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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/19/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-18 and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 1, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information, by statistical analysis or machine learning.” Claim 1, lines 13-15 disclose “wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour of the meters.” Claim 1, lines 8-10 disclose that the parameters are established through either statistical analysis or machine learning. Claim 1 then disregards the statistical analysis and only utilizes the machine learning for establishing the scheduling. Said another way, if the statistical analysis is utilized for the establishing of parameters, then the scope of the claim does not include utilizing a learned communication performance behaviour of the meters. Therefore the scope of the claim is unclear. For the purposes of the present examination, “based on the statistical analysis or learned communication performance behaviour of the meters” is construed. However, further clarification is required.
Claims 2-9 and 20 are rejected by virtue of their dependence from claim 1.
Claim 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 2, lines 7-8 disclose “where applicable.” The term “where applicable” is an arbitrary term limiting the scope of the claim to an applicable situation, which is not explicitly stated. Therefore the scope of the claim is unclear, as it is not clear when a situation would be applicable. For the purposes of the present examination, “with reference to a timestamping” is always applicable. However, further clarification is required.
Claim 3 is rejected by virtue of its dependence from claim 2.
Claim 7 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 1, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information, by statistical analysis OR machine learning.” Claim 7 discloses “wherein establishing said parameters representing a behaviour of each of the communicating meters comprises a learning.” Claim 1 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 1 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinction. However, further clarification is required.
Claims 8-9 are rejected by virtue of their dependence from claim 7.
Claim 8 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 1, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information, by statistical analysis OR machine learning.” Claim 8 discloses “wherein the learning by means of a module.” Claim 1 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 1 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinct. However, further clarification is required.
Claim 9 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 1, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information, by statistical analysis OR machine learning.” Claim 9 discloses “wherein the learning by means.” Claim 1 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 1 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinction. However, further clarification is required.
Claim 10 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 10, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information by statistical analysis or machine learning.” Claim 10, lines 13-15 discloses “wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour of the meters.” Claim 10, lines 8-10 disclose that the parameters are established through either statistical analysis or machine learning. Claim 10 then disregards the statistical analysis and only utilizes the machine learning for establishing the scheduling. Said another way, if the statistical analysis is utilized for the establishing of parameters, then the scope of the claim does not include utilizing a learned communication performance behaviour of the meters. Therefore the scope of the claim is unclear. For the purposes of the present examination, “based on the statistical analysis or learned communication performance behaviour of the meters” is construed. However, further clarification is required.
Claims 11-18 are rejected by virtue of their dependence from claim 10.
Claim 11 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 11, line 7 disclose “where applicable.” The term “where applicable” is an arbitrary term limiting the scope of the claim to an applicable situation, which is not explicitly stated. Therefore the scope of the claim is unclear, as it is not clear when a situation would be applicable. For the purposes of the present examination, “with reference to a timestamping” is always applicable. However, further clarification is required.
Claim 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 10, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information by statistical analysis OR machine learning.” Claim 16 discloses “establish said parameters representing a behaviour of each of the communicating meters by learning.” Claim 10 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 10 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinction. However, further clarification is required.
Claims 17-18 are rejected by virtue of their dependence from claim 16.
Claim 17 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 10, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information by statistical analysis OR machine learning.” Claim 17 discloses “configured to implement said learning.” Claim 10 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 10 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinction. However, further clarification is required.
Claim 18 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite. Claim 10, lines 8-10 disclose “establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information by statistical analysis OR machine learning.” Claim 18 discloses “configured to implement said learning.” Claim 10 is rejected by a cited statistical analysis. It is therefore unclear how a statistical analysis may learn, as the choices of claim 10 discloses either a statistical analysis or machine learning. For the purposes of the present examination, the limitations appear to not have patentable distinction. However, further clarification is required.
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 1-18 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The claims are evaluated for patent subject matter eligibility under 35 U.S.C. 101 using the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) as follows:
Step 1:
Claims 1-9 and 20 are directed to a method and therefore falls within the four statutory categories of subject matter.
Step 2A:
This step asks if the claim is directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea. Step 2A is a two-prong inquiry: in prong 1 it is determined whether a claim recites a judicial exception, and if so, then in prong 2 it is determined if the recited judicial exception is integrated into a practical application of that exception.
