, calculating contribution rates of the pollutants of the all water quantity components in the water quality assessment section in the research region;
v) according to the calculation in step iv), obtaining a list of contribution rates of pollution loads of all water quantity components; and
vi) according to the list of contribution rates of pollution loads obtained in step v), ranking the contribution rates of all water quantity components in the water quality assessment section, sequentially determining whether the weighted average concentrations of pollutants exceed a pollutant discharge standard, and if the weighted average concentrations exceed a standard threshold, then constructing sewage treatment devices to control pollution discharge concentrations of the water quantity components; and if the weighted average concentrations do not exceed the standard threshold, then controlling discharge amounts of the water quantity components”.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category.
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitation the fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter that, when recited as such in a claim limitation, covers performing mathematics and/or mental steps.
Next, under Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that since the claimed methods and system are not tied to a particular machine or apparatus, they do not represent an improvement to another technology or technical field. Similarly, there are no other meaningful limitations linking the use to a particular technological environment. Finally, there is nothing in the claims that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Finally, under Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because a processing unit, memory, and database are generic computer elements and not considered significantly more than the abstract idea. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
A method for determining a contribution rate of pollution load in a water quality assessment section is well understood and routine equipment for necessary data gathering recited in generality and represent insignificant field of use limitations that is not meaningful to indicate a practical application.
Claims 2-12 further limit the abstract ideas without integrating the abstract concept into a practical application or including additional limitations that can be considered significantly more than the abstract idea.
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 1-2, and 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Louisell, III et al. (US 20220343194), hereinafter ‘Louisell’ in view of Li et al. (CN 110866367), hereinafter ‘Li’ in view of Zhang et al. (CN 111199341), hereinafter ‘Zhang” and further in view of Chen et al. (CN 109101781), hereinafter ‘Chen’
Regarding Claim 1, Louisell, discloses i) determining water quantity components in a research region, comprising a plurality of rainfall runoffs, wastewater discharge and water diversion (e.g., The storm effects module can receive data from public/private databases regarding current water levels [0046]; the “Hydrology” module, which can receive data from the storm effects module regarding predicted weather/rainfall in a given area, then use hydrology i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity (i.e., determining water quantity components in a research region, comprising a plurality of rainfall runoffs) [0047]); The wastewater output (i.e., wastewater discharge) by one city or industry can influence the source water for another, such that how respective entities receive, treat, and otherwise use their water [0064]; hydrologic data, topographic data, location of key riverine system nodes, transport and storage characteristics of those nodes, distances between nodes, and the influence of significant man-made diversion/storage/flow management systems such as dams and overflow channels (i.e., water diversion) [0047]),
ii) constructing a river network water quantity constitute model, regarding the all water quantity components (e.g., use known hydrologic data, topographic data, location of key riverine system nodes (i.e., constructing a river network) , transport and storage characteristics of those nodes, distances between nodes [0047]; The spatially and temporally structured normalized data can be input into an AI (Artificial Intelligence) engine (an algorithm), which generates forecast outputs in the form of an overall water quality level for the given location, while also identifying likely contaminant constituency (i.e., water quantity constitute model) [0037]; The identification of contaminant levels can, for example, involve the use of historical data; stormwater outfalls and associated seasonal contaminant constituency: industrial sites and associated contaminant constituency, water treatment plants and associated practices, wastewater treatment plants, and associated practices, etc.; hydrology within the watershed; current and/or predicted rainfall (i.e., regarding the all water quantity components) [0060]),
