DETAILED ACTION
This communication is a Non-Final Office Action rejection on the merits. Claims 1-20 are currently pending and have been addressed below.
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 .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without reciting significantly more.
Independent Claim 1
Step One - First, pursuant to step 1 in the January 2019 Revised Patent Subject Matter Eligibility Guidance (“2019 PEG”) on 84 Fed. Reg. 53, the claim 1 is directed to a method which is a statutory category.
Step 2A, Prong One - Claim 1 recites: A method for mission planning and execution, the method comprising: receiving, by a commander, course of action (COA) data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains; coordinating simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a likelihood of success (LOS) of the COAs, and executing models of the entities performing the activities; generating, a graphical view of the simulation of the COAs including scores associated with each COA; implementing a COA of the COAs selected by the commander; receiving information regarding a state of executing the COA; and providing a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the LOS updated as the COA is implemented. These claim elements are considered to be abstract ideas because they are directed to “certain methods of organizing human activity” which include “managing personal behavior.” In this case, providing information to support planning and execution across all echelons and domains is a social activity. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 - The judicial exception is not integrated into a practical application. Claim 1 includes additional elements: a user interface (UI); an orchestrator service; an analysis engine; a command and control engine; and multiple applications including an intelligence management service, a non-kinetic fires management service, a video sensor management service, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains.
The UI engine is merely used to: receive data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains; and provide a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the LOS updated as the COA is implemented (Paragraph 0068). The orchestrator service is merely used to: coordinate simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device; generate a graphical view of the simulation of the COAs including scores associated with each COA; and receive information regarding a state of executing the COA (Paragraph 0068). The analysis engine is merely used to determine a likelihood of success (LOS) of the COAs (Paragraph 0068). The command and control engine is merely used to execute models of the entities performing the activities (Paragraph 0068). The multiple applications are merely used to receive information regarding a state of executing the COA (Paragraph 0068). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f). These elements of “UI,” “orchestrator service,” “analysis engine,” “command and control engine,” and “applications” are recited at a high level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer element. The UI and the multiple applications are considered “field of use” since they are just used to receive information for a simulation analysis, but the technology is not improved (MPEP 2106.05h). Accordingly, alone and in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Step 2B - The claim does not include additional elements that are sufficient to amount significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the claims describe how to generally “apply” the concept of planning a mission based on the results of the simulation. The specification shows that the UI engine is merely used to: receive data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains; and provide a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the LOS updated as the COA is implemented (Paragraph 0068). The orchestrator service is merely used to: coordinate simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device; generate a graphical view of the simulation of the COAs including scores associated with each COA; and receive information regarding a state of executing the COA (Paragraph 0068). The analysis engine is merely used to determine a likelihood of success (LOS) of the COAs (Paragraph 0068). The command and control engine is merely used to execute models of the entities performing the activities (Paragraph 0068). The multiple applications are merely used to receive information regarding a state of executing the COA (Paragraph 0068). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f). In this case, the steps of “providing a dynamic location of the threat and threat mitigation activities” is considered a well-understood, routine, and conventional function since it's just “performing repetitive calculations” and “receiving or transmitting data over a network” (MPEP 2106.05(d)). Also, claim 1 does not provide any specific details of how the selected COA is implemented (MPEP 2106.05(f)). Lastly, the UI is merely used to arrange information in a manner that assists users in processing information more quickly, which is not sufficient to show an improvement in computer functionality (see MPEP 2106.05a). Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Independent claim 9 is directed to an article of manufacture at step 1, which is a statutory category. Claim 9 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one; step 2a, prong 2; and step 2b. Claim 9 further recites: a non-transitory machine-readable medium; and a machine – which are treated as just an explicit “processor/computer” for executing the operations and are treated under MPEP 2106.05f in the same manner as claim 1. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Independent claim 16 is directed to an apparatus at step 1, which is a statutory category. Claim 16 recites similar limitations as claim 1 and is rejected for the same reasons at step 2a, prong one; step 2a, prong 2; and step 2b. Claim 16 further recites: a processing circuitry; a display; and a memory – which are treated as just an explicit “processor/computer” for executing the operations and are treated under MPEP 2106.05f in the same manner as claim 1. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Dependent claims 2, 10, and 17 are directed to an additional element such as: a feasibility service. The feasibility service is merely used to narrow down a list of all possible friendly assets that can perform the actions to only those assets that can satisfy one or more of the feasibility criterion: (i) perform a required activity of the mission, (ii) are or can be in range of the target in time, (iii) have enough fuel to reach the target, (iv) are not adversely impacted by the weather, (v) are not impacted by readiness (training), (vi) are not adversely impacted by the terrain (uses data from modified combined obstacle overlays (MCOOs)), (vii) have sufficient field of view (if a satellite), or a combination thereof (Paragraph 0040). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is not patent eligible.
Dependent claims 3, 11, and 18 are directed to an additional element such as: a user data service. The user data service is merely used to receive possible actions that can be performed by each feasible entity selected for each activity (Paragraph 0070). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Thus, nothing in the claim adds significantly more to the abstract idea. The claim is not patent eligible.
Dependent claims 4-7, 12-15, and 19-20 are directed to additional elements such as: machine learning tools. The machine learning tools include: an asset optimization service that determines, for each feasible entity of the feasible entities, a time that the entity is to take action to perform a corresponding activity of the activities; a patterns of life service that monitors the geographical region for a new threat; and receive a change in location of the threat (Paragraphs 0070-0071). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. In this case, the claims do not provide any specific details about how the machine learning operates (e.g., how the machine learning is trained to identify the best time to attack the enemy and/or identify a threat). See 2024 AI Guidance, example 47, claim 2. Further, the step of “providing updated information regarding a new state of executing the COA” is considered a well-understood, routing, and conventional function since it's just “performing repetitive calculations” and “receiving or transmitting data over a network” (MPEP 2106.05(d)). Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
Dependent claim 8 is directed to an additional element such as: a single pane of glass. The single pane of glass is merely used to provide improved course of action support in an integrated common operational picture across the echelons (Paragraph 0001). Merely stating that the step is performed by a computer component results in “apply it” on a computer (MPEP 2106.05f) being applicable at both Step 2A, Prong 2 and Step 2B. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, the single pane of glass is merely used to arrange information in a manner that assists users in processing information more quickly, which is not sufficient to show an improvement in computer functionality (see MPEP 2106.05a). Thus, nothing in the claim adds significantly more to the abstract idea. The claim is ineligible.
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 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.
Claims 1, 9, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Mathew (US 2019/0353492 A1), in view of Hanneman et al. (US 2007/0130098 A1), in further view of Hanson et al. (US 2019/0310639 A1).