Analyzing claim 1 under prong 1 of step 2A, the language:
A method for collecting,
and the method comprising:
i) obtaining first information representing a communication performance behavior
said first information comprising at least a response time and a response rate with reference to a timestamping and a cell identifier,
ii) establishing parameters representing a communication performance behaviour from said first information, by statistical analysis or machine learning based on observed communication data,
iii) establishing a schedule of collection of data from said parameters representing the communication performance behaviour
wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour and
has a scope that encompasses mathematical concepts and/or mental steps, e.g., mathematical relationships and/or mathematical calculations and/or concepts that may be performed in the human mind; e.g., human observation/performable with pen and paper/mere data gathering. Claim 1 discloses A method for collecting and the method comprising; construed as a preamble setting forth intended use; i) obtaining first information representing a communication performance behavior said first information comprising at least a response time and a response rate for each meter with reference to a timestamping and a cell identifier; construed by the examiner as a mental step; e.g., mere data gathering; ii) establishing parameters representing a communication performance behaviour from said first information, by statistical analysis or machine learning based on observed communication data; construed by the examiner as a mental step and/or a mathematical concept; e.g., performable with pen and paper and/or a mathematical calculation; iii) establishing a schedule of collection of data from said parameters representing the communication performance behaviour wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour and; construed by the examiner as a mental step; e.g., mere data gathering and/or performable with pen and paper. The broadest reasonable interpretation of the abovementioned steps in light of the specification has a scope that encompasses a mathematical relationship between variables or numbers and/or steps that may be performed in the human mind. It is therefore concluded under prong 1 of step 2A that claim 1 recites a judicial exception in the form of an abstract idea, i.e., mathematical concepts and/or mental steps. See MPEP 2106.04(a)(2)(A-C) and MPEP 2106.05(f).
In prong 2 of step 2A it is determined whether the recited judicial exception is integrated into a practical application of that exception by: (1) identifying whether there are any additional elements recited in the claim beyond judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application.
Analyzing claim 1 under prong 2 of step 2A, in addition to the abstract ideas described above, claim 1 further recites:
the method being implemented in a data collection system
Analyzing these additional elements of claim 1 under prong 2 of step 2A, these additional elements appear to merely recite the use of a generic processor/computer as a tool to implement the abstract idea and/or to perform functions in its ordinary capacity, e.g., receive, store, or transmit data. However, 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 component 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 MPEP 2106.05(f).
iv) transmitting data collection messages in accordance with said scheduling established.
Analyzing this additional element of claim 1 under prong 2 of step 2A, this additional element appears to merely collect and interpolate mathematical data, interpreted by the examiner as insignificant extra-solution activity. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps. An example of post-solution activity is an element that is not integrated into the claim as a whole, which is recited in a claim to analyze and manipulate information. See MPEP 2016.05(g). Also, employing well-known computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not integrate the exception into a practical application or add significantly more. See MPEP 2106.07(a).II.
via a communication network of a cellular type, data available in communicating meters,
connected to said communication network,
of said communicating meters
for each meter
of each of the communicating meters
from all or some of said communicating meters
of each of said communicating meters,
of the meters
to said all or some of said communicating meters
Analyzing this additional element of claim 1 under prong 2 of step 2A, this additional element appears to generally link the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible “simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.” Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; e.g., see MPEP 2106.05(h).
Step 2B:
In step 2B it is determined whether the claim recites additional elements that amount to significantly more than the judicial exception. The additional elements discussed above in connection with prong 2 of step 2A merely represents implementation of the abstract idea using a generic processor/computer and use of a generic processor/computer. However, use of a computer or other machine 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 MPEP 2106.05(f).
The further additional elements discussed above in connection with prong 2 of step 2A also merely represents insignificant extra-solution activity. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps. An example of post solution activity is an element that is not integrated into the claim as a whole, which is recited in a claim to analyze and manipulate information. See MPEP 2016.05(g).
The still further additional elements discussed above in connection with prong 2 of step 2A also merely represents generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible “simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.” Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; e.g., see MPEP 2106.05(h).
It is therefore concluded under step 2B that claim 1 does not recite additional elements that amount to significantly more than the judicial exception.
Dependent claims 2-9 and 20 merely recite further details of the abstract idea of claim 1 and therefore do not represent any additional elements that would integrate the abstract idea into a practical application or represent significantly more than the abstract idea itself.
Step 1:
Claims 10-18 are directed to a system and therefore falls within the four statutory categories of subject matter.
Step 2A:
This step asks if the claim is directed to a law of nature, a natural phenomenon (product of nature) or an abstract idea. Step 2A is a two-prong inquiry: in prong 1 it is determined whether a claim recites a judicial exception, and if so, then in prong 2 it is determined if the recited judicial exception is integrated into a practical application of that exception.