iii) collecting pollution loads and wastewater quantity of all wastewater discharges (e.g., to receive current hydrologic event forecasts; in-situ water quality; and potential for wastewater treatment generated and/or pass through loadings (i.e., collecting pollution loads) [0037]; The sector module can generate contaminant loads for placement into the hydrologic flow system. Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to wastewater treatment activities (i.e., wastewater quantity of all wastewater discharges) [0048]),
and calculating a weighted average concentration of all wastewater discharge pollutants (e.g., the system may (1) execute water quality predictions using all of the models, then combine the results using averaging or by weighting the models based on a level of predicted relevance; or (2) by combining the models before execution (e.g., combining the weights of variables, particular sub-routines/analyses) (i.e., calculating a weighted average) [0042]; the module can access one or more databases which identify geographic sources for various contaminants identified by the sector module, and properties associated with the dispersion of those contaminants (such as solubility, weight, etc.) [0049]); Core to the indexing system is the ability to automatically generate a continuous mathematical function that relates a level of concentration of a given contaminant, or a combination of contaminants, with a level of significance (i.e., calculating a weighted average concentration) [0052]; to receive current hydrologic event forecasts; in-situ water quality; and potential for wastewater treatment generated and/or pass through loadings to forecast changes in water quality for a specific geo-location along surface water system paths (i.e., of all wastewater discharge pollutants) [0037]),
using a hydrological model and a pollution load model to calculate a pollution load, a wastewater quantity and a water yield of land use types of all rainfall runoffs (e.g., the “Hydrology” module, which can receive data from the storm effects module regarding predicted weather/rainfall in a given area, then use hydrology (i.e., using a hydrological model) i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity (i.e., calculate a water yield of land use types of all rainfall runoffs), peaking profile, elevated flow duration, and time of concentration [0047]; The sector module can generate contaminant loads for placement into the hydrologic flow system. Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to agriculture, stormwater management, industry, water treatment, and wastewater treatment activities (i.e., calculate a pollution load, a wastewater quantity) [0048]),
and calculate a weighted average concentration of rainfall runoff pollutants (e.g., Core to the indexing system is the ability to automatically generate a continuous mathematical function that relates a level of concentration of a given contaminant, or a combination of contaminants, with a level of significance, illustrated in FIG. 1. The level of significance can, for example, indicate how much harm may be conveyed to an individual in contact with the respective contaminant (i.e., calculate a weighted average concentration) [0052]; the system will not only identify contaminants from the standard contamination sources, but also access databases identifying contaminants which may spread from the rainfall such as agricultural contaminants fertilizer runoff, anaerobic lagoons, holding ponds, etc.) and/or vehicular pollution oil, rubber, and other road waste) (i.e., of rainfall runoff pollutants) [0049]),
and acquiring a weighted average concentration of water diversion pollutants (e.g., the system may (1) execute water quality predictions using all of the models, then combine the results using averaging or by weighting (i.e., acquiring a weighted average) the models based on a level of predicted relevance (where the system predicts relevance based on how close the sensor data, aligns with a given model); or (2) by combining the models before execution (e.g., combining the weights of variables) [0042]; Core to the indexing system is the ability to automatically generate a continuous mathematical function that relates a level of concentration of a given contaminant (i.e., a weighted average concentration), or a combination of contaminants [0052]; use known hydrologic data, topographic data, location of key riverine system nodes, transport and storage characteristics of those nodes, distances between nodes, and the influence of significant man-made diversion/storage/flow management systems (i.e., water diversion) [0047]; The sector module can generate contaminant loads for placement into the hydrologic flow system. Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to stormwater management (i.e., of water diversion pollutants) [0048]).
