DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are pending in this Application.
Priority
This application claims priority as a continuation from U.S. Non-Provisional patent application Ser. No. 18/404,152, filed on May 6, 2019, the entirety of which is expressly incorporated by reference herein for all purposes.
Specification Objection
The disclosure is objected to because of the following informalities:
Paragraph [0001] recites “… U.S. Non-Provisional patent application Ser. No. 18/404,152,…”.
The parent application has a different serial number. This seems an inadvertent typographical error.
This should be -- U.S. Non-Provisional patent application Ser. No. 16/404,152—
Also, paragraph [0065[ recites “The aggregate data can further include information from external sources specific to the polygon. For example, external surfaces made reference to indicate the terrain type, the current weather, historical weather, user entered information such as crop type, land usage type, landscaping feature type,…”
It seems that the term "external surfaces" was meant to recite -external sources—
Furthermore, [0065] recites "Deviant moisture content may further be indicated by a change in moisture content over time (between two or more for damages taken at different successive times).
This seems to be --Deviant moisture content may further be indicated by a change in moisture content over time (between two or more images taken at different successive times).
Appropriate correction is required.
The specification is also objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required:
Claim 5 recites “wherein the type and location of property features includes soil type and evapotranspiration values for each property polygon”. This subject matter is not described in the specification.
Claim 13, recites “wherein the type and location of property features includes soil type and evapotranspiration values for each property polygon”. This subject matter is not described in the specification.
Claim 19, recites “wherein generation of the leak notification is dependent on soil type and evapotranspiration values for each property polygon”. This subject matter is not described in the specification.
The Applicant can overcome this objection by pointing support for the limitations above or by adding the limitations to the specification since the limitations above have support in the original claims.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 5, 13, and 19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 5 recites “wherein generation of the leak notification is dependent on whether a type and location of property features correlates to the identified leak location in the specific property, wherein the type and location of property features includes soil type and evapotranspiration values for each property polygon”. There is insufficient written description for these limitations in the original disclosure.
The original disclosure does not have any suggestion or recitations for “soil type and evapotranspiration values”, or how the leak location detection depends on these variables.
Furthermore, par. [0010] recites “The property polygons identify and delineate the type and locations of property features for the specific property”. Thus, based on the definitions of claim 5, and par. [0010] can be interpreted as “The property polygons identify and delineate evapotranspiration values”. This does not suggest a leak detection location based on soil type or evapotranspiration values.
As to claim 13, this claim is the system claim corresponding to the method claim 5 and is rejected for the same reasons mutatis mutandis
Claim 19 recites “wherein generation of the leak notification is dependent on soil type and evapotranspiration values for each property polygon”. There is insufficient written description for these limitations in the original disclosure.
The original disclosure does not teach, suggest, or recite “soil type” and evapotranspiration values” being used or associated to the determination of a leak/leak location.
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 4-5 and 12-13 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 4 recites “wherein generation of the leak notification is dependent on whether a type and location of property features correlates to the identified leak location in the specific property”. These limitations are unclear and confusing and make the claim indefinite.
For instance, Claim 5 recites “wherein the type and location of property features includes soil type and evapotranspiration values for each property polygon”. The original disclosure does not have any suggestion or recitations for “soil type and evapotranspiration values”, or how the leak detection depends on these variables.
Furthermore, par. [0010] recites “The property polygons identify and delineate the type and locations of property features for the specific property”. Thus, based on the definitions of claim 5, par. [0010] can be interpreted as “The property polygons identify and delineate evapotranspiration values”. This is unclear.
Paragraph [0063] recites “Portion data may include the images and further include additional information related to the images such as a terrain type displayed in the image”.
For purposes of Examination, claim 4-5 will be interpreted as:
claim 4 “wherein generation of the leak notification is dependent on a type and location of property features of the identified leak location in the specific property,
Claim 5 “wherein the type and location of property features includes soil type and evapotranspiration values for each property polygon”.
As to claim 5, this claim depends on claim 4 and it is rejected for the same reasons mutatis mutandis as its parent claim since it inherits the same error.
As to claim 12-13, these claims are the system claim corresponding to the method claims 4-5 and are rejected for the same reasons mutatis mutandis.