Analyzing claim 10 under prong 1 of step 2A, the language:
A system for collecting, the collection system comprising
i) obtaining first information representing a communication performance behaviour said first information comprising at least a response time and a response rate with reference to a timestamping and a cell identifier,
ii) establishing parameters representing a communication performance behaviour from said first information by statistical analysis or machine learning based on observed communication data,
iii) establishing a scheduling of collection of data from said parameters representing a communication performance behaviour wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour and
has a scope that encompasses mathematical concepts and/or mental steps, e.g., mathematical relationships and/or mathematical calculations, and/or concepts that may be performed in the human mind; e.g., human observation/performable with pen and paper/mere data gathering. Claim 10 discloses A system for collecting, the collection system comprising; construed as a preamble setting forth intended use; i) obtaining first information representing a communication performance behaviour said first information comprising at least a response time and a response rate with reference to a timestamping and a cell identifier; construed by the examiner as a mental step; e.g., mere data gathering; ii) establishing parameters representing a communication performance behaviour from said first information by statistical analysis or machine learning based on observed communication data; construed by the examiner as a mental step and/or a mathematical concept; e.g., performable with pen and paper and/or a mathematical calculation; iii) establishing a scheduling of collection of data from said parameters representing a communication performance behaviour wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour and; construed by the examiner as a mental step; e.g., performable with pen and paper and/or observation. The broadest reasonable interpretation of the abovementioned steps in light of the specification has a scope that encompasses a mathematical relationship between variables or numbers and/or steps that may be performed in the human mind. It is therefore concluded under prong 1 of step 2A that claim 10 recites a judicial exception in the form of an abstract idea, i.e., mathematical concepts and/or mental steps. See MPEP 2106.04(a)(2)(A-C) and MPEP 2106.05(f).
In prong 2 of step 2A it is determined whether the recited judicial exception is integrated into a practical application of that exception by: (1) identifying whether there are any additional elements recited in the claim beyond judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application.
Analyzing claim 10 under prong 2 of step 2A, in addition to the abstract ideas described above, claim 10 further recites:
electronic circuitry configured for
Analyzing these additional elements of claim 10 under prong 2 of step 2A, these additional elements appear to merely recite the use of a generic processor/computer as a tool to implement the abstract idea and/or to perform functions in its ordinary capacity, e.g., receive, store, or transmit data. However, 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 component 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 MPEP 2106.05(f).
iv) transmitting data collection messages in accordance with said scheduling established.
Analyzing this additional element of claim 10 under prong 2 of step 2A, this additional element appears to merely collect and interpolate mathematical data, interpreted by the examiner as insignificant extra-solution activity. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps. An example of post-solution activity is an element that is not integrated into the claim as a whole, which is recited in a claim to analyze and manipulate information. See MPEP 2016.05(g). Also, employing well-known computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not integrate the exception into a practical application or add significantly more. See MPEP 2106.07(a).II.
via a communication network of a cellular type, data available in communicating meters,
of said communicating meters,
for each meter
of each of the communicating meters
from all or some of said communicating meters
of each of the communicating meters
of the meters,
to said all or some of said communicating meters
Analyzing this additional element of claim 10 under prong 2 of step 2A, this additional element appears to generally link the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible “simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.” Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; e.g., see MPEP 2106.05(h).
Step 2B:
In step 2B it is determined whether the claim recites additional elements that amount to significantly more than the judicial exception. The additional elements discussed above in connection with prong 2 of step 2A merely represents implementation of the abstract idea using a generic processor/computer and use of a generic processor/computer. However, use of a computer or other machine 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 MPEP 2106.05(f).
The further additional elements discussed above in connection with prong 2 of step 2A also merely represents insignificant extra-solution activity. The term “extra-solution activity” can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process, which is recited as part of a claimed process of analyzing and manipulating the gathered information by a series of steps. An example of post solution activity is an element that is not integrated into the claim as a whole, which is recited in a claim to analyze and manipulate information. See MPEP 2016.05(g).
The still further additional elements discussed above in connection with prong 2 of step 2A also merely represents generally linking the use of a judicial exception to a particular technological environment or field of use. As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible “simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use.” Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; e.g., see MPEP 2106.05(h).
It is therefore concluded under step 2B that claim 10 does not recite additional elements that amount to significantly more than the judicial exception.
Dependent claims 11-18 merely recite further details of the abstract idea of claim 10 and therefore do not represent any additional elements that would integrate the abstract idea into a practical application or represent significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 10-13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over T. Khalifa, K. Naik and A. Nayak, "A Survey of Communication Protocols for Automatic Meter Reading Applications," in IEEE Communications Surveys & Tutorials, vol. 13, no. 2, pp. 168-182, Second Quarter 2011, doi: 10.1109/SURV.2011.041110.00058, hereinafter Khalifa, in view of Ma et al. (US 2023/0328792 A1), hereinafter Ma.