Regarding claim 1, Mathew discloses a method for mission planning and execution, the method comprising (Paragraph 0003, In one embodiment, there is provided a computer-implemented method for military planning, comprising: detecting a current geographical position; obtaining a destination geographical position; computing a plurality of travel routes to the destination geographical position; computing an attack probability for each travel route of the plurality of travel routes; organizing the plurality of travel routes into a list, wherein the list is sorted based on attack probability; and displaying the list on an electronic display):
receiving, by a commander through a user interface (UI), course of action (COA) data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0035, In embodiments, the computer system 102 evaluates each route on one or more of the following conditions: distance, time required, attack probability, and/or an escape factor. In embodiments, the attack probability may further be based on a variety of criteria, including, but not limited to, a detectability factor, and a proximity to enemy positions, as well as the confidence level associated with each of the enemy positions; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established; Examiner interprets: “time required” as “timing of the activities”; “air support information and naval support information” as the “entities to perform the activities”; “enemy locations and enemy capabilities” as the “threat data”; and “actionable intelligence” as the “threat mitigation”);
coordinating, by an orchestrator service, simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a [score] of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established);
generating, by the orchestrator service, a graphical view of the simulation of the COAs including scores associated with each COA (Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown);
implementing, by the orchestrator service, a COA of the COAs selected by the commander (Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0065, The significance of disclosed embodiments is that they facilitate more consensus building amongst commanders for decision making as well as immediate actions and/or preparations by other elements within the support sections. This enables the possibility of more effective operations with higher success rates, reduced casualties, and reduced financial costs);
receiving, by the orchestrator service and from multiple applications including an intelligence management service, …, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0034, The computer system 102 may then retrieve additional data from intelligence database 156. The additional data from intelligence database 156 can include, but is not limited to, enemy location, enemy numbers (number of troops, tanks, planes, etc. . . . ), enemy speed and heading, and a confidence level for the intelligence information. As an example, information that has been confirmed by a recent satellite image may be given a high confidence level, whereas information provided by an unreliable informant may be deemed to be at a low confidence level; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include airplanes or tanks. Therefore, based on broadest reasonable interpretation in light of the specification, Mathew discloses a kinetic fires management system since it can receive real-time intelligence information of the location of the airplanes or tanks. Also, Examiner notes that Mathew discloses: an intelligence management system since it can receive real-time intelligence information; and a sustainment management service since it can operate across multiple domains such as air support and naval support);
and providing, by the UI, a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the [score] updated as the COA is implemented (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0059, FIG. 7 shows an example of a virtual range card 700 in accordance with embodiments of the present invention. In such an embodiment, using the camera and geolocation system of the device 200, an annotated virtual range card is created. The virtual range card (VRC) indicates distances to important objects within a scene; Paragraph 0063, FIG. 8 shows a tactical information display 800 in accordance with additional embodiments of the present invention. Tactical information display 800 includes a route list 802, showing a list of possible routes. Tactical information display 800 may further include a virtual range card 804, displaying important information from a particular vantage point. Tactical information display 800 may further include a popup notice 806. Tactical information display 800 may further include a course of action recommendation (COAR) map 808; In this case, the score is updated after receiving real-time battlefield intelligence information. Also, Examiner notes that at least one of the threat mitigation activities may be to provide alternate routes).
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Although Mathew discloses receiving information regarding a state of executing the COA from a kinetic fires management service and a camera management server (e.g., real-time battlefield intelligence including enemy location, image of the scene, etc.), Mathew does not specifically disclose a non-kinetic fires management service and a video sensor management service.
However, Hanneman et al. discloses … a non-kinetic fires management service, a [picture] management service, a kinetic fires management service (Paragraph 0037, In one aspect, inputs/actions include political interactions, military interactions (both kinetic and non-kinetic), monetary exchange and others, as described below; Paragraph 0045, Turning in detail to FIG. 2, Microworld 205 is coupled to plural modules, including cultural model 206, IO model 208, kinetic model 209, non-kinetic model 211, operational conditions 210 and a database 207. The use and affect of these plural modules will now be described; Paragraph 0047, Microworld 205 also interfaces with kinetic model 209 and non-kinetic model 211. Kinetic model 209 provides inputs that are mobile. For example, in a military application, a weapon-target pairing tool provides an input that allows an entity to shoot a specific target and then report the damage. Microworld 205 takes the postulated outcome (i.e., whether the target was destroyed or not) and then evaluate the effect of destroying the target. For example, although the target was destroyed, but if it was a place of worship or was a school, it may have an undesired effect and that is analyzed by Microworld 205; Paragraph 0048, Non-kinetic model 211 provides non-kinetic input. Examples of such input are dropping leaflets, implementing a computer malfunction, deceptively re-routing supplies, or electronic warfare operations such as jamming a specific frequency. For example, a non-kinetic support tool provides a decision to jam a radio tower disabling communication. Microworld 205 evaluates the effect of the radio jamming beyond frequency detection that confirms that a radio tower has been jammed. For example, by jamming a radio tower, the local population does not get traffic related information and causes traffic jams delaying emergency operation. Microworld 205 will evaluate and consider these plural possibilities; Paragraph 0055, FIG. 3 provides an example of using Microworld 205. The operational environment 314 includes an aircraft 301 and a military tank 302 in a military situation. Information about the two vehicles is collected by information module 303. Information about vehicles 301 and 302 is provided to a logictics center 306, command control (CC) 305 and an intelligence-gathering module 304. It is noteworthy that modules 306, 305 and 304 may be computing systems placed in the same or different locations; Paragraph 0056, Command operational picture module (COP) 307 then sends out operational conditions 308 to simulation environment 315. Simulation environment 315 includes the Microworld 205 that is dynamically updated; Paragraph 0057, Microworld 205 receives the operational conditions and provides predicted outcomes/effects 309 based on potential DIME actions 312 and at time 311. As actions occur, the environment changes, thereby causing successive actions to have different effects than they would have previously (with respect to time 311). The predicted outcomes (309) are received by COP 307 that eventually takes action based on the recommendations. This information is then used to monitor and control the behavior of vehicles 301 and 302; Paragraph 0058, The adaptive aspects of the present invention can be used in military and civilian environments. Microworld 205 architecture allows a user to analyze and predict beneficial courses of action that specific entities should take depending on different parameters).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein information regarding a state of executing the COA is received from multiple applications/services of the invention of Mathew to further incorporate other information regarding a state of executing the COA (e.g., non-kinetic information and videos) of the invention of Hanneman et al. because doing so would allow the method to analyze and predict beneficial courses of action that specific entities should take depending on different parameters such as kinetic and non-kinetic inputs (see Hanneman et al., Paragraph 0058). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Although Mathew discloses determining a score of the COAs by an analysis engine, Mathew does not specifically disclose wherein the score is a likelihood of success. Also, although Mathew discloses receiving information regarding a state of executing the COA from multiple applications, the combination of Mathew and Hanneman et al. does not specifically disclose a video sensor management service.