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 1-4, 6-7, 9-12, 14-15, 17-18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Guy (US 20180224550) in view of Armon et al (US 20120185184).
As per claim 1, Guy teaches a computer implemented method implemented on a computer system including non-transient memory storing instructions for identifying leak locations based on environmental imagery (see [0025] “method and a system for
remote detection of underground polar liquid (e.g., drinking water, sewage water, etc.), for example, drinking water leakage from an urban water system”), comprising:
tracking a utility supply usage environment in environmental imagery captured over a period of time (see page 9 claim 1 “receiving, from a radiofrequency radiation sensor, a main scan of an area, the main scan including reflections at a radiofrequency range from the area, the sensor being attached to an object located at least 50 meters above the area”; also, see [0027], [0030] “scans”; also, see [0043] “The first, second and optionally the third scans may be received as grayscale images of microwave intensity levels converted into grayscale levels (e.g. each pixel in the map has different gray scale level)”; also, see [0038] and [0062] and [0081]);
identifying changes in the environmental imagery indicative of a leak location (see [0029] “drinking water content or amount may be calculated from the drinking water related reflections and converted into quantities of water capacity (e.g., cubic meters/hour, gallons/hour, etc.,). This information may be displayed on a geographical map (e.g., a street map of a city) showing, for example, the amount and location of each suspected leakage in a city”; also, see [0056] and [0081] “In some embodiments, the received set of scans may be analyzed to detect changes in the area through time. Such a process is known in the art as interferometry”; also, see [0059] and [0063]; Thus, changes of water contents in specific areas are indicative of a leak location);
applying a property profile to the utility supply usage environment to generate leak location property data (see Fig. 8 location and polygons (squares) where the suspected leak detected are presented; also, see [0029] “This information
may be displayed on a geographical map (e.g., a street map of a city) showing, for example, the amount and location of each suspected leakage in a city”; also, see [0060] “location information”);
generating a leak notification based on the leak location in the environmental imagery, the property profile data and (see Fig. 8; also, see [0029] “This information
may be displayed on a geographical map (e.g., a street map of a city) showing, for example, the amount and location of each suspected leakage in a city”; also, see [0060] “in FIG. 8. Since the received scans may include information (e.g., pixels) from a relatively large area, the geographical map presenting the data to a user ( e.g., city official) may include only a portion of the scanned area. The user may shift the geographical map on the screen ( e.g., using a mouse or a keyboard) covering all areas of interest (e.g., the city quarters) in the scanned area. Some of the detected leakages, illustrated as small gray dots in FIG. 7 were given a polar liquid capacity value and location in the corresponding geographical map (e.g., using coordinates). For example, as illustrated in FIG. 8 each of the marks located in a particular place on the map presents different amounts of polar liquid leakage (e.g. in gallons/hour). It should be appreciated by those skilled in the art that the displayed information may be displayed on top of a Geographic Information System (GIS)”).
While Guy teaches that flow devices such as valve and pipes are identified based on the leak detection (see [0060]) and the leak information may be displayed over a GIS (GIS is a map that includes the pipeline infrastructure and meters along the pipeline ), Guy does not explicitly teach identifying one or more flow measurement devices based on the leak location and leak location property data, and generating a leak notification based on meter data from the identified one or more flow measurement devices.