calculating contribution rates of the pollutants of the all water quantity components in the water quality assessment section in the research region (e.g., FIG. 6 illustrates an example water pedigree, formed by combining 602 the hydrology map 402 information with the process nodes 502. The combined pedigree can be used to calculate runoff, travel schema, and/or the aggregation of contaminants (i.e., calculating contribution rates of the pollutants of the all water quantity components in the water quality assessment section in the research region) [0067]; Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to agriculture, stormwater management, industry, water treatment, and wastewater treatment activities (i.e., calculating contribution rates of the pollutants of the all water quantity components) [0048]; The identification of contaminant levels can, for example, involve the use of historical data; known activities and locations of agricultural areas; stormwater outfalls and associated seasonal contaminant constituency: wastewater treatment plants, and associated practices, etc.; hydrology within the watershed; current and/or predicted rainfall; seasonal variance data (i.e., calculating contribution rates of the pollutants of the all water quantity components) [0060]),
v) according to the calculation in step iv), obtaining a list of contribution rates of pollution loads of all water quantity components (e.g., FIG. 16 illustrates a first example of water quality indexing based on tiered contaminants (i.e., according to the previous calculation). In this example, the list of contaminants (i.e., calculating contribution rates of the pollutants of the all water quantity components) is tiered according to impact, with contaminants having a higher impact on water quality listed as “Tier I”, and contaminants having less impact on water quality listed as tiers II-IV [0082]; Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to agriculture, stormwater management, industry, water treatment, and wastewater treatment activities (i.e., pollution loads of all water quantity components) [0048]),
vi) according to the list of contribution rates of pollution loads obtained in step v), ranking the contribution rates of all water quantity components in the water quality assessment section (e.g., FIG. 19 illustrates a third example of water quality indexing based on tiered contaminants (i.e., ranking the contribution rates of all water quantity components in the water quality assessment section), with the respective impacts of the detected chemicals illustrated. For example, a contaminant with high impact (based on both the amount detected as well as its tiered classification) (i.e., according to the list of contribution rates of pollution loads obtained) is illustrated as darker [0085]; FIG. 20 illustrates an example of ranking health factors, which can be used in identifying in which tier various contaminants should be placed (i.e., ranking the contribution rates) [0087]; FIG. 22 illustrates an example of ranking contaminants (i.e., ranking the contribution rates). In this example, the contaminants are organized by the health impact each respective contaminant may have [0089]),
sequentially determining whether the weighted average concentrations of pollutants exceed a pollutant discharge standard (e.g., Such tagging supports the operations related to identifying sequences of contaminant loads (i.e., sequentially determining whether the weighted average concentrations of pollutants) for use in the water quality forecast use case in the form of the water pedigree. Geospatial and temporal tags can be generated using data headers, e.g. headers associated with digital imagery, point-of-discharge reports (i.e., discharge standard) [0075]; FIG. 19 illustrates a third example of water quality indexing based on tiered contaminants. For example, a contaminant with high impact (i.e., pollutants exceed a pollutant discharge standard) (based on both the amount detected as well as its tiered classification) is illustrated as darker, whereas a contaminant with relatively low impact is illustrated as having less shading (i.e., sequentially determining whether the weighted average concentrations of pollutants) [0085]; the system could have a first model to identify water quality conditions when rain levels are below a first threshold amount within a two week period, a second model to identify water quality conditions above the first threshold amount (i.e., pollutants exceed a pollutant discharge standard) [0042]; The forecast mechanism considers such factors as: land use, soil data, seasonality, and surface water information quality (physical, chemical, biological, metallurgical, and radiological properties) flow volume, and flow velocities) provided by monitoring public & private, real-time & near real-time, sensor data, where data can be developed from authoritative public historical data bases (i.e., discharge monitoring reports) (i.e., discharge standard) [0037]; The identification of contaminant levels can, for example, involve the use of historical data; and/or other data descriptive of the constituency, toxicity, and volume of discharges (i.e., discharge standard) [0060]),
and if the weighted average concentrations exceed a standard threshold, then constructing sewage treatment devices to control pollution discharge concentrations of the water quantity components (e.g., based on the types of contaminants and/or the indexed water quality level (i.e., if the weighted average concentrations exceed a standard threshold), the system can support, using private and/or public data, a recommendation of pre-treatment technologies and their associated implementation processes that will generate environmental compliance given the specific contaminants and/or operating characteristics of a business, facility, and/or campus (i.e., then constructing sewage treatment devices to control pollution discharge concentrations of the water quantity components) [0062]),
and if the weighted average concentrations do not exceed the standard threshold, then controlling discharge amounts of the water quantity components (e.g., based on the types of contaminants and/or the indexed water quality level (i.e., if the weighted average concentrations do not exceed the standard threshold), the system can use the forecast surface and/or groundwater water quality conditions to suggest that discharges from certain process should be delayed for a specific time such that the impact of the discharge on the receiving waters will minimize adverse downstream impact (i.e., then controlling discharge amounts of the water quantity components) [0062]).