Regarding claim 1, Khalifa discloses A method for collecting,
via a communication network of a cellular type, (Khalifa, e.g., see pg. 174, section D disclosing various 3G wireless technologies have been introduced to the community, some of which had actual implementations. Long Term Evolution (LTE), High Speed Packet Access (HSPA) and IEEE 802.16 (known as Worldwide Interoperability for Microwave Access or WiMAX) comply with International Mobile Telecommunications (IMT-2000). Currently, WiMAX and LTE are atop the list, and with regards to AMR both of them are good candidates. Similar to WiMAX, LTE has a great potential in being widely deployed in the near future as it can flexibly operate on different frequency spectrum (1.25 MHz to 20 MHz). It offers high data rates with low delay and large cells: data rate of 100 Mbps and 50 Mbps at 20 MHz spectrum for downlink and uplink respectively, 5 ms latency to send a packet from a terminal to radio access network edge, cell size of 5 km typically, and up to 100 km but with relaxed performance requirements; wherein WiMAX and/or LTE is construed as via a communication network of a cellular type)
data available in communicating meters, (Khalifa, e.g., see fig. 1 illustrating a smart meter H/W [Hardware] Architecture; see also pg. 168, col. 2, History of Meters disclosing smart meters enjoy high hardware/software capabilities that enable them to run TCP/IP suite and have the ability to run applications on top of TCP or UDP. Smart meters are equipped with processing capability ranging from SoC microcontrollers to 32-bit processors (Fig. 1). The operating system supporting an extensive library of routines and applications, has a task schedular that rotates between a number of tasks such as communication, measurement and database management; see also pg. 168, col. 2, AMR Benefits – pg. 169, col. 1 disclosing Power quality measurement: the electric utility engineers need more detailed readings than Kwhr [KW/h] so that they can efficiently plan the network expansion and deliver a higher quality of supply. Power quality involves the measurement of voltage sags, swells, under and over voltages, harmonics distortion, voltage and current imbalances, and record duration of each event. Bundling with water and gas: The ultimate objective behind a fully functional AMR is to serve all kinds of meters, electricity, water and gas, under one communication technology and one protocol standard).
the method being implemented in a data collection system connected to said communication network, and (Khalifa, e.g., see rejection as applied above; see also fig. 5 illustrating a WiMAX typical architecture explicitly illustrating fixed stations within buildings which is connected to a communication network).
the method comprising:
i) obtaining first information representing a communication performance behaviour of said communicating meters, said first information comprising at least a response time and a response rate for each meter with reference to a timestamping and a packet order, (Khalifa, e.g., see rejection as applied above; see also pg. 173, col. 2, section B disclosing Reliability: the AMR network must guarantee the arrival of all meter readings as well as all utility server control packets. The success rate or the loss rate performance metric; construed as a response rate, shall give us a fair assessment of the given network. Scalability: a designed network shall be assessed according to its ability to providing support to a large number of meters covering a large geographical area; construed as a “for each meter.” Real time communication: data reported from a given meter must arrive within a given amount of time. Certain traffic types (e.g., fault detection) mandate a short time delay. A performance metric of end-to-end delay is required to provide a good evaluation of response time of different traffic types. Order: Packets representing different readings should be stamped with the time of measurement; construed as timestamping, so that packet ordering at the receiving station can be guaranteed; see also pg. 176, col. 2, disclosing Object Identification System OBIS: OBIS provides standard identification codes for all the data items, which are used for configuration or obtaining information about the behavior of the meter).
ii) establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information, by statistical analysis or machine learning based on observed communication data, (Khalifa, e.g., see rejection as applied above; see also fig. 10 illustrating and OBS code structure of A-F; see also pg. 176, col. 2 disclosing OBIS codes are organized into a hierarchical structure using six value groups of size one byte each A to F (Fig. 10). the value group A defines the energy type to which the metering is related. Group B defines the channel number, assuming different connections, possibly from different sources. Group C defines the abstract or physical data items related to the information source concerned, for example, current, voltage, or temperature. Group D identifies the processing methods and country specific codes. Group E is used for identifying rates or can be used for further classification. Last, group F is used for identifying historical values or can be used for further classification; examiner notes Codes A-F are construed as parameters representing a communication performance behaviour of each of the communicating meters, which is derived from the data cited above; see also pg. 172, col. 2, section A – pg. 173, col. 1 disclosing to achieve scalability and elongated battery life in large-scale sensor networks, instead of having homogenous sensors rotating the role of clusterhead among themselves, heterogeneity is introduced. That is, nodes that have sophisticated hardware and higher battery energy take on the role of a clusterhead to perform complex computations and long range communication. Data aggregation allows nodes to combine multiple readings into one report containing the result of a function such as average, median, Min or Max. Different algorithms are available to achieve that. For example, Tiny Aggregation (TAG) allow the sink to send queries toa certain set of nodes and let the nodes along the path perform the requested data aggregation type; examiner notes that TAG is described as, and is necessarily such, a statistical analysis).