However, Armon, teaches a method and system comprising identifying one or more flow measurement devices based on the leak location and leak location property data ([0008] “when alerting on an anomaly the detection system or work process will yield a general location such as a DMA, or part of the water utility network”, also, see [0011] “…Types of anomalies include leaks,…receiving anomaly data… The anomaly event data is associated with meter data produced by one or more of the meters, typically at least the meters that are affected by the anomaly or from which meter data was received by which the anomaly was detected. There may also be a predetermined list of meters that are relevant to that zone, e.g., in a DMA, the relevant meters may be defined as all the flow and pressure meters at the perimeter of that DMA and within it. The anomaly event data may also include previously computed data on the magnitude of the anomaly, the statistical likelihood of the occurrence of such an anomaly, the region or zone in the water utility network in which the anomaly was detected, and other information”, Thus, meters associated with a possible leak location (DMA) are identified; also, see [0029] “The system stores, manipulates, and reports to the user, regions in the form of predefined network parts (such as a DMA, or pressure zone), polygon on a geographical map, a range of addresses (in one embodiment from GIS data), or a set of marked or named network assets, such as lengths of pipe”; also, see [0037] and [0057] the identified sensors closest to a possible leak are presented), and generating a leak notification based on meter data from the identified one or more flow measurement devices (see [0016] “For example, where the anomaly event data represents an indication of a leak, the affected values being compared may be flow or pressure values in the meters. The one or more affected values of the meter data may be compared in one of several ways, such as by computing an absolute increase in the one or more affected values in each of the meters relative to a predicted or expected value and comparing the absolute increases across the meters…”; also, see [0017]; also, see Fig. 13 and [0058] a notification of an anomaly/leak is presented with a corroborated and better location than the general location (DMA)).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy’s invention to include identifying one or more flow measurement devices based on the leak location and leak location property data, and generating a leak notification based on meter data from the identified one or more flow measurement devices.as taught by Armon in order to determine more precisely the location of a leak/anomaly based on the meter data (see [0008]-[0009]) and to enhance and provide a more robust leak detection system as taught by Guy (including meter data such as flow measurements to corroborate the existence of a leak in an area, improves the system of guy that predicts leaks based on aerial images).
As per claim 2, Guy-Armon teaches the method of claim 1, Guy further teaches wherein generating leak location property data includes identifying a specific property and property polygons for the specific property (see [0016] and see Fig. 8 leak locations includes specific property names and polygons). Armon also teaches these limitations (see [0029] “regions in the form of predefined network parts (such as a DMA, or pressure zone), polygon on a geographical map, a range of addresses (in one embodiment from GIS data).
As per claim 3, Guy-Armon teaches the method of claim 2, Guy further teaches wherein the property polygons identify and delineate the type and locations of property features for the specific property (see Fig. 8 the polygons identify the locations of the properties based on the street addresses around them and the polygon the type and locations of properties based on the squares/polygon).
As per Claim 4, Guy-Armon teaches the method of claim 3, Guy further teaches wherein generation of the leak notification is dependent on whether a type and location of property features correlates to the identified leak location in the specific property (this has been interpreted as wherein generation of the leak notification depends on a type and location of property features of the identified leak location in the specific property) (Guy teaches that the leak detection depends on a type and location of property features, see [0033] “geographical data related to the scanned area (e.g., a type of soil, amount of humidity in the solid, a road map, etc.), and roughness values of various types of polar liquid (e.g., drinking water, sewage water, etc.) sources or any other required data according to embodiments of the invention”; also, see [0040] “The penetration depth of RF waves into the ground may vary with the type of the soil, the amount of moisture in the soil, the structure of the land cover and the like”, thus, leak detection depends on soil type; also, see [0028] “In some embodiments, EM roughness values (e.g., surface water roughness values) from sewage pipes, seas, lakes and swimming pools may be filtered or removed from the filtered noise scan thus leaving in the scan only reflection received from polar liquid (e.g., drinking water, sewage water, etc.) leakages”, location of property features such as lakes are eliminated from the map used for the generation of leak notification/detection).