Louisell does not explicitly disclose regarding conservative substances, calculating water quantity ratios of the water quantity components in each water quality assessment section, based on a water quality model, regarding the all water quantity components as the conservative substances, regardless of transformation and fate, and representing model results as volume ratios of all water quantity components, wherein n rivers are set, corresponding flow rates of rivers L1, L2, …, Ln-1 are q1, q2, …, qn-1 respectively, and the n-1 rivers all flow to the river Ln, which means that a water quantity of the river Ln is composed of water quantity of the rivers L1, L2, …, Ln-1, so that a flow rate of Ln is that q= q1+q2+, …, +qn-1, and ratios of the water quantity are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively; and assuming that concentrations of the conservative substances entering the river with the water flow are all 1.0, concentrations of the all conservative substances in the river Ln are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively; and determining the water quantity ratios of the all water quantity components according to the concentrations of the conservative substances in the river, and iv) according to the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants.
Li discloses regarding conservative substances (e.g., a real-time tracking method of normal burst water pollution group under complex river network water flow condition. based on the complex and variable river network hydrological power characteristic; the conservative substance [Abstract]),
wherein a construction method of the river network water quantity constitute model comprises: based on a water quality model, regarding the all water quantity components as the conservative substances, regardless of transformation and fate (e.g., the conservative substance water quality model boundary condition and initial condition according to the following way defining and assignment, namely the original water storage of the storage node and the river is defined as the first large-class conservative substance (i.e., construction method of the river network water quantity constitute model); defining the rainfall runoff as the second large conservative substance; defining the waste water discharge as the third large type of conservative substance; in order to track the transmission path of accident discharging waste water in the river network, orderly defining each waste water discharging source as the corresponding conservative substance (i.e., based on a water quality model, regarding the all water quantity components as the conservative substances); no matter how the actual substance concentration of each control boundary is entered (i.e., regardless of transformation and fate) [Pg. 4, Para. 4]; the conservative substance concentration process corresponding to the river net section can represent the dynamic transmission process and way of accident discharge waste water in the river network. The conventional accident pollutant after entering the water is gradually mixed with the same kind of pollutant together, along with the water flow to mix, transfer and degradation, loss of the unique source characteristic of the substance. a certain section appears corresponding conservative substance concentration (i.e., regardless of transformation and fate) [Pg. 8, Para. 5]),
assuming that concentrations of the conservative substances entering the river with the water flow are all 1.0, concentrations of the all conservative substances in the river (e.g., selecting the rainfall runoff collecting river micro-section as the control boundary of the second large type of conservative substance. no matter how the actual substance concentration of each control boundary is entered, defining the corresponding conservative substance concentration of each boundary condition is 1.0 (i.e., assuming that concentrations of the conservative substances entering the river with the water flow are all 1.0, concentrations of the all conservative substances in the river) [Pg. 4, Para. 4]),
according to the concentrations of the conservative substances in the river (e.g., the conservative substance concentration process corresponding to the river net section can represent the dynamic transmission process and way of accident discharge waste water in the river network (i.e., according to the concentrations of the conservative substances in the river) [Pg. 8, Para. 5]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III with Li for regarding conservative substances, wherein a construction method of the river network water quantity constitute model comprises: based on a water quality model, regarding the all water quantity components as the conservative substances, regardless of transformation and fate, and according to the concentrations of the conservative substances in the river as this would give the advantage of dynamically tracking the accident waste water and accident pollutant transmission process and path in the river network, obtaining the accident pollutant at different sensitive receptors and corresponding conservative substance concentration process line, and estimating the reaction time of different sensitive receptor accident effect; duration and maximum pollutant concentration, (see Li, [Abstract]).
It would have been further obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III with Li for assuming that concentrations of the conservative substances entering the river with the water flow are all 1.0, concentrations of the all conservative substances in the river as this would give the advantage of defining the corresponding conservative substance concentration of each boundary condition, no matter how the actual substance concentration of each control boundary is entered, and the initial concentration of other types of conservative substance is zero, (see Li, [Pg. 4, Para. 4]).