iii) establishing a scheduling of collection of data from all or some of said communicating meters from said parameters representing the communication performance behaviour of each of said communicating meters, (Khalifa, e.g., see rejection as applied above disclosing the derived parameters; see also pg. 168, col. 2, History of Meters disclosing the operating system, supporting an extensive library of routines and applications, has a task scheduler that rotates between a number of tasks such as communication, measurement and database management; see also pg. 174, col. 1, section C disclosing all the previous work focuses on gathering power consumption information, in which AMR data is pushed from meters into the network at certain fixed times. As utility providers are interested in a large variety of data with much higher frequency, three modes of communication are required to be supported: fixed scheduling, event-driven and demand-driven. Each mode is more suitable for a certain kind of data and as such the three modes must co-exist. Fixed Scheduling: In this mode, a meter reports data at fixed intervals. This is a straight forward mechanism with the advantage of guaranteeing a certain rate for every meter under the knowledge of the available bandwidth. Event-driven: data are generated and transmitted as a result of events at meters. Examples of this mode include packets generated when consumption reaches a certain threshold value, power quality when it starts to degrade, and includes alarm data. Demand-driven: Upon a request from the data collection center, data packets are generated and transmitted back. A utility company uses polling to identify faults, or gets a consumption report at a certain time for a subset of meters; see also pg. 174, col. 2, section D disclosing typically, an LTE system will have two types of network elements: (i) The evolved NodeB (eNodeB), which is in charge of a set of cells, and it controls Radio Resource Management (RMM), Handover, and scheduling of users. (ii) Access Gateway (AGW), which provides access to the IP core network).
wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour of the meters, and (Khalifa, e.g., see rejection applied above disclosing TAG (tiny aggregation), in which the communication performance behaviour of the meters is established; see also fig. 7 and pg. 175, cols. 1-2 disclosing for the uplink, the base station also schedules the subscriber stations access to the channel through UL-MAP messages. These messages specify the amount of time assigned to a subscriber within the uplink sub-frame. The initial field is used for subscribers to transmit radio link control messages requesting admission and authentication, and the request connection field, during which subscribers may contend to send their bandwidth requests. Each burst (a.k.a. slot) can be assigned to a different subscriber, i.e., a meter. Meters skip the bursts that contain no relevant traffic, thus reducing the processing load. A good feature as well is that a downlink burst can be shared among multiple meters, for example, for broadcasting a certain information. the downlink/uplink number of slots ratio can be configured according to the traffic type, typically 70/30, 60/40, 50/50, or adaptively (Fig. 7). Numerically, we assume a WiMAX cell configured with TDD duplexing, a frame size of 5 ms, symbol size of 50 s, and 2 symbols per time slot. Thus, a single frame consists of 50 time slots. Taking out the time assigned for control signaling, the number of data slots would be 40 slots. Assuming 50/50 downlink/uplink ratio leaves 20 time slots for uplink. In a TCP/IP setting (Section IV-B), a meter may send packets of size of 100 bytes typically. A complete session to retrieve information from a meter consists of three stages: 1) establishing the connection, 2) data transfer, and 3) connection release. Thus, depending on the type of information collected, a session may involve a number of message exchanges between the data collection system and the meter. Assuming an average of 100 bytes packet size and 5 upload packets per session, the following estimation holds. a rate of 20 slots per 5 ms corresponds to 2.4 million slots in 10 minutes. With each meter reporting its measurement once within this time window, this channel may support up to 48 thousand to 240 thousand metering devices ideally. In conclusion, technologies such as WiMAX and LTE offer a truly scalable solution to the AMR system, supporting a large number of meter and frequent measurement reporting; examiner notes that a scheduling optimization is being described).