As per claims 6-7, Guy-Armon teaches the method of claim 1, Armon further teaches wherein generation of the leak notification includes determining whether the identified changes can be correlated to the meter data from the identified one or more flow measurement devices, wherein determining whether the identified changes can be correlated to the meter data from the identified one or more flow measurement devices includes determining whether the leak location correlates to a conduit between an inflow measurement device and outflow measurement devices and a leak has been detected based on aggregation of the meter data from the measurement devices (this has been interpreted as suggested in the original disclosure [0011] correlating the leak location with a conduit and flow measurements devices to further corroborate a leak; Armon teaches see [0011] “…Types of anomalies include leaks,…receiving anomaly data… The anomaly event data is associated with meter data produced by one or more of the meters, typically at least the meters that are affected by the anomaly or from which meter data was received by which the anomaly was detected. There may also be a predetermined list of meters that are relevant to that zone, e.g., in a DMA, the relevant meters may be defined as all the flow and pressure meters at the perimeter of that DMA and within it. The anomaly event data may also include previously computed data on the magnitude of the anomaly, the statistical likelihood of the occurrence of such an anomaly, the region or zone in the water utility network in which the anomaly was detected, and other information”, Thus, meters associated with a possible leak location (DMA) are identified and correlated to verify a leak; also, see [0029] “The system stores, manipulates, and reports to the user, regions in the form of predefined network parts (such as a DMA, or pressure zone), polygon on a geographical map, a range of addresses (in one embodiment from GIS data), or a set of marked or named network assets, such as lengths of pipe”; also, see [0037] and [0057] the identified sensors closest to a possible leak are presented; see [0016] “For example, where the anomaly event data represents an indication of a leak, the affected values being compared may be flow or pressure values in the meters. The one or more affected values of the meter data may be compared in one of several ways, such as by computing an absolute increase in the one or more affected values in each of the meters relative to a predicted or expected value and comparing the absolute increases across the meters…”; also, see [0017]; also, see Fig. 13 and [0058] a notification of an anomaly/leak is presented with a corroborated and better location than the general location (DMA)).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy’s invention to include wherein generation of the leak notification includes determining whether the identified changes can be correlated to the meter data from the identified one or more flow measurement devices, wherein determining whether the identified changes can be correlated to the meter data from the identified one or more flow measurement devices includes determining whether the leak location correlates to a conduit between an inflow measurement device and outflow measurement devices and a leak has been detected based on aggregation of the meter data from the measurement devices as taught by Armon in order to determine more precisely the location of a leak/anomaly based on the meter data (see [0008]-[0009]) and to enhance and provide a more robust leak detection system as taught by Guy (including meter data such as flow measurements to corroborate the existence of a leak in an area, improves the system of guy that predicts leaks based on aerial images).
As to claim 9, this claim is the system claim corresponding to the method claim 1 and is rejected for the same reasons mutatis mutandis.
As to claim 10, this claim is the system claim corresponding to the method claim 2 and is rejected for the same reasons mutatis mutandis.
As to claim 11, this claim is the system claim corresponding to the method claim 3 and is rejected for the same reasons mutatis mutandis.
As to claim 12, this claim is the system claim corresponding to the method claim 4 and is rejected for the same reasons mutatis mutandis.
As to claims 14-15, these claims are the system claims corresponding to the method claims 6-7 and are rejected for the same reasons mutatis mutandis.
As per claim 17, Guy teaches a computer implemented method implemented on a computer system including non-transient memory storing instructions for identifying leak locations based on environmental imagery (see [0025]), comprising:
tracking a utility supply usage environment in environmental imagery captured over a period of time (see [0027], [0030], [0043], and [0081]);
identifying changes in the environmental imagery indicative of a leak location (see [0029], [0056], [009], and [0081]);
applying a property profile to the utility supply usage environment to generate leak location property data including identification of polygon data records for the leak location (see [0016] and see Fig. 8 leak locations includes specific property names and polygons).
generating a leak notification based on the leak location in the environmental imagery and the polygon data record, the property profile data (see Fig. 8; also, see [0029]); and
While Guy teaches that flow devices such as valve and pipes are identified based on the leak detection (see [0060]) and the leak information may be displayed over a GIS (GIS is a map that includes the pipeline infrastructure and meters along the pipeline ), Guy does not explicitly teach identifying one or more flow measurement devices based on the leak location and leak location property data in the polygon data record, and generating a leak notification based on meter data from the identified one or more flow measurement devices, and updating criteria used to generate the leak notification based on actual leak data.
