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 .
This communication is in response to Application 18/992,834 filed on 1 January, 2025 and is a national stage filing under 35 U.S.C. § 371 of International Application No. PCT/IN2024/050589, filed on May 20, 2024, which claims the benefit of priority to Indian Application No. IN 202321043367, filed on June 28, 2023.
Claims 1-9, and 12-17 are pending.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 4, 9 and 13-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hao et al (US 2011/0298804).
Regarding claim 1, Hao teaches a system (100) for generating at least one thematic layer for network performance monitoring and analysis (Hao fig.2; Hao [0017] provides “The present disclosure provides systems and methods for providing a visual display of data attributes from a plurality of data sources. The visual display may allow a user to visually correlate data attributes from a plurality of data sources in a single view using a graphical representation in a common timeline. In addition to allowing a user to visually correlate data attributes, the system can also perform the correlation and provide a display of the correlation to the user. The system can further be configured to align data attributes and display data attributes to the user. The systems and methods can enable a single view of data attributes from multiple scattered data sources using graphical cells arranged in columns and synchronized with a common timeline”; Hao figs. 3, 4, 6), the system (100) comprising:
an input unit (102) configured to receive at least one request from a user (Hao [0018] provides “The graphical selection module 114 may allow the user to select a graphical representation of a data attribute”; Hao [0022] provides “The selection module may prompt the user 208 to select data attribute names associated with the data attributes that will be visually displayable”);
a plurality of data sources (104), each of the plurality of data sources (104) is configured to store a plurality of information corresponding to a plurality of performance attributes associated with the network (Hao [0019-0020] provides “The process 200 can comprise a plurality of data sources 202a-c… the plurality of data sources 202 may comprise data records that store information related to a database or other data warehouse data source component. The information stored in the plurality of data sources may describe the performance of the data management system”);
and a processing unit (106) configured to cooperate with the input unit (102) and the plurality of data sources (104) to receive the at least one request and the stored information, respectively and is further configured to extract at least one information of the plurality of information corresponding to the received request (Hao [0021] provides “The attribute identification module 102 in FIG. 1 can search the data sources 202a-c for data attributes. For example, the attribute identification module can search the data source 202a and may find the data attributes A and B stored in the data source. The measurements in the data source 202a may have been stored at a measuring period of time T. Also, the attribute identification module can search the data source 202b and may find the data attributes C, D, and E stored in the data source”) and to process the extracted information for generating the at least one thematic layer (Hao [0022] provides “The selection module may prompt the user 208 to select data attribute names associated with the data attributes that will be visually displayable. For example, in FIG. 2, at the selection 210, the user 208 may select the data attributes associated with the data attributes A, B, C, D, and E for visual display”).
Regarding claim 2, the system (100) as claimed in claim 1, includes a display unit (112) configured to cooperate with the processing unit (106) and is further configured to display the at least one generated thematic layer (Hao [0022] provides “…the display module 110 in FIG. 1 may create graphical representations of the user selected data attributes as shown in FIG. 2”).
Regarding claim 4, the system (100) as claimed in claim 1, wherein the at least one request includes at least one or more of a data source from the plurality of data sources (104), at least one attribute from the plurality of performance attributes corresponding to the source, and an operator (Hao [0019-0022] provides “The process 200 can comprise a plurality of data sources 202a-c… the plurality of data sources 202 may comprise data records that store information related to a database or other data warehouse data source component. The information stored in the plurality of data sources may describe the performance of the data management system”).
Regarding claim 9, the system (100) as claimed in claim 1, wherein the user is configured to customize the at least one thematic layer by defining at least one or more of data points, adjusting color schemes associated with the at least on thematic layer, and incorporating animations (Hao [0031] provides “The visual display can display data attributes according to color”; Hao [0034] provides “...the display module assigns the graphical cell 310 a fill pattern or color. The fill pattern or color corresponds to a specific value for the quantified display attribute. The fill pattern may comprise a specific color, a grayscale value, a hatch pattern, etc. For example, the fill legend 312 can associate particular fill patterns with numeric values for the data attributes”).
Regarding claim 13, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
Regarding claim 14, this claim contains limitations found within those of claim 2, and the same rationale of rejection applies, where applicable.
Regarding claim 15, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
Regarding claim 16, the method (600) as claimed in claim 13, further comprising selecting, by the user, a data source from the plurality of data sources (104), at least one attribute from the plurality of performance attributes 28 corresponding to the selected source, and an operator via the input unit (102) (Hao [0018] provides “The graphical selection module 114 may allow the user to select a graphical representation of a data attribute”; Hao [0022] provides “The selection module may prompt the user 208 to select data attribute names associated with the data attributes that will be visually displayable”; Hao [0019-0022] provides “The process 200 can comprise a plurality of data sources 202a-c… the plurality of data sources 202 may comprise data records that store information related to a database or other data warehouse data source component. The information stored in the plurality of data sources may describe the performance of the data management system”).