However, Hanson et al. discloses coordinating, by an orchestrator service, simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a likelihood of success (LOS) of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0198, For example, and without limitation, a Mission Simulation and Training module 2020 may enable mission plans to be “run virtually” with various scenarios including variations in weather, sea state, and external system encounters. Operators may interject simulated manual control of unmanned vehicles. The Mission Simulation and Training module 2020 may provide a valuable estimate as to the likely success of the planned mission under various scenarios; Paragraph 0200, Also for example, and without limitation, a Mission Execution System 2040 may provide the functions necessary to begin and complete a successful mission of a fleet of unmanned vehicles 100. FIG. 19 illustrates a high level flow diagram of exemplary functions provided by the Mission Execution System modules; Paragraph 0201, Also for example, and without limitation, a Mission Data Processing System 2050 may receive and record mission data transmitted from the unmanned vehicles 100. A majority of missions may be presumed to relate to data gathering for intelligence, surveillance and reconnaissance (ISR) purposes. The Mission Data Processing system 2050 may collect and process large amounts of data, and may extract the most useful information out of the data in near real time. The Mission Data Processing system 2050 may perform complex data pattern processing in addition to raw storage and reporting; Paragraph 0230, The command and control block 3504, which may be under operator direction, or receive autonomous instructions as described above, sends positioning instructions to the well deck positioning controller 3502. Such instructions may include well deck pitch, well deck depth, well deck heading, well deck turn rate or well deck pitch rate, for example. The well deck positioning controller 3502 sends position information back to the command and control block 3504); …
receiving, by the orchestrator service and from multiple applications including an intelligence management service, …, a video sensor management service, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0075, For example, and without limitation, levels of abstraction for asset assignment may include an individual unmanned vehicle being assigned a specific task, an unmanned vehicle sub-group being responsible for a mission sub-goal, and/or a full set of available assets being dedicated to an overall mission goal. Therefore, planning may involve pre-configuring missions for each unmanned vehicle as well as mapping and visualizing groups of unmanned vehicles. “Control,” as used herein, refers to asset tracking, data collection, and mission adjustments accomplished in real-time as execution of a plan unfolds and as a mission evolves. Control, in the context of unmanned vehicle use, may involve selection of deployment modes (for example, and without limitation, air, marine, and submarine) and operational timing (for example and without limitation, active, wait at location, and remain on standby); Paragraph 0101, The present invention may include a sensor system to collect both vehicle 100 functional systems data and also external environmental data. The sensor system may comprise a variable set of sensors of many kinds that collect a wide variety of data from disparate sources, an electronic communication network over which the sensors may send data, and a data processing and routing system for collected sensor data. In one embodiment of the present invention, data representing the condition of components in the on-board environment may be collected by functional sensors such as the following: Global Position System (GPS), electronic compass, accelerometers, roll, pitch, yaw orientation, depth, pressure, temperature, voltage, drive train revolutions per minute (RPM), vibration at multiple locations, vehicle humidity, fuel level, and charge level. External environmental data may be collected by sensors that may include a video camera with computer-controlled articulation, zoom and night vision; electro-optical/infrared imaging and an audio sensor. Optional sensors may include, but are not limited to, radar, sonar, chemical and radiation sensors. External sensors may be mounted on a retractable device rack, as described below. Sensor signals may be connected to a signal multiplexing unit that may provide signal conditioning and routing, and the multiplexing component may be connected to a sensor data processing subsystem that includes a computer software component that may be located in the vehicle's 100 central computer; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include radar. Therefore, based on broadest reasonable interpretation in light of the specification, Hanson et al. discloses a kinetic fires management system since it can receive real-time intelligence information from a radar. Also, Examiner notes that Hanson et al. discloses: an intelligence management system since it can receive real-time intelligence information; a video sensor management service since it can collect environmental data from a video camera; and a sustainment management service since it can operate across multiple domains such as air and sea).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein a score is determined for the different COAs of the invention of Mathew and Hanneman et al. to further incorporate a likelihood of success for the different COAs of the invention of Hanson et al. because doing so would allow the method to provide a valuable estimate as to the likely success of the planned mission under various scenarios (see Hanson et al., Paragraph 0198). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 9, Mathew discloses a non-transitory machine-readable medium including instructions that, when executed by a machine, cause the machine to perform operations for mission planning and execution, the operations comprising (Paragraph 0003, In one embodiment, there is provided a computer-implemented method for military planning, comprising: detecting a current geographical position; obtaining a destination geographical position; computing a plurality of travel routes to the destination geographical position; computing an attack probability for each travel route of the plurality of travel routes; organizing the plurality of travel routes into a list, wherein the list is sorted based on attack probability; and displaying the list on an electronic display; Paragraph 0025, In some embodiments, the memory 204 may be a non-transitory computer readable medium. Memory 204 stores instructions, which when executed by the processor, implement the steps of the present invention):
receiving, by a commander through a user interface (UI), course of action (COA) data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0035, In embodiments, the computer system 102 evaluates each route on one or more of the following conditions: distance, time required, attack probability, and/or an escape factor. In embodiments, the attack probability may further be based on a variety of criteria, including, but not limited to, a detectability factor, and a proximity to enemy positions, as well as the confidence level associated with each of the enemy positions; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established; Examiner interprets: “time required” as “timing of the activities”; “air support information and naval support information” as the “entities to perform the activities”; “enemy locations and enemy capabilities” as the “threat data”; and “actionable intelligence” as the “threat mitigation”);
coordinating simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a [score] of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established);
generating a graphical view of the simulation of the COAs including scores associated with each COA (Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown);
implementing a COA of the COAs selected by the commander (Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0065, The significance of disclosed embodiments is that they facilitate more consensus building amongst commanders for decision making as well as immediate actions and/or preparations by other elements within the support sections. This enables the possibility of more effective operations with higher success rates, reduced casualties, and reduced financial costs);
receiving, from multiple applications including an intelligence management service, …, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0034, The computer system 102 may then retrieve additional data from intelligence database 156. The additional data from intelligence database 156 can include, but is not limited to, enemy location, enemy numbers (number of troops, tanks, planes, etc. . . . ), enemy speed and heading, and a confidence level for the intelligence information. As an example, information that has been confirmed by a recent satellite image may be given a high confidence level, whereas information provided by an unreliable informant may be deemed to be at a low confidence level; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include airplanes or tanks. Therefore, based on broadest reasonable interpretation in light of the specification, Mathew discloses a kinetic fires management system since it can receive real-time intelligence information of the location of the airplanes or tanks. Also, Examiner notes that Mathew discloses: an intelligence management system since it can receive real-time intelligence information; and a sustainment management service since it can operate across multiple domains such as air support and naval support);
and providing, by the UI, a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the [score] updated as the COA is implemented (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0059, FIG. 7 shows an example of a virtual range card 700 in accordance with embodiments of the present invention. In such an embodiment, using the camera and geolocation system of the device 200, an annotated virtual range card is created. The virtual range card (VRC) indicates distances to important objects within a scene; Paragraph 0063, FIG. 8 shows a tactical information display 800 in accordance with additional embodiments of the present invention. Tactical information display 800 includes a route list 802, showing a list of possible routes. Tactical information display 800 may further include a virtual range card 804, displaying important information from a particular vantage point. Tactical information display 800 may further include a popup notice 806. Tactical information display 800 may further include a course of action recommendation (COAR) map 808; In this case, the score is updated after receiving real-time battlefield intelligence information. Also, Examiner notes that at least one of the threat mitigation activities may be to provide alternate routes).