Louisell, III and Li do not explicitly disclose calculating water quantity ratios of the water quantity components in each water quality assessment section, representing model results as volume ratios of all water quantity components, wherein n rivers are set, corresponding flow rates of rivers L1, L2, …, Ln-1 are q1, q2, …, qn-1 respectively, and the n-1 rivers all flow to the river Ln, which means that a water quantity of the river Ln is composed of water quantity of the rivers L1, L2, …, Ln-1, so that a flow rate of Ln is that q= q1+q2+, …, +qn-1, and ratios of the water quantity are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively, concentrations of the all conservative substances in the river Ln are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively; and determining the water quantity ratios of the all water quantity components, and iv) according to the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants.
Zhang discloses calculating water quantity ratios of the water quantity components in each water quality assessment section, and representing model results as volume ratios of all water quantity components (e.g., monitoring water volume and water quality at the estuary; analysis of pollution sources in the watershed: calculating the average water volume and water quality (i.e., representing model results as volume ratios of all water quantity components) in each water period; counting the emissions of various pollution sources (i.e., calculating water quantity of the water quantity components in each water quality assessment section) [Abstract]; FIG. 2 different periods each into the river sewage water amount ratio (%) (i.e., calculating water quantity ratios) [Pg. 6, Para. 5]),
determining the water quantity ratios of the all water quantity components (e.g., calculating the average water volume and water quality in each water period; counting the emissions of various pollution sources (i.e., determining the water quantity ratios of the all water quantity components) [Abstract]; FIG. 2 different periods each into the river sewage water amount ratio (%) (i.e., determining water quantity ratios) [Pg. 6, Para. 5]),
and iv) according to the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants (e.g., monitoring water volume and water quality at the estuary; analysis of pollution sources in the watershed: calculating the average water volume and water quality in each water period; counting the emissions of various pollution sources (i.e., the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants) [Abstract]; change proportional to the concentration (i.e., concentration of the pollutants) of a single pollutant flux, the total flux of the given period pollutant is the sum of all known source pollutant flux [Pg. 2, Para. 6]; FIG. 2 different periods each into the river sewage water amount ratio (%) (i.e., according to the water quantity ratios) [Pg. 6, Para. 5]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III and Li with Zhang for calculating water quantity ratios of the water quantity components in each water quality assessment section, and representing model results as volume ratios of all water quantity components, determining the water quantity ratios of the all water quantity components, and iv) according to the water quantity ratios of the all water quantity components and the weighted average concentration of the pollutants as this would give the advantage of determining the distribution and types draining outlets, simultaneously monitoring water volume and water quality, analysis of pollution sources, calculating the average water volume and water quality, counting the emissions of various pollution sources, and analyzing the contribution of various sewage draining outlets to the pollution of the watershed, derive the pollution contribution of emission source of each type or even each emission source. The analytical results are objective and close to the actual emission situation, thus providing targets for precise source control and improving the efficiency of watershed pollution control, (see Zhang, [Abstract]).
Louisell, III and Li with Zhang do not explicitly disclose wherein n rivers are set, corresponding flow rates of rivers L1, L2, …, Ln-1 are q1, q2, …, qn-1 respectively, and the n-1 rivers all flow to the river Ln, which means that a water quantity of the river Ln is composed of water quantity of the rivers L1, L2, …, Ln-1, so that a flow rate of Ln is that q= q1+q2+, …, +qn-1, ratios of the water quantity are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively, and concentrations of the all conservative substances in the river Ln are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively.