Regarding claim 17, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
Regarding claim 18, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
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.
Claims 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Hao et al (US 2011/0298804), in view of Maluf et al (US 9,824,128).
Regarding claim 5, Hao teaches the system (100) as claimed in claim 4, but Hao does not explicitly teach wherein the operator is a relational operator or a user defined operator. However, in a similar field of endeavor, Maluf teaches wherein the operator is a relational operator or a user defined operator (Maluf claim 21 provides “…updating said query search object with user-defined schema values for a relational operator”).
One of ordinary skill in the art before the effective filing date of Applicant’s claimed invention would have recognized the utility of the operators as taught by Maluf, in the Hao system to support filtering, manipulating, and analyzing data. Operators will allow user to perform arithmetic calculations, evaluate logical conditions, compare values, and match patterns, which is essential for writing efficient queries and managing data accurately.
Regarding claim 6, Hao-Maluf teaches the system (100) as claimed in claim 5, wherein the user defined operator is a defined range or a distinct value (Maluf col.8 lines 14-20 provides “Values that may be entered through the use of menus, user interface prompts, or other input methods include, but are not limited to: database identifier values; search context values; set operation identifiers; or any other alpha numeric symbol or semantic identifier relevant to developing queries or specifying results to be returned from a search of heterogeneous databases”). Motivation provided with reference to claim 5.
Regarding claim 7, Hao-Maluf teaches the system (100) as claimed in claim 5, wherein the relational operator is equals to, not equal to, less than or equal to, greater than or equal to, less than, greater than (Maluf col.8 lines 49-51 provides “Logical operations, which may be performed by logical operations processor 49 includes, but is not limited to, the following: logical operations, contains, not contains, greater than, less than, greater than or equal, less than or equal, equal to, not equal”). Motivation provided with reference to claim 5.
Claims 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Hao et al (US 2011/0298804), in view of Purdy et al (US 2017/0237628).
Regarding claim 3, Hao teaches the system (100) as claimed in claim 1, but Hao does not explicitly teach wherein the plurality of performance attributes includes a cell level attribute, a site level attribute, an end user mute rate, a peak data rate, a peak spectral efficiency, an area traffic capacity, a latency, a connection density, an average spectral efficiency, an energy efficiency, an air fiber connectivity, a mobility interruption time, and a bandwidth. However, in a similar field of endeavor, Purdy teaches wherein the plurality of data sources (104) includes a performance management source, a site level attributes source, a cell level attributes source, a configuration management source, and a fault management source (Purdy [0011] provides for performance, configuration and fault management, [0061] provides for cell site sources).
One of ordinary skill in the art before the effective filing date of Applicant’s claimed invention would have recognized the utility of collecting multiple sources and types of data as taught by Purdy, in the Hao system to reveal correlations, and provide a comprehensive view of complex datasets.
Regarding claim 8, Hao has taught the system (100) as claimed in claim 1, but Hao does not explicitly teach wherein the plurality of data sources (104) includes a performance management source, a site level attributes source, a cell level attributes source, a configuration management source, and a fault management source. However, in a similar field of endeavor, Purdy teaches wherein the plurality of data sources (104) includes a performance management source, a site level attributes source, a cell level attributes source, a configuration management source, and a fault management source (Purdy [0011] provides for performance, configuration and fault management, [0061] provides for cell site sources). Motivation provided with reference to claim 8.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Hao et al (US 2011/0298804), in view of Souza (US 2011/0012917).
Regarding claim 12, Hao teaches system (100) as claimed in claim 1, but Hao does not explicitly teach further including a database (110) for storing the at least one generated thematic layer as an image, such that the system is configured to analyze the stored thematic layer for generating at least one pattern, at least one trend, and at least one anomaly related to the network. However, in a similar field of endeavor, Souza teaches including a database (110) for storing the at least one generated thematic layer as an image, such that the system is configured to analyze the stored thematic layer for generating at least one pattern, at least one trend, and at least one anomaly related to the network (Souza Abstract provides “The application may generate a digital image by determining a color for each pixel of the digital image based on how the cells are mapped to colors. The digital image enables data analysis, such as the identification of trends, patterns, and/or anomalies, on any number of data sets in an expeditious and intuitive manner. The digital image may be dynamically updated to reflect further analysis or incremental updates to the data sets”).
One of ordinary skill in the art before the effective filing date of Applicant’s claimed invention would have recognized the utility of storing data as an image as taught by Souza to allow for faster processing of large continuous variables.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Papantoniou et al US 2022/0284432.
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/I.R/ Examiner, Art Unit 2459 /SCHQUITA D GOODWIN/Primary Examiner, Art Unit 2459
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