DETAILED ACTION
1. Claims 1, 3, and 5-10 have been presented for examination.
Claims 2 and 4 have been cancelled.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
PRIORITY
3. Acknowledgment is made that this application is a 371 of PCT/CN2021/122097 filed 09/30/2021.
Response to Arguments
4. Following Applicants amendments, resulting in a change in scope, and arguments, filed 3/26/26, an additional prior art rejection has been presented below.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
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 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.
5. Claim(s) 1, 3, 5-10 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 20200042915, hereafter Samson in view of U.S. Patent Publication No. 20110251975, hereafter Evans.
Regarding Claim 1: The reference discloses A BIM visualization system, comprising: a visualization platform and a management platform, wherein the management platform comprises a design client and a construction client;
the management platform is configured to acquire design data uploaded by the design client and construction data uploaded by the construction client, and is further configured to forward the design data to the construction client; and (Samson. [0028] “In another example a user could overlay a document and drawing with a Building Information Model (BIM) model for a construction project. The module may also be used to actively communicate or display content outside of the system for example in BIM database or a smart phone, smart device, mobile device etc.” [0077] The system also provides automatic creation of temporary signalization plans for a construction phase. [0078] The system may also provide a visual tool showing the actual and projected interdependencies between different trades, conflicting materials between different systems and any discrepancies.)
the visualization platform is configured to acquire the design data and the construction data from the management platform, generate a three-dimensional model according to the design data and the construction data, and display the three-dimensional model; (Samson. [0079] A visualization tool may show the progress of the construction in 3-D and provides a user with the option to visualize the impact of any kind of change for example the materials, size of material, changes in the construction phases, etc. [0080] A simulation program may be available to the user to show any deviations from the original design.)
wherein the management platform further comprises a supervision client, and the management platform is further configured to generate supervision data by the supervision client and forward the supervision data to the design client and the construction client. (Samson. [0032] The present invention may optionally include management level strategy by integrating an alarm notification system. Different levels of access may be set up for each category of users. There may be default settings attributed to each kind of user but such settings may be changed and customized. [0076] The database may provide the users with sustainable construction and design methodologies such as LEED construction, which may involve incorporating adaptations for energy efficient buildings and utilities construction, use of energy efficient machinery, adding energy efficient production processes to areas such as automation, control technology, efficient engines, and heat recovery. [0026] “The notifications may escalate to different users or higher levels of management ensuring the risk is mitigated.”)
wherein the supervision client is configured to acquire preset product data and product data forwarded by the management platform, … and compare the preset product data with the product data to generate production supervision data, wherein the production supervision data is used to characterize whether products satisfy requirements of the preset product data. (Samson. [0027] Predictive analysis uses techniques such as data mining, statistical algorithms and modeling to process and analyze data. It may provide analysis of a parameter in relative comparison with an expected target. The system may display the variation between current data and expected parameter targets. Identification of potential abnormalities may be based on parameters set by default for example parameters set by default using BIM, ERP or customized project targets. Referring to FIG. 4. predictive analysis may receive input data from a user 31 or 35, using BIM 32 or ERP 36 data as a precedent or default, the system formulates targeted parameters from BIM metadata 33 or ERP metadata or customized project specific targets 37 and displays this to the user 30 or 34.)
Samson does not explicitly recite wherein the product data indicates actual data acquired by a production layer during actual production of products according to the design data and the preset product data.
However Evans discloses wherein the product data indicates actual data acquired by a production layer during actual production of products according to the design data and the preset product data. (Evans. [0055] “[0055] Manufacturers make significant investment in their engineering and design organizations to maintain and manage detailed geometry and other design data related to their engineered products. Disclosed embodiments leverage this repository of data in an efficient manner to extend existing engineering design constructs for visual representation, viewing and comparison of product designs to actual physical assets that are manufactured…”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to utilize the actual product data of Evans for the model/system of Samson since “one product design can result in hundreds or thousands of physical assets related to it, the potential for being able to access relevant accurate design data in context of a specific physical product significantly increases the footprint and application of the intellectual capital that has been developed…” as per Evans [0055]
Regarding Claim 3: The reference discloses The system according to claim 1, wherein the supervision client is configured to acquire preset design data and the design data forwarded by the management platform, and compare the design data with the preset design data to generate design supervision data. (Samson. [0027] Predictive analysis uses techniques such as data mining, statistical algorithms and modeling to process and analyze data. It may provide analysis of a parameter in relative comparison with an expected target. The system may display the variation between current data and expected parameter targets. Identification of potential abnormalities may be based on parameters set by default for example parameters set by default using BIM, ERP or customized project targets. Referring to FIG. 4. predictive analysis may receive input data from a user 31 or 35, using BIM 32 or ERP 36 data as a precedent or default, the system formulates targeted parameters from BIM metadata 33 or ERP metadata or customized project specific targets 37 and displays this to the user 30 or 34… If the module recognizes a negative pattern, a report or alert may be generated providing suggested actions to remediate or mitigate the negative pattern.)