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Although Mathew discloses receiving information regarding a state of executing the COA from a kinetic fires management service and a camera management server (e.g., real-time battlefield intelligence including enemy location, image of the scene, etc.), Mathew does not specifically disclose a non-kinetic fires management service, a video sensor management service.
However, Hanneman et al. discloses … a non-kinetic fires management service, a [picture] management service, a kinetic fires management service (Paragraph 0037, In one aspect, inputs/actions include political interactions, military interactions (both kinetic and non-kinetic), monetary exchange and others, as described below; Paragraph 0045, Turning in detail to FIG. 2, Microworld 205 is coupled to plural modules, including cultural model 206, IO model 208, kinetic model 209, non-kinetic model 211, operational conditions 210 and a database 207. The use and affect of these plural modules will now be described; Paragraph 0047, Microworld 205 also interfaces with kinetic model 209 and non-kinetic model 211. Kinetic model 209 provides inputs that are mobile. For example, in a military application, a weapon-target pairing tool provides an input that allows an entity to shoot a specific target and then report the damage. Microworld 205 takes the postulated outcome (i.e., whether the target was destroyed or not) and then evaluate the effect of destroying the target. For example, although the target was destroyed, but if it was a place of worship or was a school, it may have an undesired effect and that is analyzed by Microworld 205; Paragraph 0048, Non-kinetic model 211 provides non-kinetic input. Examples of such input are dropping leaflets, implementing a computer malfunction, deceptively re-routing supplies, or electronic warfare operations such as jamming a specific frequency. For example, a non-kinetic support tool provides a decision to jam a radio tower disabling communication. Microworld 205 evaluates the effect of the radio jamming beyond frequency detection that confirms that a radio tower has been jammed. For example, by jamming a radio tower, the local population does not get traffic related information and causes traffic jams delaying emergency operation. Microworld 205 will evaluate and consider these plural possibilities; Paragraph 0055, FIG. 3 provides an example of using Microworld 205. The operational environment 314 includes an aircraft 301 and a military tank 302 in a military situation. Information about the two vehicles is collected by information module 303. Information about vehicles 301 and 302 is provided to a logictics center 306, command control (CC) 305 and an intelligence-gathering module 304. It is noteworthy that modules 306, 305 and 304 may be computing systems placed in the same or different locations; Paragraph 0056, Command operational picture module (COP) 307 then sends out operational conditions 308 to simulation environment 315. Simulation environment 315 includes the Microworld 205 that is dynamically updated; Paragraph 0057, Microworld 205 receives the operational conditions and provides predicted outcomes/effects 309 based on potential DIME actions 312 and at time 311. As actions occur, the environment changes, thereby causing successive actions to have different effects than they would have previously (with respect to time 311). The predicted outcomes (309) are received by COP 307 that eventually takes action based on the recommendations. This information is then used to monitor and control the behavior of vehicles 301 and 302; Paragraph 0058, The adaptive aspects of the present invention can be used in military and civilian environments. Microworld 205 architecture allows a user to analyze and predict beneficial courses of action that specific entities should take depending on different parameters).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein information regarding a state of executing the COA is received from multiple applications/services of the invention of Mathew to further incorporate other information regarding a state of executing the COA (e.g., non-kinetic information and videos) of the invention of Hanneman et al. because doing so would allow the method to analyze and predict beneficial courses of action that specific entities should take depending on different parameters such as kinetic and non-kinetic inputs (see Hanneman et al., Paragraph 0058). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Although Mathew discloses determining a score of the COAs by an analysis engine, Mathew does not specifically disclose wherein the score is a likelihood of success. Also, although Mathew discloses receiving information regarding a state of executing the COA from multiple applications, the combination of Mathew and Hanneman et al. does not specifically disclose a video sensor management service.