Chen discloses wherein n rivers are set, corresponding flow rates of rivers (e.g., river i (i=1, 2, ..., n) (i.e., n rivers are set), wherein river i in the j-th point source pollution contribution to n target river, Qout, 0 represents the source water flow rate (i.e., corresponding flow rates of rivers), Qout, i-1 is the i-1 river flow [Pg. 3, Para. 8-10]),
and the n-1 rivers all flow to the river, which means that a water quantity of the river is composed of water quantity of the rivers, so that a flow rate of river is that q= q1+q2+, …, +qn-1 (e.g., Qout, 0 represents the source water flow rate, Qout, i-1 is the i-1 river flow outlet (i.e., the n-1 rivers all flow to the river); Qout, i is the i of the river flow (i.e., a flow rate of river is q= q1+q2+, …, +qn-1), n is the target sections of the flow rate (i.e., which means that a water quantity of the river is composed of water quantity of the rivers) [Pg. 5, Para. 6]),
ratios of the water quantity (e.g., Qpump, i is the amount of the river, the unit is m3s-1, Vi is the volume of river (i.e., ratios of the water quantity) [Pg. 3, Para. 5]),
and concentrations of the all conservative substances in the river (e.g., collecting the flow river point source surface source pollution source position, type, discharge time, flux, pollutant emission concentration data, transferring and converting pollutant analogue constructing a three-dimensional numerical value model of the contaminant mass conservation (i.e., concentrations of the all conservative substances) [Pg. 2-3, Para. 15-1]; Ci is the contaminant concentration of the river, the unit is mg L-1 Ci-1 is the concentration of the pollutant of the river i-1, the unit is mg L-1, Ci + 1 of river pollutant concentration of i + 1 (i.e., concentrations of the all conservative substances in the river), the unit is mg L-1 [Pg. 3, Para. 5]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III, Li, and Zhang with Chen for n rivers are set, corresponding flow rates of rivers L1, L2, …, Ln-1 are q1, q2, …, qn-1 respectively, and the n-1 rivers all flow to the river Ln, which means that a water quantity of the river Ln is composed of water quantity of the rivers L1, L2, …, Ln-1, so that a flow rate of Ln is that q= q1+q2+, …, +qn-1, ratios of the water quantity are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively, and concentrations of the all conservative substances in the river Ln are L1: q1/q, L2: q2/q, …, Ln-1: q n-1/q respectively as this would give the advantage to provide a pollution contribution ratio calculating method in a complex network, generalized on the basis of complex river, determine river flow, collect flow basic data and pollution source data, and the pollutant measured concentration of the target section, (see Chen, [Pg. 2, Para. 5]).
Regarding Claim 2, Louisell, III, Li, Zhang, and Chen disclose the limitations as discussed above in Claim 1.
Louisell, III further discloses wherein in the step ii), meteorological conditions of precipitation and land use conditions in the research region are input into the hydrological model to calculate runoff rates of all land use types (e.g., the A.I. engine can receive weather or other meteorological forecast data. The weather forecasts can be combined with hydrology data to make water runoff and stream flow predictions for the given area (i.e., meteorological conditions of precipitation) [0045]; the “Storm Effects” module, which can make weather, and specifically precipitation (rain and snow), forecasts for a given Area Of interest (AOI), The storm effects module can receive data from public/private databases regarding current water levels, current storm activity, weather patterns, seasonal data, etc. [0046]; the “Hydrology” module, which can receive data from the storm effects module regarding predicted weather/rainfall in a given area, then use hydrology i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity, peaking profile, elevated flow duration, and time of concentration (i.e., meteorological conditions of precipitation and land use conditions in the research region are input into the hydrological model to calculate runoff rates of all land use types) [0047]),
the water yields of the land uses are taken as the water quantity components of the rainfall runoff (i.e., can receive data from the storm effects module regarding predicted weather/rainfall in a given area, then use hydrology i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity (i.e., the water yields of the land uses are taken as the water quantity components of the rainfall runoff) [0047]);
collected wastewater discharge quantity are taken as the water quantity components of the wastewater discharge (i.e., use hydrology i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity [0047]; involve the use of historical data; wastewater treatment plants, and associated practices, etc. (i.e., collected wastewater discharge quantity are taken); hydrology within the watershed; and/or other data descriptive of the constituency, toxicity, and volume of discharges (i.e., as the water quantity components of the wastewater discharge) [0060]);
water diversion quantity outside the research region are taken as the water quantity components of the water diversion (e.g., use hydrology i.e. storm intensity, land cover, land use, and topography data to predict water runoff in terms of expected quantity (i.e., water diversion quantity), use known hydrologic data, topographic data, location of key riverine system nodes (i.e., outside the research region), transport and storage characteristics of those nodes, distances between nodes, and the influence of significant man-made diversion/storage/flow management systems such as dams and overflow channels to predict the effects (i.e., taken as the water quantity components of the water diversion) of the anticipated rainfall on a downstream area (i.e., outside the research region) [0047]),
and the water quantity constitute model (e.g., The spatially and temporally structured normalized data can be input into an AI (Artificial Intelligence) engine (an algorithm), which generates forecast outputs in the form of an overall water quality level for the given location, while also identifying likely contaminant constituency (i.e., the water quantity constitute model) [0037]).
