DETAILED ACTION
Claims 1-20 are pending.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 6/20/2025 is being considered by the examiner.
Claim Rejections - 35 USC § 102
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 1-5, 8-12, and 15-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jaggers (US 11,113,987 B1)
With regards to Claim 1, Jaggers teaches a non-transitory machine-readable medium storing one or more sequences of instructions forming a technological collaboration tool facilitating support in field services (i.e., The present disclosure relates to systems and methods to facilitate the training, assessment, and dispatching of technicians to a customer location for at least the purpose of servicing or repairing machines, devices, or systems present at the customer location, Col. 1, Lines 7-10), wherein execution of said one or more instructions by one or more processors contained in a digital processing system cause said digital processing system to perform the actions of: obtaining a training data comprising characteristics of a plurality of technicians and characteristics of activities completed by each technician in resolving prior issues (i.e., Information presented to and collected by the technician at the customer location can be associated with a machine learning system., Col 8, Lines 29-40; Col 9. Lines 33-47;); training a machine learning (ML) model based on said training data, said ML model thereafter operable to determine a proficiency level of technicians in helping with a given activity (i.e., As would be appreciated, selection of the training material automatically via the training module can be useful to manage the content and amount of training material provided to a technician, a group of technicians, and/or a class of technicians over time. As used herein, a class of technicians can be a collection of technicians that entered a company or program at the same time such as “hired in January 2019,” whereas a grouping of technicians can be a ranking or level for a group of technicians, such as “novice,” “intermediate,” “expert,” “six months on the job,” or the like. Database records for such classes or groups of technicians can be incorporated into the database records for use in the selection of technicians for a service call as discussed elsewhere herein, Col. 20, Lines 25-38; Col 25, Lines 41-46); receiving, from a technician, a request for help with an activity, said technician being contained in said plurality of technicians (i.e., Also, should the technician find that he does not have the necessary skills to work on the specific aspect of the first machine, device, or system when after he performs an operational diagnosis thereof, he can provide a notification via interaction with a mobile app, voice, text, email, or the like, Upon such notification, the technician can be provided with training materials to assist him in completing the diagnosed problem. Information regarding such lack of qualification, and any actions relevant thereto, can be incorporated into the technician's database record. Yet further, the technician can also be provided with remote assistance via live interaction, Col. 14, Lines 5-16); determining, based on said ML model and said activity, a set of technicians capable of helping with said activity, said set of technicians being contained in a said plurality of technicians (i.e., In another implementation, the methods and systems can include a help module that connects the technician with a remote technician, for example an expert who is available off-site, in response to technician input. Such on-call expertise can facilitate the availability of expertise on an as-needed basis in view of the shortage of seasoned technician in today's job market. The expert can interact with the technician in need of training with real-time video, chat, voice, etc, Col. 25, Lines 20-28); and creating a group chat including said technician and said set of technicians as a response to said request (i.e., In another implementation, the methods and systems can include a help module that connects the technician with a remote technician, for example an expert who is available off-site, in response to technician input. Such on-call expertise can facilitate the availability of expertise on an as-needed basis in view of the shortage of seasoned technician in today's job market. The expert can interact with the technician in need of training with real-time video, chat, voice, etc, Col. 25, Lines 20-28)
With regards to Claim 2, Jaggers teaches wherein said creating comprises sending a request to a collaboration service to create said group chat including said technician and said set of technicians (i.e., In another implementation, the methods and systems can include a help module that connects the technician with a remote technician, for example an expert who is available off-site, in response to technician input. Such on-call expertise can facilitate the availability of expertise on an as-needed basis in view of the shortage of seasoned technician in today's job market. The expert can interact with the technician in need of training with real-time video, chat, voice, etc, Col. 25, Lines 20-28)