However, Armon, teaches a method and system comprising identifying one or more flow measurement devices based on the leak location and leak location property data ([0008] “when alerting on an anomaly the detection system or work process will yield a general location such as a DMA, or part of the water utility network”, also, see [0011] “…Types of anomalies include leaks,…receiving anomaly data… The anomaly event data is associated with meter data produced by one or more of the meters, typically at least the meters that are affected by the anomaly or from which meter data was received by which the anomaly was detected. There may also be a predetermined list of meters that are relevant to that zone, e.g., in a DMA, the relevant meters may be defined as all the flow and pressure meters at the perimeter of that DMA and within it. The anomaly event data may also include previously computed data on the magnitude of the anomaly, the statistical likelihood of the occurrence of such an anomaly, the region or zone in the water utility network in which the anomaly was detected, and other information”, Thus, meters associated with a possible leak location (DMA) are identified; also, see [0029] “The system stores, manipulates, and reports to the user, regions in the form of predefined network parts (such as a DMA, or pressure zone), polygon on a geographical map, a range of addresses (in one embodiment from GIS data), or a set of marked or named network assets, such as lengths of pipe”; also, see [0037] and [0057] the identified sensors closest to a possible leak are presented), and generating a leak notification based on meter data from the identified one or more flow measurement devices (see [0016] “For example, where the anomaly event data represents an indication of a leak, the affected values being compared may be flow or pressure values in the meters. The one or more affected values of the meter data may be compared in one of several ways, such as by computing an absolute increase in the one or more affected values in each of the meters relative to a predicted or expected value and comparing the absolute increases across the meters…”; also, see [0017]; also, see Fig. 13 and [0058] a notification of an anomaly/leak is presented with a corroborated and better location than the general location (DMA)), and updating criteria used to generate the leak notification based on actual leak data (see Fig. 12 includes likely locations of leaks, see [0057] and Fig. 13 is updated with leakages locations based on detected leakages based on the meter data; see [0038] and [0058] “The screen 1301 displays colored indications of a pipe 1303a affected by a detected anomaly and located between assets 1302a-b”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy’s invention to include identifying one or more flow measurement devices based on the leak location and leak location property data, and generating a leak notification based on meter data from the identified one or more flow measurement devices, and updating criteria used to generate the leak notification based on actual leak data as taught by Armon in order to determine more precisely the location of a leak/anomaly based on the meter data (see [0008]-[0009]) and to enhance and provide a more robust leak detection system as taught by Guy (including meter data such as flow measurements to corroborate the existence of a leak in an area, improves the system of guy that predicts leaks based on aerial images).
Armon also teaches identification of polygon data records for the leak location (see [0029] “regions in the form of predefined network parts (such as a DMA, or pressure zone), polygon on a geographical map, a range of addresses (in one embodiment from GIS data).
As per claim 18, Guy-Armon teaches the method of claim 17, Guy further teaches wherein generating leak location property data includes identifying a specific property and property polygons for the specific property (see Guy [0016] and see Fig. 8 leak locations includes specific property names and polygons), each property polygon having a unique polygon data record (see [0060] “Some of the detected leakages, illustrated as small gray dots in FIG. 7 were given a polar liquid capacity value and location in the corresponding geographical map (e.g., using coordinates). For example, as illustrated in FIG. 8 each of the marks located in a particular place on the map presents different amounts of polar liquid leakage (e.g. in gallons/hour)”, thus, each polygon has a data record/location; also, see [0067] “FIG. 12 is a map of a portion of an area presenting 4 land cover types at different location on the map according to one embodiment. The land coves: at location A may be classified as an industrial area, at location B may be classified as urban area, at location C may be classified as a park and at locations D may be classified as paved areas. Other classifications may be used”, thus, the polygons have data record including classifications; also, see [0068] “In some embodiments, the geographical data may include a location, length, width and height of objects (e.g., buildings) in the scanned area”, this, also suggest data record.).
As to claim 20, this claim is the method corresponding to the method claim 6 and is rejected for the same reasons mutatis mutandis.
Claims 5, 13, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Guy (US 20180224550) in view of Armon et al (US 20120185184) as applied to claim 1 above, and further in view of Kageyama et al (JP 2010044048 as supported by the machine translation provided).
As per claim 5, Guy-Armon teaches the method of claim 4, Guy further teaches wherein the type and location of property features includes soil type and (see [0033] and [0040] thus, Guy teaches that the type pf property features includes soil type). Guy-Armon does not explicitly teach the type and location of property features includes evapotranspiration values.
However, KAGEYAMA teaches a system and method comprising detecting seepage water (water leak) based on evapotranspiration values detected on satellite images (see [0011], [0016], and [0023] evapotranspiration values for each region based on satellite data is calculated; also, see [0024] seepage is calculated based on evapotranspiration data).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy-Armon’s combination as taught above to include the type and location of property features including evapotranspiration values for detecting seepage of water as taught by Kageyama in order to detect water leak since seepage of water are indicative of leaks.