Louisell, III does not explicitly discloses conditions of evaporation, the water quantity ratio of each water quantity component in the water quality assessment section is calculated by, which is ϕij, and ϕij is a water quantity ratio of an ith water quantity component in a jth water quality assessment section.
Li discloses conditions of evaporation (e.g., collecting and finishing the research area boundary and monitoring site hydrological water quality time series data; collecting and finishing the research area precipitation, evaporation and point (i.e., conditions of evaporation), face source and so on data [Pg. 2-3, Para. 8-1]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III with Li for meteorological conditions of evaporation as this would give the advantage of providing a real-time tracking method of conventional burst water pollution group under the condition of complex river network water flow, as the beneficial supplement of the existing sudden water pollution pre-warning, (see Li, [Pg. 2, Para. 3]).
Louisell, III and Li do not explicitly disclose the water quantity ratio of each water quantity component in the water quality assessment section is calculated by, which is ϕij, and ϕij is a water quantity ratio of an ith water quantity component in a jth water quality assessment section.
Zhang discloses the water quantity ratio of each water quantity component in the water quality assessment section (e.g., calculating the average water volume and water quality in each water period; counting the emissions of various pollution sources (i.e., the water quantity ratio of each water quantity component in each water quality assessment section) [Abstract]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III, and Li, with Zhang for the water quantity ratio of each water quantity component in the water quality assessment section as this would give the advantage of providing targets for precise source control and improving the efficiency of watershed pollution control, (see Zhang, [Abstract]).
Louisell, III, Li, and Zhang do not explicitly disclose ϕij, and ϕij is a water quantity ratio of an ith water quantity component in a jth water quality assessment section.
Chen discloses a water quantity ratio of an ith water quantity component in a jth water quality assessment section (e.g., j-th pollution river i (i=1, 2, ..., n) of flux contribution to pollution ratio formula (i.e., a water quantity ratio) specific sections (4) to (5): wherein river i in the j-th point source pollution contribution to n target river; direct the pollution load of the j-th surface source (i.e., an ith water quantity component) involved is the i-th river pollution contribution of the n target river (i.e., in a jth water quality assessment section) [Pg. 3, Para. 9-10]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III, Li, and Zhang with Chen for ϕij, and ϕij is a water quantity ratio of an ith water quantity component in a jth water quality assessment section as this would give the advantage to provide a pollution contribution ratio calculating method in a complex network, collect flow basic data and pollution source data, and the pollutant measured concentration of the target section, (see Chen, [Pg. 2, Para. 5]).
Regarding Claim 5, Louisell, III, Li, Zhang, and Chen disclose the limitations as discussed above in Claim 1.