iv) transmitting data collection messages to said all or some of said communicating meters in accordance with said scheduling established. (Khalifa, e.g., see rejection as applied above, specifically to the established scheduling; see also fig. 12 -14 illustrating transmission of data collection messages to meters; see also pg. 177, col. 2 - 178, col. 2 disclosing [SIP] can be perfectly employed in any application that involves session initiation and event subscription and notification(e.g., file sharing). In the same manner, the AMR system involves the creation, modification and termination of communication sessions. Thus, SIP has the potential of making communication between the meters and the data collection center devices highly flexible and better controlled. That can be seen in the following points: SIP determines the media and media parameters (e.g. addresses, port numbers, and media specific parameters.) More session details such as sampling rate and codec can be carried using Session Description Protocol (SDP) encapsulated in SIP messages. SIP determines the availability of the other party to be engaged with a communication session. For example, the meters may need to determine the availability and the proper data collection device to report to. For addressing any of the AMR devices (metering devices, data collection devices, or proxy), SIP makes use of Uniform Resource Identifier. SIP makes event-driven and polling reporting mechanisms possible. Data collection devices can register for event notification (e.g. a consumption value has reached some threshold). By setting the field “expires” to zero immediate response (polling mechanism) takes place. A possible messaging scenario can be seen in Fig. 14 showing the basic functions of SIP. The end points (data collection device and meter) negotiate the session parameters through INVITE and ACK messages. The proxy helps forward the requests from both sides. The COSEM application session takes place next and continues until a termination message from either of the parties is submitted. Any of the end points can start up the SIP session, giving to the AMRJ high flexibility. The data constitutes small packets transmitted from hundreds of thousands of small devices (meters) very frequently and control data sent down to the meters).
Khalifa is not relied upon as explicitly disclosing a cell identifier.
However, Ma further discloses a cell identifier. (Ma, e.g., see para. [0058] disclosing a UE (115) [user equipment] may include or may be referred to as a mobile device, a wireless device, a remote device, a handheld device, or a subscriber device, or some other suitable terminology, where the “device’ may also be referred to as a unit, a station, a terminal, or a client, among other examples. A UE (115) may also include… a meter (e.g., parking meter, electric meter, gas meter, water meter); see also para. [0062] disclosing the communication links (125) shown in the wireless communication system (100) may include uplink transmission from a UE (115) to a base station (105), or downlink transmissions from a base station (105) to a UE (115); see also para. [0070] disclosing each base station (105) may provide communication coverage via one or more cells, for example, a macro cell, a small cell, a hot spot, or other types of cells, or any combination thereof. The term “cell” may refer to a logical communication entity used for communication with a base station (105) (e.g., over a carrier) and may be associated with an identifier for distinguishing neighboring cells (e.g., a physical cell identifier (PCID)s, a virtual cell identifier (VCID), or others)).
Accordingly, it would be prima facie obvious to one of ordinary skill in the art, at the time the invention was effectively filed, to have modified Khalifa with Ma’s cell identifier for at least the reasons that cell identification may either be for a macro cell or a small cell, wherein knowledge of the cell identifier comprises identification of restricted and/or unrestricted access for transmitting the data, as taught by Ma; e.g., see para. [0071].
Regarding claim 2, Khalifa in view of Ma discloses The data collection method according to claim 1, wherein said first information comprises at least:
- an identifier of a cell of said communication network with reference to a communicating meter identifier, see rejection as applies to claim 1, specifically Ma, e.g., paras. [0058], [0062], and [0070].
- a state of obtaining a response from a communicating meter to a message that is sent to it with reference to a timestamping, (Khalifa, e.g., see rejection as applied to claim 1, pg. 173, col. 2 disclosing an ordering of packets; see also figs. 12 illustrating a data collection device subscribing to the meter device, the meter device acknowledging and notifying, the data collection device acknowledging the ACK and NOTIFY, and the Meter device notifying the data collection device, with the data collection device acknowledging; see also fig. 14 illustrating the use of a Utility Data Collection communicating with a meter through a proxy server, wherein the same “state of obtaining” is explicitly illustrated; see also pg. 178, col. 1 disclosing SIP makes event-driven and polling reporting mechanisms possible. Data collection devices can register for event notification (e.g., a consumption value has reached some threshold) through the use of SUBSCRIBE and NOTIFY (fig. 12). By setting the field “expires” to zero immediate response (polling mechanism) takes place).
- a response time of a communicating meter to a message that is sent to it, where applicable, with reference to a timestamping. (Khalifa, e.g., see rejection as applied to claim 1; see also pg. 178., col. 2 disclosing session are short (granularity of seconds), with a long waiting period (granularity of minutes) between two sessions. Tolerance to delay is different according to the traffic type, ranging from real time delivery to a delay of until next session is due. Constraining jitter delay between successive packets is not necessary. Order of data packets can be ignored as long as there is a recording mechanism at the receiver. Data aggregation is not feasible. The collection center must identify uniquely the meter ID and the time at which the consumption measurement is taken).