As to claim 13, this claim is the system claim corresponding to the method claim 5 and is rejected for the same reasons mutatis mutandis.
As per claim 19, Guy-Armon teaches the method of claim 18, Guy further teaches wherein generation of the leak notification is dependent on soil type and see [0033] and [0040] thus, Guy teaches that the type pf property features includes soil type).
Guy-Armon does not explicitly teach wherein generation of the leak notification is dependent on evapotranspiration values.
However, KAGEYAMA teaches a system and method comprising detecting seepage water (water leak) based on evapotranspiration (ET) values detected on satellite images (see [0011], [0016], and [0023] evapotranspiration values for each region based on satellite data is calculated; also, see [0024] seepage is calculated based on evapotranspiration data).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy-Armon’s combination as taught above to include evapotranspiration values for detecting seepage of water/leaks as taught by Kageyama in order to detect and generate water leak based on ET values since seepage of water are indicative of leaks.
Claims 8 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Guy (US 20180224550) in view of Armon et al (US 20120185184) as applied to claim 1 above, and further in view of Picardi et al (US 20190025150).
As per claim 8, Guy-Armon teaches the method of claim 1, but it does not explicitly teach wherein generation of the leak notification includes controlling a supply flow within a utility supply network.
However, Picardi teaches a method and system comprising wherein generation of a leak notification includes controlling a supply flow within a utility supply network (see [0012] “(i) alerts the resident of a detected water leak and (ii) outputs a selectable icon that, when selected, triggers transmission of an instruction to the connected water meter instructing the connected water meter to close a water shut off valve”; also, see [0038] “However, the systems and methods could also trigger a notification of a leak, a shut-off of water at the property, or both, if multiple leaks were occurring at the same property”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Guy-Armon’s combination as taught above to include wherein generation of the leak notification includes controlling a supply flow within a utility supply network as taught by Picardi in order to mitigate damages and waste of water and stop a leak (see [[007] and [0041]).
As to claim 16, this claim is the system claim corresponding to the method claim 8 and is rejected for the same reasons mutatis mutandis.
Conclusion
Note: the specification objections, 112(a), 112(b), 103(a) rejections were previously presented in the parent Application.
The prior art made of record and not relied upon, as cited in PTO form 892, is considered pertinent to applicant's disclosure.
The references Ravid teaches a system for receiving measurement data of water flow or usage and detect a leak (see Fig. 3; 0059);
Barker teaches a system for detecting leak based on measurements of flow and pressure (see 0007 and Fig. 9);
Rainone teaches a system for detecting leaks (0042) and controlling devices to alleviate the problem (see 0042-0043);
Guan teaches a system for taking images of areas and determining ponds of water (0002-0006);
Calvanese teaches a system for detecting leaks based on images (see the Abstract and 0046);
Scolnicov teaches a system, comprising GIS data related to power distribution networks, and identifying leaks (see 0027);
teaches a system for detecting leaks in certain areas, using GIS data to locate the pertinent leak location in a more refined location detection (see 0010, 0015, 0033, 0046);
Peleg teaches a system for detecting leaks in a water network systems based on meter data (see Fig. 3) and using GIS data to present to a user the exact location of the leak event (see Fig. 3);
Palayur teaches a system to detect water leaks based on collected data (see 0044);
Abernathy teaches a system for detecting leaks using image data and applying GIS data maps to identify the location of the leak (see Fig. 8A);
Scharpf clearly teaches GIS data and polygon associated with data record including identification codes (see Fig. 2, 6 ), and identifying the properties based on events or measurements detected at the property location (see [0037].
Thus, these reference alone or in combination teach or suggest the detection of water leaks based on images and based on water flow rate determined from predetermined flow measurement devices associated to leaks detected in particular location.
Examiner respectfully requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). This will assist Examiner in prosecuting the application.
When responding to this Office Action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. Applicant must also show how the amendments avoid or differentiate from such references or objections. See 37 CFR 1.111 (c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLVIN LOPEZ ALVAREZ whose telephone number is (571) 270-7686 and fax (571) 270-8686. The examiner can normally be reached Monday thru Friday from 9:00 A.M. to 6:00 P.M.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Robert Fennema, can be reached at (571) 272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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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) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/O. L./
Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117