Louisell further discloses wherein in step iii), the weighted average concentration of the water diversion pollutants is determined by water quality monitoring data (e.g., the system may (1) execute water quality predictions using all of the models, then combine the results using averaging or by weighting (i.e., the weighted average) the models based on a level of predicted relevance; or (2) by combining the models before execution (e.g., combining the weights of variables, particular sub-routines/analyses) [0042]; the module can access one or more databases which identify geographic sources for various contaminants identified by the sector module (i.e., pollutants is determined by water quality monitoring data), and properties associated with the dispersion of those contaminants (such as solubility, weight, etc.) [0049]; Core to the indexing system is the ability to automatically generate a continuous mathematical function that relates a level of concentration of a given contaminant, or a combination of contaminants (i.e., the weighted average concentration) [0052]; use known hydrologic data, topographic data, location of key riverine system nodes, transport and storage characteristics of those nodes, distances between nodes, and the influence of significant man-made diversion/storage/flow management systems (i.e., water diversion) [0047]; The sector module can generate contaminant loads for placement into the hydrologic flow system. Loads can be generated on a sector-by-sector basis for contaminant generation activities attributable to stormwater management (i.e., the water diversion pollutants is determined by water quality monitoring data) [0048]).
Regarding Claim 6, Louisell, III, Li, Zhang and Chen disclose the limitations as discussed above in Claim 2 and the limitations as discussed above in Claim 5.
Claims 3 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Louisell, III, Li, Zhang, and Chen in view of Xie et al. (CN 106570334), hereinafter ‘Xie’ and further in view of Yang et al. (CN 110909484), hereinafter ‘Yang’.
Regarding Claim 3, Louisell, Li, Zhang and Chen disclose the limitations as discussed above in Claim 1.
Louisell, III, Li, Zhang, and Chen do not explicitly disclose wherein in the step i), the rainfall runoff is defined as a non-point source and the wastewater discharge is defined as a point source, the non-point source is classified into domestic pollution of rural residents, planting pollution, livestock and poultry pollution and urban surface runoff pollution, and the point source is classified into direct discharge industrial pollution, wastewater treatment plant pollution and other untreated domestic pollution.
Xie discloses the rainfall runoff is defined as a non-point source and the wastewater discharge is defined as a point source (e.g., increases the industrial waste water, city sewage point source (i.e., the wastewater discharge is defined as a point source) pollution control. city rainfall runoff pollution (city non-point source pollution (i.e., the rainfall runoff is defined as a non-point source) of the main type) the city water environment pollution contribution [Pg. 2, Para. 3]),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Louisell, III, Li, Zhang, and Chen with Xie for the rainfall runoff is defined as a non-point source and the wastewater discharge is defined as a point source as this would give the advantage for researching city rainfall runoff pollution load (pollution generation amount) for developing city rainfall runoff pollution control, making pollution control measures, so as to improve the city water environment, (see Xie, [Pg. 2, Para. 3]).
Louisell, III, Li, Zhang, Chen, and Xie do not explicitly disclose the non-point source is classified into domestic pollution of rural residents, planting pollution, livestock and poultry pollution and urban surface runoff pollution, and the point source is classified into direct discharge industrial pollution, wastewater treatment plant pollution and other untreated domestic pollution.
Yang discloses the non-point source is classified into domestic pollution of rural residents, planting pollution, livestock and poultry pollution and urban surface runoff pollution (e.g., non-point source (urban runoff, farmland runoff, rural domestic dispersing breeding, etc.) (i.e., the non-point source is classified into domestic pollution of rural residents, planting pollution, and urban surface runoff pollution) more pollution [Pg. 5, Para. 7]; the rural non-point source pollution prevention and scaled poultry breeding as the priority item key related work (i.e., the non-point source is classified into poultry pollution) [Pg. 11, Para. 5]; Ai is the ith number of pollution (animal, paddy drought, rural population) (i.e., the non-point source is classified into livestock pollution) [Pg. 7, Para. 2]),
and the point source is classified into direct discharge industrial pollution, wastewater treatment plant pollution and other untreated domestic pollution (e.g., pollution type comprises point source (town sewage treatment plant tail water, industrial large-scale enterprise wastewater, sewage farm, etc.) (i.e., the point source is classified into direct discharge industrial pollution, wastewater treatment plant pollution and other untreated domestic pollution) [Pg. 5, Para. 7]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention t