Prosecution Insights
Last updated: April 19, 2026
Application No. 18/511,930

ELECTRIC VEHICLE FLEET MOBILE APPLICATION

Non-Final OA §103
Filed
Nov 16, 2023
Examiner
HOLLY, JOHN H
Art Unit
3696
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Iems Solution Ltd.
OA Round
1 (Non-Final)
54%
Grant Probability
Moderate
1-2
OA Rounds
3y 6m
To Grant
84%
With Interview

Examiner Intelligence

Grants 54% of resolved cases
54%
Career Allow Rate
267 granted / 499 resolved
+1.5% vs TC avg
Strong +31% interview lift
Without
With
+30.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
24 currently pending
Career history
523
Total Applications
across all art units

Statute-Specific Performance

§101
40.7%
+0.7% vs TC avg
§103
39.4%
-0.6% vs TC avg
§102
4.3%
-35.7% vs TC avg
§112
7.8%
-32.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 499 resolved cases

Office Action

§103
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 . DETAILED ACTION This Office Action is in response to Applicant’s communication filed on December 17, 2023 for the patent application 18/511,930. Claims 1 – 10 are pending in the application. Information Disclosure Statement The Information Disclosure Statement (IDS) submitted on March 19, 2025 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, this Information Disclosure Statement is being considered by the Examiner. 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 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 of this title, 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 10 and 1 – 9 are rejected under 35 U.S.C. 103 as being obvious over John A. Dorn et al. (Pat. # US 9,766,671 B2 – herein referred to as Dorn) in view of Rajit Gadh et al. (Pat. # US 9,026,347 B2 – herein referred to as Gadh). Re: Claim 10, Dorn discloses a method for managing electric vehicle fleet with a mobile app, comprising: providing a distributed energy resource management platform comprising a distributed energy resource management engine connected to a distribution system operator software agent, a driver software agent, an electric vehicle servicing entities software agent, and a blockchain service module connected to each software agent (Dorn, col. 4, lines 36 – 45 – The charging infrastructure management system 100 pro­ vides a distributed intelligence system that may be used to track power usage of electric vehicles across a fleet or from various domestic customers. The system 100 includes a network 101 through which to communicate, which may be wired or wireless or a combination thereof, and may include the Internet and other communications networks, whether of the LAN or WAN variety. A plurality of customer computers 102 and mobile devices 103 may access the network 101 and services provided by the system 100.), providing an electric vehicle servicing entity platform with an electric vehicle servicing entity controller software module connected to at least one charging station (Dorn, col. 15, lines 1 – ? – The computer system 900 may include a processor 908, such as a central processing unit (CPU) and/or a graphics processing unit (GPU). The processor 908 may include one or more general processors, digital signal processors, application specific integrated circuits, field programmable gate arrays, digital circuits, optical circuits, analog circuits, combinations thereof, or other now known or later-developed devices for analyzing and processing data. The processor 908 may implement the set of instructions 902 or other software program, such as manually-programmed or computer-generated code for implementing logical functions. The logical function or any system element described may, among other functions, process and/or convert an analog data source such as an analog electrical, audio, or video signal, or a combination thereof, to a digital data source for audio-visual purposes or other digital processing purposes such as for compatibility for computer processing.), providing an advanced distribution management system platform (Dorn, col. 4, lines 36 – 45 – The charging infrastructure management system 100 pro­ vides a distributed intelligence system that may be used to track power usage of electric vehicles across a fleet or from various domestic customers. The system 100 includes a network 101 through which to communicate, which may be wired or wireless or a combination thereof, and may include the Internet and other communications networks, whether of the LAN or WAN variety. A plurality of customer computers 102 and mobile devices 103 may access the network 101 and services provided by the system 100.), providing an electric vehicle driver platform (Dorn, col. 7, lines 56 – 67 – FIG. 3 shows a hierarchy view of the EV charging infrastructure management systems 100, 200 of PIGS. 1 and 2, showing flow of power and types of communication between different levels of the grid and a fleet 107 of electric vehicles and of EV charging stations 106. The different levels of the grid include, but are not limited to: (4) enterprise; (3) substation; (2) pole top 305; and (1) local. Pole top 305 refers to the transformer level and local refers to the street level, such as in parking lots, charging stations and in homes. A home controller 310 may provide a gateway for communication between a home (or residential) charging station 108 and the network 101.). However, Dorn does not expressly disclose: connecting the distributed energy resource management platform with the advanced distribution management system platform, the electric vehicle driver platform electronically, and the electric vehicle servicing entity platform through a network, such that the distributed energy resource management platform generates and manages at least one smart contract based on transactive energy web app data from the distribution system operator platform, metered data from the electric vehicle servicing entity platform, and transactive energy mobile data app data from the electric vehicle driver platform. In a similar field of endeavor, Gadh discloses: connecting the distributed energy resource management platform with the advanced distribution management system platform, the electric vehicle driver platform electronically, and the electric vehicle servicing entity platform through a network, such that the distributed energy resource management platform generates and manages at least one smart contract based on transactive energy web app data from the distribution system operator platform, metered data from the electric vehicle servicing entity platform, and transactive energy mobile data app data from the electric vehicle driver platform (Gadh, col. 32, lines 4 – 21 – The mobile devices used in the WINSmartEV architecture of the system would enable real-time event based aggregation and charge scheduling. A central server would host this software, maintaining push connections to user devices, and maintaining a database of user charging preferences that would be synced whenever the user updates it using the web application. In addition, the server architecture would maintains a database of battery information including: (a) safety data including make, model, nominal capacity (Ah), nominal voltage (V), max charge current (A), charging voltage, and initial charging current; (b) current EV battery status (including a time stamp, location with latitude and longitude), status (charging, discharging, backfill), current state of charge (V); and (c) station ID, level, charging station location with latitude and longitude, level (1,2,3), plug type. The software within the WINSmartEV architecture would enable interfacing with