Regarding claim 3, Khalifa in view of Ma is not relied upon as explicitly disclosing: The data collection method according to claim 2, wherein establishing a data-collection scheduling from said parameters is implemented with reference, for each of the communicating meters, to an identifier of a cell from which a communicating meter is accessible.
However, Ma further discloses: wherein establishing a data-collection scheduling from said parameters is implemented with reference, for each of the communicating meters, to an identifier of a cell from which a communicating meter is accessible. (Ma, e.g., see para. [0070] as disclosed in claim 1; see also para. [0068] disclosing a subframe, a slot, a mini-slot, or a symbol may be the smallest scheduling unit (e.g., in the time domain) of the wireless communication system (100) and may be referred to as transmission time interval (TTI); see also para. [0075] disclosing some UEs (115), such as MTC [machine type communications ] or IoT devices, may be low cost or low complexity devices and may provide for automated communication between machines (e.g., via Machine-to-Machine (M2M) communication). Examples of applications for MTC devices include smart metering, inventory monitoring, water level monitoring, equipment monitoring, healthcare monitoring, wildlife monitoring, weather and geological event monitoring, fleet management and tracking, remote security sensing, physical access control, and transaction-based business charging; see also para. [0072] disclosing a carrier may support multiple cells, and different cells may be configured according to different protocol types (e.g., MTC, narrowband IoT) that may provide access for different types of devices).
Accordingly, it would be prima facie obvious to one of ordinary skill in the art, at the time the invention was effectively filed, to have modified Khalifa in view of Ma’s method with Ma’s establishing a data-collection scheduling from said parameters is implemented with reference, for each of the communicating meters, to an identifier of a cell from which a communicating meter is accessible for at least the reasons that it would be beneficial to know what communication protocol to utilize for the individual cells.
Regarding claim 4, Khalifa in view of Ma discloses The data collection method according to claim 1, wherein establishing said parameters representing a behaviour of each of the communicating meters comprises a Statistical analysis. see rejection as applied to claim 1 disclosing tiny aggregation.
Regarding claim 10, Claim 10 recites A system for collecting, via a communication network of a cellular type, data available in communicating meters, the collection system comprising electronic circuitry configured for: i) obtaining first information representing a communication performance behaviour of said communicating meters, said first information comprising at least a response time and a response rate for each meter with reference to a timestamping and a cell identifier, ii) establishing parameters representing a communication performance behaviour of each of the communicating meters from said first information by statistical analysis or machine learning based on observed communication data, iii) establishing a scheduling of collection of data from all or some of said communicating meters from said parameters representing a communication performance behaviour of each of the communicating meters, wherein said scheduling is established to optimize data collection based on the learned communication performance behaviour of the meters, and iv) transmitting data collection messages to said all or some of said communicating meters in accordance with said scheduling established., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma for reasons analogous to those set forth in connection with claim 10.
Regarding claim 11, Claim 11 recites The data collection system according to claim 10, furthermore comprising circuitry configured to process said first information comprising: - an identifier of a cell of said communication network with reference to a communicating meter identifier, - a state of obtaining a response from all or some of said communicating meters to a message that is sent to it with reference to a timestamping, - a response time of a meter to a message that is sent to it, where applicable, with reference to a timestamping., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma for reasons analogous to those set forth in connection with claim 2.
Regarding claim 12, Claim 12 recites The data collection system according to claim 10, comprising electronic circuitry configured to establish a data collection scheduling from said parameters established with reference, for each of the communicating meters, to a cell identifier from which a communicating meter is accessible., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma for reasons analogous to those set forth in connection with claim 3.
Regarding claim 13, Claim 13 recites The data collection system according to claim 10, furthermore comprising electronic circuitry configured to establish said parameters representing a behaviour of each of all or some of said communicating meters by making a statistical analysis., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma for reasons analogous to those set forth in connection with claim 4.
Regarding claim 20, Kallus in view of Ma discloses A non-transitory information storage medium comprising a computer program comprising a computer program code instructions that, when executed by a processor, performs the method according to claim 1. (Khalifa, e.g., see fig. 1 illustrating a ROM, SRAM, Flash, and RTC, as well as an ARM CPU Cortex M3/M0; see also pg. 168, col. 2 disclosing smart meters enjoy high hardware/software capabilities that enable them to run TCP/IP suite and have the ability to run applications on top of TCP or UDP. Smart meters are equipped with processing capabilities ranging from SoC microcontrollers to 32-bit processors (Fig. 1). The operating system, supporting an extensive library of routines and applications, has a task scheduler that rotates between a number of tasks such as communication, measurement and database management).