Regarding Claim 5: The reference discloses The system according to claim 1, wherein the supervision client is configured to acquire the preset design data and the construction data forwarded by the management platform, and compare the preset design data with the construction data to generate construction supervision data, where the construction supervision data is used to characterize whether the products are subjected to construction operation according to the requirements of the preset design data. (Samson. [0027] Predictive analysis uses techniques such as data mining, statistical algorithms and modeling to process and analyze data. It may provide analysis of a parameter in relative comparison with an expected target. The system may display the variation between current data and expected parameter targets. Identification of potential abnormalities may be based on parameters set by default for example parameters set by default using BIM, ERP or customized project targets. Referring to FIG. 4. predictive analysis may receive input data from a user 31 or 35, using BIM 32 or ERP 36 data as a precedent or default, the system formulates targeted parameters from BIM metadata 33 or ERP metadata or customized project specific targets 37 and displays this to the user 30 or 34. [0079] A visualization tool may show the progress of the construction in 3-D and provides a user with the option to visualize the impact of any kind of change for example the materials, size of material, changes in the construction phases, etc.”)
Regarding Claim 6: The reference discloses The system according to claim 1, wherein the management platform is configured to compare the design data with product data forwarded by the management platform to generate first comparison data, where the first comparison data is used to characterize whether products satisfy requirements of the design data. (Samson. [0027] Predictive analysis uses techniques such as data mining, statistical algorithms and modeling to process and analyze data. It may provide analysis of a parameter in relative comparison with an expected target. The system may display the variation between current data and expected parameter targets. Identification of potential abnormalities may be based on parameters set by default for example parameters set by default using BIM, ERP or customized project targets. Referring to FIG. 4. predictive analysis may receive input data from a user 31 or 35, using BIM 32 or ERP 36 data as a precedent or default, the system formulates targeted parameters from BIM metadata 33 or ERP metadata or customized project specific targets 37 and displays this to the user 30 or 34.)
Regarding Claim 7: The reference discloses The system according to claim 1, wherein the management platform is configured to compare product data forwarded by the management platform with the construction data to generate second comparison data, where the second comparison data is used to characterize whether physical products satisfy requirements of the product data. (Samson. [0027] Predictive analysis uses techniques such as data mining, statistical algorithms and modeling to process and analyze data. It may provide analysis of a parameter in relative comparison with an expected target. The system may display the variation between current data and expected parameter targets. Identification of potential abnormalities may be based on parameters set by default for example parameters set by default using BIM, ERP or customized project targets. Referring to FIG. 4. predictive analysis may receive input data from a user 31 or 35, using BIM 32 or ERP 36 data as a precedent or default, the system formulates targeted parameters from BIM metadata 33 or ERP metadata or customized project specific targets 37 and displays this to the user 30 or 34.)
Regarding Claim 8: The reference discloses The system according to claim 1, further comprising: a technique and construction method database, wherein the technique and construction method database communicates with the management platform; and the management platform is configured to acquire the design data form the technique and construction method database, and forward the design data to the design client, the construction client, or a supervision client in the management platform. (Samson. [0032] The present invention may optionally include management level strategy by integrating an alarm notification system. Different levels of access may be set up for each category of users. There may be default settings attributed to each kind of user but such settings may be changed and customized. [0076] The database may provide the users with sustainable construction and design methodologies such as LEED construction, which may involve incorporating adaptations for energy efficient buildings and utilities construction, use of energy efficient machinery, adding energy efficient production processes to areas such as automation, control technology, efficient engines, and heat recovery. [0026] “The notifications may escalate to different users or higher levels of management ensuring the risk is mitigated.”)
Regarding Claim 9: The reference discloses The system according to claim 1, wherein the management platform comprises: a cloud database configured to store preset design data and preset product data. (Samson. [0034] Referring to FIGS. 2 and 5 the first step of the data acquisition may be based on the internet of things, intelligent electronic labels, scanning technology or by other means that enable data collection in real-time from any data source such as a sensor 40 or a sensor node 20 from any location including construction, operational and administrative sites provided that there exists a network 21 connection, The information can be provided to an end-point module or node 22 such as any mobile device, IOS, Android, wearable device, or any other smart platform. The data may be transferred to a server or a cloud server 23 or 41. Based on algorithms, the relevant data may be processed and transferred to the assigned modules 42 of the system. The data may be accessed by a user using a preconfigured user interface 24 such as a computer, mobile device, smart device, augmented reality device, etc.)
Regarding Claim 10: The reference discloses The system according to claim 1, wherein the management platform further comprises a production client, and the management platform is further configured to acquire preset product data and product data uploaded by the production client. (Samson. [0062] Equipment maintenance alarm notifications may be generated. For example, customizable parameters include temperature, pressure, levels, etc. that may monitored and any deviations may be communicated to the designated users. [0063] Equipment hours tracking may provide useful information with respect to allocation of hours of specific activities, or maintenance cycles. [0064] Alarm notification may be generated for abnormal equipment's operation hours (e.g. unused equipment, operation out of regular work hours, overtime, etc.).)
Conclusion
6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
7. All Claims are rejected.
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
i) U.S. Patent Publication No. 20150271218
ii) Johansson, Mikael, Mattias Roupé, and Petra Bosch-Sijtsema. "Real-time visualization of building information models (BIM)." Automation in construction 54 (2015): 69-82.
iii) Chuang, Tien-Hsiang, Bo-Cing Lee, and I-Chen Wu. "Applying cloud computing technology to BIM visualization and manipulation." 28th International Symposium on Automation and Robotics in Construction. Vol. 201. No. 1. 2011.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Saif A. Alhija whose telephone number is (571) 272-8635. The examiner can normally be reached on M-F, 10:00-6:00.
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) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Renee Chavez, can be reached at (571) 270-1104. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. Informal or draft communication, please label PROPOSED or DRAFT, can be additionally sent to the Examiners fax phone number, (571) 273-8635.
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SAA
/SAIF A ALHIJA/Primary Examiner, Art Unit 2186
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