hardware including the chargers themselves, if avail­ able, and sensor nodes via a direct interface or through a middleware.). Therefore, in light of the teachings of Gadh, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the method of Dorn, motivation according to one KSR Exemplary Rationale where a known technique is used to improve similar methods and systems in the same way by provide an electric vehicle may also include a voltage sensor connected to the computer and associated programming for measuring battery voltage, and as well as a current sensor connected to the computer and programming for measuring battery current. Additionally, the electric vehicle may include a global positioning sensor for determining the position of the electric vehicle, a transmitter for transmitting the position, state of charge, and identification of the electric vehicle. The electric vehicle may include a receiver for receiving information from a remote source. Such information received from the remote source may include the location of a charging station, the charge capacity of the charging station, and the cost per kWh of charge at the charging station. (Gadh, cols. 2 - 3, lines 54 – 4) – Re: Claim 1, Claim 1 is a system claim corresponding to method claim 10. Therefore, claim 1 is analyzed and rejected as previously discussed with respect to claim 10. Re: Claim 2, Dorn discloses the mobile app of claim 1, wherein the electric vehicle driver platform is connected to at least one sensor, wherein the sensor has Internet-of-Things capability (Dorn, col. 12, lines 1 – 4 – Sensors may be placed on the transformers that communicate over fiber, wireless or via power lines to pass its data to the substation controllers coupled with the charge applications and to the enterprise communication systems (FIG. 3).); (Dorn, col. 14, lines 46 – 59 – The computer system 900 may also be implemented as or incorporated into various devices, such as a personal computer or a mobile computing device capable of executing a set of instructions 902 that specify actions to be taken by that machine, including and not limited to, accessing the Internet or Web through any form of browser. Further, each of the systems described may include any collection of sub-systems that individually or jointly execute a set, or multiple sets, of instructions to perform one or more computer functions.). Re: Claim 3, Dorn in view of Gadh discloses the mobile app of claim 1, wherein the smart contract the software agents can manage and accept offers of smart contracts (Gadh, col. 33, lines 38 – 44 – The WINSmartEV architecture would enable the ability to pay the service providers only for the amount of data trans­ actions performed provides an opportunity to both small and large charging station organizations to minimize costs in data storage and the option to scale up their operations easily. Cloud based database service providers are typical in such a distributed architecture for the above mentioned reasons.). The rationale for support of motivation, obviousness and reason to combine see claim 1 above. Re: Claim 4, Dorn discloses the mobile app of claim 1, wherein the electric vehicle serving entity platform is implemented on a grid-to-vehicle system and transmits fleet charging service data (Dorn, col. 2, lines 1 – 8 – The smart meter may then communicate that information via some network back to the local utility for monitoring and billing purposes (telemetering). While these recent advances in upgrading the power grid are beneficial, more advances are necessary. It has been reported that in the United States alone, half of generation capacity is unused, half the long distance transmission network capacity is unused, and two thirds of its local distribution is unused.). Re: Claim 5, Dorn discloses the mobile app of claim 1, wherein the electric vehicle serving entity platform is implemented on a vehicle-to-grid system and transmits fleet discharging service data (Dorn, col. 4, lines 36 – 45 – The charging infrastructure management system 100 pro­ vides a distributed intelligence system that may be used to track power usage of electric vehicles across a fleet or from various domestic customers. The system 100 includes a network 101 through which to communicate, which may be wired or wireless or a combination thereof, and may include the Internet and other communications networks, whether of the LAN or WAN variety. A plurality of customer computers 102 and mobile devices 103 may access the network 101 and services provided by the system 100.). Re: Claim 6, Dorn discloses the mobile app of claim 1, wherein the electric vehicle driver platform receives and transmits at least one incentive price data (Dorn, col. 11, lines 4 – 9 – The utility company may provide a rebate to the customer when the customer schedules, ahead of time, a time and place to charge an electric vehicle to incentivize customers alerting the system 200 as to future demand needs, making it easier for the system 200 to forecast expected load distribution.). Re: Claim 7, Dorn discloses the mobile app of claim 1, further comprising at least one user interface for said platforms (Dorn, col. 8, lines 45 – 60 – FIG. 5 is an exemplary EV optimization engine solution architecture 500 that interfaces with and is a part of the EV charging infrastructure management systems 100, 200 of FIGS. 1-3. The architecture 500 may include the EV optimization engine 142, the complex event processor (CEP) 144, the demand response management system 158, a customer profiles database 159, other devices 180 that consume and/or generate power, distributed generation 204, a customer profiles database 503, and locational marginal prices (LMP) data 505 that may be stored in a database.). Re: Claim 8, Dorn discloses the mobile app of claim 7, wherein the user interface includes a vehicle status tab, a vehicle specification tab, and an electric vehicle servicing entity map tab, and an electronic wallet tab (Dorn, col. 7, lines 46 – ? – The Web 2.0 & mobile device application 178 may also, as shown in FIG. 4, provide to mobile devices 103 the ability for users to search, find, map and get turn-by-turn directions to charge point stations, to determine if the station is available or in use, and/or to provide information as to cost of charging at the charge point station. The mobile device user may then start and stop a charging session directly from the mobile (or other handheld smart) device, and receive real-time charging status notifications.). Re: Claim 9, Dorn discloses the mobile app of claim 7, wherein the user interface provides for managing locational marginal pricing data (Dorn, col. 10, lines 34 – 43 – The EV optlm1zation engine 142 may send analysis results and suggested control measures to the DMS system 158, which may then send real-time commands to electric vehicles, EV charging stations, substations, pole top or pad transformers and the like to control flow of power, charging timing that affects pricing and availability, and rules related to charging, power flow management and other aspects of optimizing power usage. The CEP 144 may calculate the cost of service, load use and track the cost over time and during different periods.). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOHN H. HOLLY whose telephone number is (571)270-3461. The examiner can normally be reached on MON. - FRI 10 AM - 8 PM. 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, MATTHEW S. GART can be reached on 571-272-8395. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /John H. Holly/Primary Examiner, Art Unit 3696
Read full office action