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Khalifa in view of Ma, in further view of Leclerc et al. (FR 3073652 A1), hereinafter Leclerc.
Regarding claim 5, Khalifa in view of Ma discloses The data collection method according to claim 4, wherein the statistical analysis is implemented with reference to a maximum function. (Khalifa, e.g., see pg. 173, col. 1 disclosing data aggregation allows nodes to combine multiple readings into one report containing the result of a function such as average, median, Min or Max).
Khalifa in view of Ma is not relied upon as explicitly disclosing a maximum collection time.
However, Leclerc further discloses a maximum collection time. (Leclerc, e.g., see rejection as applied above; see also pg. 8, para. [0002] disclosing the method makes it possible to recover raw water consumption data (104), preferably from a remotely read business database, and transform them into usable information, of daily consumption by user. The raw consumption data may in particular include time-stamped consumption indexes (i.e. cumulative consumption). The data can be available over a variable time step, for example six hours or 1 hour, each user being able to have his own program range (the index programs not necessarily being synchronized). The raw consumption data can also include a maximum dated daily flow representing the maximum volume consumed, over a time step of 15 minutes for example).
Accordingly, it would be prima facie obvious to one of ordinary skill in the art, at the time the invention was effectively filed, to have modified Khalifa in view of Ma’s method with Leclerc’s maximum collection time for at least the reasons that confidence intervals can be determined on historical data at different time steps, as taught by Leclerc; e.g., see pg. 8, para. [0004].
Regarding claim 14, Claim 14 recites The data collection system according to claim 13, furthermore comprising electronic circuitry configured to make the statistical analysis with reference to a maximum collection time., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma, in further view of Leclerc for reasons analogous to those set forth in connection with claim 5.
Claims 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Khalifa in view of Ma, in further view of Kallus et al. (US 2019/0098377 A1), hereinafter Kallus.
Regarding claim 6, Khalifa in view of Ma discloses The data collection method according to claim 4, wherein the statistical analysis is implemented with reference to a reduced use of said communication network. (Khalifa, e.g., see rejection above and to claim 1; see also pg. 173, col. 1 disclosing to reduce traffic load of a sensor network and reduce energy cost, the amount of data transmitted in the network is reduced by means of data aggregation).
Khalifa in view of Ma is not relied upon as explicitly disclosing a minimum use of said communication network.
However, Kallus further discloses a minimum use of said communication network. (Kallus, e.g., see para. [0014] disclosing an individual transmit time can be determined for each smart meter, a transmission time with a lower success rate can be avoided so that the success rate of the transmission of the measurement report increases. This leads to a smaller number of retransmissions of the measurement report, the retransmission rate is minimized; see also para. [0073] disclosing the system enables several transmit schemes: it is possible to implement different algorithms from simple adapted randomization strategy to complex long-term machine learning based solutions in a modular manner; wherein the learning strategy cited above described statistical analysis; see also para. [0075] disclosing the efficiency and the quality of the communication between the smart meters and the control entity will significantly increase. The message loss rate is decreasing due to the better adaptation to the measured signal-to-noise ratio of the communication line. Due to the lower loss rate, the number of retransmissions is decreased as well. The delay of receiving smart meter vents and logs decreases which reduces the time delay of the necessary action taken by the utility company).
Accordingly, it would be prima facie obvious to one of ordinary skill in the art, at the time the invention was effectively filed, to have modified Khalifa in view of Ma’s method with Kallus’ minimum use of said communication network for at least the reasons that minimum network uses requires less resources, less energy, and decreases network congestion, thereby improving the efficiency of the network.
Regarding claim 15, Claim 15 recites The data collection system according to claim 13, furthermore comprising electronic circuitry configured to make the statistical analysis with reference to a minimum use of said communication network., and is rejected under 35 U.S.C. 103 as being unpatentable by Khalifa in view of Ma, in further view of Kallus for reasons analogous to those set forth in connection with claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US 11,228,982 B2 to Gubeskys et al. relates to concurrent wireless communication and object sensing.
US 2019/0075597 A1 to Yerramalli et al. relates to methods, apparatuses and systems for supporting long term channel sensing in shared spectrum.
US 9,961,580 B2 to Strobl et al. relates to mobile terminal devices and methods of performing radio measurements.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIC S. VON WALD whose telephone number is (571)272-7116. The examiner can normally be reached Monday - Friday 7:30 - 5:30.
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/E.S.V./Examiner, Art Unit 2863
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2863