However, Hanson et al. discloses coordinating simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a likelihood of success (LOS) of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0198, For example, and without limitation, a Mission Simulation and Training module 2020 may enable mission plans to be “run virtually” with various scenarios including variations in weather, sea state, and external system encounters. Operators may interject simulated manual control of unmanned vehicles. The Mission Simulation and Training module 2020 may provide a valuable estimate as to the likely success of the planned mission under various scenarios; Paragraph 0200, Also for example, and without limitation, a Mission Execution System 2040 may provide the functions necessary to begin and complete a successful mission of a fleet of unmanned vehicles 100. FIG. 19 illustrates a high level flow diagram of exemplary functions provided by the Mission Execution System modules; Paragraph 0201, Also for example, and without limitation, a Mission Data Processing System 2050 may receive and record mission data transmitted from the unmanned vehicles 100. A majority of missions may be presumed to relate to data gathering for intelligence, surveillance and reconnaissance (ISR) purposes. The Mission Data Processing system 2050 may collect and process large amounts of data, and may extract the most useful information out of the data in near real time. The Mission Data Processing system 2050 may perform complex data pattern processing in addition to raw storage and reporting; Paragraph 0230, The command and control block 3504, which may be under operator direction, or receive autonomous instructions as described above, sends positioning instructions to the well deck positioning controller 3502. Such instructions may include well deck pitch, well deck depth, well deck heading, well deck turn rate or well deck pitch rate, for example. The well deck positioning controller 3502 sends position information back to the command and control block 3504); …
receiving, from multiple applications including an intelligence management service, …, a video sensor management service, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0075, For example, and without limitation, levels of abstraction for asset assignment may include an individual unmanned vehicle being assigned a specific task, an unmanned vehicle sub-group being responsible for a mission sub-goal, and/or a full set of available assets being dedicated to an overall mission goal. Therefore, planning may involve pre-configuring missions for each unmanned vehicle as well as mapping and visualizing groups of unmanned vehicles. “Control,” as used herein, refers to asset tracking, data collection, and mission adjustments accomplished in real-time as execution of a plan unfolds and as a mission evolves. Control, in the context of unmanned vehicle use, may involve selection of deployment modes (for example, and without limitation, air, marine, and submarine) and operational timing (for example and without limitation, active, wait at location, and remain on standby); Paragraph 0101, The present invention may include a sensor system to collect both vehicle 100 functional systems data and also external environmental data. The sensor system may comprise a variable set of sensors of many kinds that collect a wide variety of data from disparate sources, an electronic communication network over which the sensors may send data, and a data processing and routing system for collected sensor data. In one embodiment of the present invention, data representing the condition of components in the on-board environment may be collected by functional sensors such as the following: Global Position System (GPS), electronic compass, accelerometers, roll, pitch, yaw orientation, depth, pressure, temperature, voltage, drive train revolutions per minute (RPM), vibration at multiple locations, vehicle humidity, fuel level, and charge level. External environmental data may be collected by sensors that may include a video camera with computer-controlled articulation, zoom and night vision; electro-optical/infrared imaging and an audio sensor. Optional sensors may include, but are not limited to, radar, sonar, chemical and radiation sensors. External sensors may be mounted on a retractable device rack, as described below. Sensor signals may be connected to a signal multiplexing unit that may provide signal conditioning and routing, and the multiplexing component may be connected to a sensor data processing subsystem that includes a computer software component that may be located in the vehicle's 100 central computer; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include radar. Therefore, based on broadest reasonable interpretation in light of the specification, Hanson et al. discloses a kinetic fires management system since it can receive real-time intelligence information from a radar. Also, Examiner notes that Hanson et al. discloses: an intelligence management system since it can receive real-time intelligence information; a video sensor management service since it can collect environmental data from a video camera; and a sustainment management service since it can operate across multiple domains such as air and sea).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein a score is determined for the different COAs of the invention of Mathew and Hanneman et al. to further incorporate a likelihood of success for the different COAs of the invention of Hanson et al. because doing so would allow the method to provide a valuable estimate as to the likely success of the planned mission under various scenarios (see Hanson et al., Paragraph 0198). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 16, Mathew discloses a system comprising: processing circuitry; a display; a memory coupled to the processing circuitry and the display, the memory including instructions that, when executed by the processing circuitry, cause the processing circuitry to perform operations for mission planning and execution, the operations comprising (Paragraph 0003, In one embodiment, there is provided a computer-implemented method for military planning, comprising: detecting a current geographical position; obtaining a destination geographical position; computing a plurality of travel routes to the destination geographical position; computing an attack probability for each travel route of the plurality of travel routes; organizing the plurality of travel routes into a list, wherein the list is sorted based on attack probability; and displaying the list on an electronic display; Paragraph 0019, FIG. 1 shows a system 100 in accordance with embodiments of the present invention. A tactical information processing computer system 102 has a processor 140, memory 142, and storage 144. Memory 142 includes instructions stored thereon, which when executed by the processor perform steps of the present invention; Paragraph 0027, Device 200 further includes a user interface 208, examples of which include a liquid crystal display (LCD), a plasma display, a light emitting diode (LED) display, an organic LED (OLED) display, or other suitable display technology):
receiving, by a commander through a user interface (UI) of the display, course of action (COA) data regarding multiple COAs, the COA data including activities, timing of the activities, entities to perform the activities, and threat data, the activities including intelligence gathering and threat mitigation activities, the entities including multiple different domains (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0035, In embodiments, the computer system 102 evaluates each route on one or more of the following conditions: distance, time required, attack probability, and/or an escape factor. In embodiments, the attack probability may further be based on a variety of criteria, including, but not limited to, a detectability factor, and a proximity to enemy positions, as well as the confidence level associated with each of the enemy positions; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established; Examiner interprets: “time required” as “timing of the activities”; “air support information and naval support information” as the “entities to perform the activities”; “enemy locations and enemy capabilities” as the “threat data”; and “actionable intelligence” as the “threat mitigation”);
coordinating, by an orchestrator service, simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a [score] of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0065, As can now be appreciated, disclosed embodiments provide improved acquisition and dissemination of tactical information that can be used for supporting the planning, execution, and/or monitoring of military and/or law enforcement operations. In some embodiments machine learning is used to further enhance the analysis of intelligence data. Some embodiments may utilize a supervised learning model. Analyzing and identifying the kinds of combat variables, intelligence sources as well as relevancy to the mission is the critical component that facilitates the commander's course of action (COA). Compilation of combat variables are sourced from subject matter experts (SME)s, DoD institutions, combat instructors, combat operators, commanders with combat experience, and/or historical data. Vast amounts of combat variables, empirical data, historical data, and miscellaneous factors, actionable intelligence and available and known courses of action (COA) are formulated to a hybrid or ensemble formula to produce a logical and mission success oriented “recommended” course of action. Crowd-sourcing streams of intelligence via handheld device along with actionable and real-time battlefield intelligence is a practical way of keeping up to speed in a complex battlefield. SMEs may advise and provide guidance as to what a reasonable and prudent commander would consider to be a judicious threshold for gains/losses sustained during actual operations, which can serve as the litmus or control. Acceptable ranges of gains/loss “milestones” are examined by SMEs, agreed upon and subsequently established);