Prosecution Timeline

Nov 16, 2023
Application Filed
Jul 26, 2025
Non-Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12586052
STORE MOBILE TERMINAL DEVICE, PAYMENT DEVICE, SYSTEM, METHOD, AND RECORDING MEDIUM
2y 5m to grant Granted Mar 24, 2026
Patent 12572911
PREDICTING ITEM WEIGHTS USING A TRAINED MACHINE LEARNING MODEL
2y 5m to grant Granted Mar 10, 2026
Patent 12555090
REAL-TIME PROVISIONING OF TARGETED RECOMMENDATIONS BASED ON DECOMPOSED STRUCTURED MESSAGING DATA
2y 5m to grant Granted Feb 17, 2026
Patent 12511167
METHODS AND SYSTEMS FOR BALANCING LOADS IN DISTRIBUTED COMPUTER NETWORKS FOR COMPUTER PROCESSING REQUESTS WITH VARIABLE RULE SETS AND DYNAMIC PROCESSING LOADS
2y 5m to grant Granted Dec 30, 2025
Patent 12499431
CARD READER TERMINAL WITH EXTERNAL CONTACTLESS ANTENNA
2y 5m to grant Granted Dec 16, 2025
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
54%
Grant Probability
84%
With Interview (+30.8%)
3y 6m
Median Time to Grant
Low
PTA Risk
Based on 499 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month