With regards to Claim 3, Jaggers teaches wherein said ML model employs a regression ML approach, wherein said determining comprises: applying said ML model to said activity to identify for each technician of said plurality of technicians, a proficiency score indicating said proficiency level of the technician in helping with said activity; and including technicians having said proficiency score above a threshold in said set of technicians (i.e., A technician database can then be reviewed by the computer (or other computing device) at 106 to identify a technician having at least some of the technician skill sets associated with tasks pertinent to servicing the machine, device or system at 109. The technician database can include a plurality of technician profiles corresponding to technicians who may be used to fulfill the service request. The technician profiles include indications of the skill sets obtained or possessed by the individual technicians, Col. 30, Lines 46-63)
With regards to Claim 4, Jaggers teaches wherein said characteristics of each technician includes one or more of a work skill of the technician, a work zone wherein the technician works, a list of activity types for recent activities completed by the technician and corresponding counts, a list of work skills used for the recent activities and corresponding counts, and a list of work zones for the recent activities and corresponding counts,
wherein said characteristics of each activity includes one or more of an activity type, an activity work skill specifying work skills required to perform the activity, an activity work zone specifying a work zone wherein the activity is to be performed, a customer associated with the activity, an inventory list specifying the inventories associated with the activity and activity description keywords extracted from a description of the activity (i.e., Still further, the technician database can incorporate information relevant or related to one or more qualifications that each technician in the database may hold as of the date he is assessed for matching with a service request. For example, “qualification” may represent a level of competence, experience, and/or facility with a particular machine or device, such as with a machine or device of a specific identity, such as a model number thereof (e.g., an HVAC system of a specific model number). This is referred to herein as “machine, device or system-specific qualification.” Qualification can also represent a level of competence, experience, and/or facility with a specific brand of a machine, device, or system (e.g., Trane® HVAC products). This is referred to herein as “machine, device, or system brand-specific qualification,” Qualification can also represent a level of competence, experience, and facility with a class of a machine, device, or system. This is referred to as “machine or device class-specific qualification,” A technician who is listed in the technician database as having a class-specific qualification can be expected to have competence, experience, and faculty with a specific brand and specific type of machine or device, but not necessarily vice versa, Col. 10, Lines 6-27; Col 12, Lines 43-64)
With regards to Claim 5, Jaggers teaches wherein said ML model employs a key based natural learning approach, further comprising one or more instructions for: calculating, after said training by using said ML model, a proficiency score for reach technician of said plurality of technicians, indicating said proficiency level of the technician in helping with a corresponding activity; and storing, in a data store, said corresponding activity against a combination of said technician and said proficiency score, wherein said determining comprises: retrieving from said data store, a set of combinations stored corresponding to said activity; and identifying a subset of combinations having said proficiency score above a threshold, wherein said set of technicians comprise the technicians in said subset of combinations (i.e., Beginning at 203, a machine, device or system in need of, or potentially in need of, repair or servicing is selected by a user a technician or a computer or other computing device. At 206, at least one skill needed by the technician to service or repair of the machine, device or system is identified. The needed skill or skills can be recorded in information in a technician database, Col. 31, Lines 22-37)
The limitations of Claim 8 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis.
The limitations of Claim 9 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis.
The limitations of Claim 10 are rejected in the analysis of Claim 3 above, and the claim is rejected on that basis.
The limitations of Claim 11 are rejected in the analysis of Claim 4 above, and the claim is rejected on that basis.
The limitations of Claim 12 are rejected in the analysis of Claim 5 above, and the claim is rejected on that basis.
The limitations of Claim 15 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis.
The limitations of Claim 16 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis.
The limitations of Claim 17 are rejected in the analysis of Claim 3 above, and the claim is rejected on that basis.
The limitations of Claim 18 are rejected in the analysis of Claim 5 above, and the claim is rejected on that basis.
Allowable Subject Matter
Claims 6-7, 13-14, and 19-20 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SURAJ M JOSHI whose telephone number is (571)270-7209. The examiner can normally be reached Monday - Friday 8-6 ET.
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/SURAJ M JOSHI/Primary Examiner, Art Unit 2447 December 19, 2025