generating, by the orchestrator service, and providing by the display, a graphical view of the simulation of the COAs including scores associated with each COA (Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown);
implementing a COA of the COAs selected by the commander (Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0065, The significance of disclosed embodiments is that they facilitate more consensus building amongst commanders for decision making as well as immediate actions and/or preparations by other elements within the support sections. This enables the possibility of more effective operations with higher success rates, reduced casualties, and reduced financial costs);
receiving, from multiple applications including an intelligence management service, …, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0034, The computer system 102 may then retrieve additional data from intelligence database 156. The additional data from intelligence database 156 can include, but is not limited to, enemy location, enemy numbers (number of troops, tanks, planes, etc. . . . ), enemy speed and heading, and a confidence level for the intelligence information. As an example, information that has been confirmed by a recent satellite image may be given a high confidence level, whereas information provided by an unreliable informant may be deemed to be at a low confidence level; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include airplanes or tanks. Therefore, based on broadest reasonable interpretation in light of the specification, Mathew discloses a kinetic fires management system since it can receive real-time intelligence information of the location of the airplanes or tanks. Also, Examiner notes that Mathew discloses: an intelligence management system since it can receive real-time intelligence information; and a sustainment management service since it can operate across multiple domains such as air support and naval support);
and providing, by the UI, a graphical view of the state of executing the COA including an overall map of a geographical region in which the COA is implemented, the graphical view including a dynamic location of the threat and threat mitigation activities, and a dynamic view of the [score] updated as the COA is implemented (Paragraph 0002, Historically, data has been handwritten, analyzed and processed into electronic format for greater dissemination, or received directly into the Command Operation Center (COC) for the battlefield or rear echelon commanders to make a decision or Course of Action (COA). This process lags the operational tempo of battle due to slow and lack of means. Real-time battlefield intelligence is often consolidated and various combat factors are weighed together to formulate a COA. Various factors including human error and emotional based decision making may also interfere with courses of action that would most relevantly serve mission accomplishment and success. Acceptable ranges of data and action milestones must be agreed upon in order for the success of the mission as well as an acceptable gains/loss factor; Paragraph 0022, The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0027, Device 200 further includes a user interface 208; Paragraph 0052, FIG. 4 shows a course of action recommendation 400 in accordance with embodiments of the present invention. In embodiments, the course of action recommendation 400 may be rendered on an electronic display such as that of a tablet computer, smartphone, laptop computer, or other suitable computing device. Course of action recommendation 400 includes a route list 402, showing a list of possible routes. In row 404, route 1 is listed, corresponding to the route depicted in FIG. 3B. In row 406, route 2 is listed, corresponding to the route depicted in FIG. 3A. Based on the aforementioned parameters, formulas, and constants, the route of FIG. 3B is ranked higher than the route of FIG. 3A. The user can select a route (e.g. by touching, clicking, or other selection mechanism). The selected route is shown in map display 412. Additional information such as current position 410 and current heading and speed 419 may also be shown; Paragraph 0059, FIG. 7 shows an example of a virtual range card 700 in accordance with embodiments of the present invention. In such an embodiment, using the camera and geolocation system of the device 200, an annotated virtual range card is created. The virtual range card (VRC) indicates distances to important objects within a scene; Paragraph 0063, FIG. 8 shows a tactical information display 800 in accordance with additional embodiments of the present invention. Tactical information display 800 includes a route list 802, showing a list of possible routes. Tactical information display 800 may further include a virtual range card 804, displaying important information from a particular vantage point. Tactical information display 800 may further include a popup notice 806. Tactical information display 800 may further include a course of action recommendation (COAR) map 808; In this case, the score is updated after receiving real-time battlefield intelligence information. Also, Examiner notes that at least one of the threat mitigation activities may be to provide alternate routes).
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Although Mathew discloses receiving information regarding a state of executing the COA from a kinetic fires management service and a camera management server (e.g., real-time battlefield intelligence including enemy location, image of the scene, etc.), Mathew does not specifically disclose a non-kinetic fires management service and a video sensor management service.
However, Hanneman et al. discloses … a non-kinetic fires management service, a [picture] management service, a kinetic fires management service (Paragraph 0037, In one aspect, inputs/actions include political interactions, military interactions (both kinetic and non-kinetic), monetary exchange and others, as described below; Paragraph 0045, Turning in detail to FIG. 2, Microworld 205 is coupled to plural modules, including cultural model 206, IO model 208, kinetic model 209, non-kinetic model 211, operational conditions 210 and a database 207. The use and affect of these plural modules will now be described; Paragraph 0047, Microworld 205 also interfaces with kinetic model 209 and non-kinetic model 211. Kinetic model 209 provides inputs that are mobile. For example, in a military application, a weapon-target pairing tool provides an input that allows an entity to shoot a specific target and then report the damage. Microworld 205 takes the postulated outcome (i.e., whether the target was destroyed or not) and then evaluate the effect of destroying the target. For example, although the target was destroyed, but if it was a place of worship or was a school, it may have an undesired effect and that is analyzed by Microworld 205; Paragraph 0048, Non-kinetic model 211 provides non-kinetic input. Examples of such input are dropping leaflets, implementing a computer malfunction, deceptively re-routing supplies, or electronic warfare operations such as jamming a specific frequency. For example, a non-kinetic support tool provides a decision to jam a radio tower disabling communication. Microworld 205 evaluates the effect of the radio jamming beyond frequency detection that confirms that a radio tower has been jammed. For example, by jamming a radio tower, the local population does not get traffic related information and causes traffic jams delaying emergency operation. Microworld 205 will evaluate and consider these plural possibilities; Paragraph 0055, FIG. 3 provides an example of using Microworld 205. The operational environment 314 includes an aircraft 301 and a military tank 302 in a military situation. Information about the two vehicles is collected by information module 303. Information about vehicles 301 and 302 is provided to a logictics center 306, command control (CC) 305 and an intelligence-gathering module 304. It is noteworthy that modules 306, 305 and 304 may be computing systems placed in the same or different locations; Paragraph 0056, Command operational picture module (COP) 307 then sends out operational conditions 308 to simulation environment 315. Simulation environment 315 includes the Microworld 205 that is dynamically updated; Paragraph 0057, Microworld 205 receives the operational conditions and provides predicted outcomes/effects 309 based on potential DIME actions 312 and at time 311. As actions occur, the environment changes, thereby causing successive actions to have different effects than they would have previously (with respect to time 311). The predicted outcomes (309) are received by COP 307 that eventually takes action based on the recommendations. This information is then used to monitor and control the behavior of vehicles 301 and 302; Paragraph 0058, The adaptive aspects of the present invention can be used in military and civilian environments. Microworld 205 architecture allows a user to analyze and predict beneficial courses of action that specific entities should take depending on different parameters).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein information regarding a state of executing the COA is received from multiple applications/services of the invention of Mathew to further incorporate other information regarding a state of executing the COA (e.g., non-kinetic information and videos) of the invention of Hanneman et al. because doing so would allow the method to analyze and predict beneficial courses of action that specific entities should take depending on different parameters such as kinetic and non-kinetic inputs (see Hanneman et al., Paragraph 0058). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Although Mathew discloses determining a score of the COAs by an analysis engine, Mathew does not specifically disclose wherein the score is a likelihood of success. Also, although Mathew discloses receiving information regarding a state of executing the COA from multiple applications, the combination of Mathew and Hanneman et al. does not specifically disclose a video sensor management service.
However, Hanson et al. discloses coordinating, by an orchestrator service, simulation of performing of the activities by the entities, the simulation including gathering the intelligence data based on visibility and location of intelligence, surveillance, and reconnaissance (ISR) device, determining a likelihood of success (LOS) of the COAs by an analysis engine, and executing models of the entities performing the activities by a command and control engine (Paragraph 0198, For example, and without limitation, a Mission Simulation and Training module 2020 may enable mission plans to be “run virtually” with various scenarios including variations in weather, sea state, and external system encounters. Operators may interject simulated manual control of unmanned vehicles. The Mission Simulation and Training module 2020 may provide a valuable estimate as to the likely success of the planned mission under various scenarios; Paragraph 0200, Also for example, and without limitation, a Mission Execution System 2040 may provide the functions necessary to begin and complete a successful mission of a fleet of unmanned vehicles 100. FIG. 19 illustrates a high level flow diagram of exemplary functions provided by the Mission Execution System modules; Paragraph 0201, Also for example, and without limitation, a Mission Data Processing System 2050 may receive and record mission data transmitted from the unmanned vehicles 100. A majority of missions may be presumed to relate to data gathering for intelligence, surveillance and reconnaissance (ISR) purposes. The Mission Data Processing system 2050 may collect and process large amounts of data, and may extract the most useful information out of the data in near real time. The Mission Data Processing system 2050 may perform complex data pattern processing in addition to raw storage and reporting; Paragraph 0230, The command and control block 3504, which may be under operator direction, or receive autonomous instructions as described above, sends positioning instructions to the well deck positioning controller 3502. Such instructions may include well deck pitch, well deck depth, well deck heading, well deck turn rate or well deck pitch rate, for example. The well deck positioning controller 3502 sends position information back to the command and control block 3504); …
receiving, from multiple applications including an intelligence management service, …, a video sensor management service, a kinetic fires management service, and a sustainment management service that concurrently operate across the multiple domains, information regarding a state of executing the COA (Paragraph 0075, For example, and without limitation, levels of abstraction for asset assignment may include an individual unmanned vehicle being assigned a specific task, an unmanned vehicle sub-group being responsible for a mission sub-goal, and/or a full set of available assets being dedicated to an overall mission goal. Therefore, planning may involve pre-configuring missions for each unmanned vehicle as well as mapping and visualizing groups of unmanned vehicles. “Control,” as used herein, refers to asset tracking, data collection, and mission adjustments accomplished in real-time as execution of a plan unfolds and as a mission evolves. Control, in the context of unmanned vehicle use, may involve selection of deployment modes (for example, and without limitation, air, marine, and submarine) and operational timing (for example and without limitation, active, wait at location, and remain on standby); Paragraph 0101, The present invention may include a sensor system to collect both vehicle 100 functional systems data and also external environmental data. The sensor system may comprise a variable set of sensors of many kinds that collect a wide variety of data from disparate sources, an electronic communication network over which the sensors may send data, and a data processing and routing system for collected sensor data. In one embodiment of the present invention, data representing the condition of components in the on-board environment may be collected by functional sensors such as the following: Global Position System (GPS), electronic compass, accelerometers, roll, pitch, yaw orientation, depth, pressure, temperature, voltage, drive train revolutions per minute (RPM), vibration at multiple locations, vehicle humidity, fuel level, and charge level. External environmental data may be collected by sensors that may include a video camera with computer-controlled articulation, zoom and night vision; electro-optical/infrared imaging and an audio sensor. Optional sensors may include, but are not limited to, radar, sonar, chemical and radiation sensors. External sensors may be mounted on a retractable device rack, as described below. Sensor signals may be connected to a signal multiplexing unit that may provide signal conditioning and routing, and the multiplexing component may be connected to a sensor data processing subsystem that includes a computer software component that may be located in the vehicle's 100 central computer; As stated in Paragraph 0032 of Applicant’s specification, a kinetic threat may include radar. Therefore, based on broadest reasonable interpretation in light of the specification, Hanson et al. discloses a kinetic fires management system since it can receive real-time intelligence information from a radar. Also, Examiner notes that Hanson et al. discloses: an intelligence management system since it can receive real-time intelligence information; a video sensor management service since it can collect environmental data from a video camera; and a sustainment management service since it can operate across multiple domains such as air and sea).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein a score is determined for the different COAs of the invention of Mathew and Hanneman et al. to further incorporate a likelihood of success for the different COAs of the invention of Hanson et al. because doing so would allow the method to provide a valuable estimate as to the likely success of the planned mission under various scenarios (see Hanson et al., Paragraph 0198). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 2-4, 10-12, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Mathew (US 2019/0353492 A1), in view of Hanneman et al. (US 2007/0130098 A1), in further view of Hanson et al. (US 2019/0310639 A1) and Rosolio et al. (US 2021/0295732 A1).
Regarding claims 2, 10, and 17, which are dependent of claims 1, 9, and 16, the combination of Mathew, Hanneman et al., and Hanson et al. discloses all the limitations in claims 1, 9, and 16. Mathew further discloses determining, by a feasibility service communicatively coupled to the orchestration service, entities that are capable of performing each activity, and for each entity that is capable, are in range to perform the activity, can operate in … (Paragraph 0022, Embodiments may further include intelligence database 156. Intelligence database 156 may be implemented using a relational database such as an SQL (Structured Query Language Database), or other suitable database format. The intelligence database can include various information such as enemy locations, enemy troop size, enemy capabilities, weather information, friendly troop locations, air support information, naval support information, and/or other intelligence information; Paragraph 0056, The message can include additional information about the selected target (e.g. building 624), such as a type of operation (e.g. surveillance, demolition, etc.). In the case of demolition (e.g. requesting a building to be bombed by an aircraft or drone), the user may optionally receive a warning notification 610 if the user's current location is within a predetermined distance (e.g. 600 meters) from the selected target. This can provide warning to the user to move to a greater distance from the target for safety purposes; Paragraph 0059, Utilizing automatic ranging from a camera, lidar, radar, or other suitable mechanism, distances to important objects within the scene are identified and rendered on an electronic display. In the example shown, tank 706 is indicated at a distance of 250 meters, tank 708 is indicated at a distance of 120 meters and building 710 is indicated at a distance of 70 meters. Additionally, elevation information may be automatically computed and annotated for one or more scene elements, such as indicated by elevation indication 712; Examiner notes that the air support is near the target);
providing, to the commander and by the UI, for each activity of the activities that has multiple feasible entities, a software control through which the commander selects a feasible entity of the multiple feasible entities; and receiving, by the commander and through the UI, a selection of the feasible entity of the feasible entities for each activity of the activities that has multiple feasible entities (Paragraph 0018, Disclosed embodiments provide systems and methods for aggregating and displaying tactical information. Multiple navigation routes between a starting location and ending location are computed. Each route is evaluated on a variety of criteria, and a ranked list is presented to a user. Additional information, such as rendering a geographically specific notification, display of a virtual range card, and/or information pertaining to an air support operation may also be rendered. Embodiments further enable issuing of air support requests via a tactile user interface. In this way, pertinent information is rendered in a timely manner to battlefield and commanding personnel to enable effective decision-making; Examiner interprets “issuing of air support requests via a tactile user interface” as the “selection of a feasible entity.” As defined in Paragraph 0032 of Applicant’s specification, an entity type may include weapons, people, or support equipment).
Although Mathew discloses determining entities that are capable of performing each activity (Paragraph 0056, aircraft or drone), Mathew does not specifically disclose wherein the determination is based on weather conditions of a geographic region corresponding to the activity and terrain of the geographical region.
However, Rosolio et al. discloses determining, by a feasibility service communicatively coupled to the orchestration service, entities that are capable of performing each activity, and for each entity that is capable, are in range to perform the activity, can operate in weather conditions of a geographic region corresponding to the activity, and can operate in terrain of the geographical region resulting in feasible entities (Paragraph 0032, A simulation image (e.g., a video image) depicting the simulation terrain 140 is presented on display 114 respective of the actual flight pattern of aircraft 100 pursuant to flight control and maneuvering by the operator, such that the real movements of aircraft 100 are reflected in a changing depiction of the simulation environment so as to provide the perception that aircraft 100 is moving within the simulation environment; Paragraph 0037, The simulation image may also depict weapon firings, such as a firing of a surface to air missile (SAM), with indications of successful or unsuccessful target hits. Further displayed information may include flight instructions, navigational parameters, weather and climate data (e.g., instrument meteorological conditions (IMC)), and other important information relating to the simulated environment (and/or the real environment) of the aircraft).
It would have been obvious to one ordinary skill in the art before the effective filing date to modify the method for mission planning and execution, wherein the planning includes to determine entities that are capable of performing each activity of the invention of Mathew to further incorporate wherein the determination is based on weather conditions of a geographic region corresponding to the activity and terrain of the geographical region of the invention of Rosolio et al. because doing so would allow the method to change depiction of the simulation environment based on weather conditions and terrain (see Rosolio et al., Paragraph 0032). Further, the claimed invention is merely a combination of old elements, and in combination each element would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claims 3, 11, and 18, which are dependent of claims 2, 10, and 17, the combination of Mathew, Hanneman et al., Hanson et al., and Rosolio et al. discloses all the limitations in claims 2, 10, and 17. Mathew further discloses receiving, by a user data service communicatively coupled to the orchestration service, possible actions that can be performed by each feasible entity selected for each activity (Paragraph 0018, Disclosed embodiments provide systems and methods for aggregating and displaying tactical information. Multiple navigation routes between a starting location and ending location are computed. Each route is evaluated on a variety of criteria, and a ranked list is presented to a user. Additional information, such as rendering a geographically specific notification, display of a virtual range card, and/or information pertaining to an air support operation may also be rendered. Embodiments further enable issuing of air support requests via a tactile user interface. In this way, pertinent information is rendered in a timely manner to battlefield and commanding personnel to enable effective decision-making; Paragraph 0057, air support. Thus, embodiments can include rendering a map on the electronic display; receiving an area designation on the rendered map; and transmitting the area designation to a remote computing device via a communications network. The transmitted area is then used as coordinates to direct surveillance, bombs, firefighting, medical evacuation, or other air support activities as appropriate).
Regarding claims 4, 12, and 19, which are dependent of claims 2, 10, and 17, the combination of Mathew, Hanneman et al., Hanson et al., and Rosolio et al. discloses all the limitations in claims 2, 10, and 17. Mathew further discloses: receiving, from the commander and through the UI, a selection of machine learning (ML) tools; and coordinating, by the orchestration service, operation of the ML tools in the simulation (Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device; Paragraph 0065, The command level platform may be implemented in a desktop format that provides the capability of receiving data by mobile platforms as well as manual data entry. The significance of disclosed embodiments is that they facilitate more consensus building amongst commanders for decision making as well as immediate actions and/or preparations by other elements within the support sections).
Potential Allowable Subject Matter
Mathew further discloses: coordinating operation of the ML tools in the simulation (Paragraph 0023, In embodiments, the computer system 102 may implement an artificial intelligence scenario simulation process. The artificial intelligence (AI) scenario simulation process may execute on processor 140. The process may perform a combination of empirical analysis and machine learning techniques to provide recommendations to personnel via their client device); and threat data (Paragraph 0022, enemy locations, enemy troop size, enemy capabilities). Hanson et al. further discloses a time that the entity is to take action to perform a corresponding activity of the activities (Paragraph 0075, Control, in the context of unmanned vehicle use, may involve selection of deployment modes (for example, and without limitation, air, marine, and submarine) and operational timing (for example and without limitation, active, wait at location, and remain on standby)). However, the combination of Mathew, Hanneman et al., Hanson et al., and Rosolio et al. does not specifically disclose: wherein the ML tools include an asset optimization service that determines, for each feasible entity of the feasible entities, a time that the entity is to take action to perform a corresponding activity of the activities; wherein the ML tools include a patterns of life service that monitors the geographical region for a new threat; an alert indicating an updated location that is a change in location of the threat; and wherein the graphical view and the results, are all provided on a single pane of glass. Therefore, dependent claims 5-8, 13-15, and 20 have potential allowable subject matter.
.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Herman (US 2006/0271245 A1) – discloses sensing conditions in the engagement scenario. This may entail sensing conditions, such as threat type and range, via the sensors 70 (see FIG. 3). The process 300 also includes the step 304 of comparing the sensed engagement scenario conditions with data derived from simulation. This may entail looking-up corresponding conditions in the tables of FIGS. 6A-6D. The process 300 further includes the step 306 of determining values for suggesting a course of action for the attack vehicle. This may entail selecting one or more values associated with the corresponding conditions in the table(s) (see at least Paragraph 0052, Figure 4, and Figures 7-8).
Manouchehri et al. (US 11,960,283 B1) – discloses the AI measures used by the drones may include convolutional neural networks (CNNs), which are a type of deep learning algorithm commonly used for image and video analysis. Drones equipped with high-resolution cameras and sensors can use CNNs to identify and classify objects in their environment, such as third party vehicles or personnel. This can help the drone to detect and track potential threats, and provide valuable intelligence to alliance entities nearby. In the context of countering cyber or Offensive drone attacks, CNNs can be used to identify and track incoming drones in real-time. This can help personnel to quickly respond to potential threats and deploy defensive measures to neutralize the attack (see at least Column 21, lines 40-59).
Christensen (Christensen, C. and Salmon, J., 2022. Principles for small-unit sUAS tactical deployment from a combat-simulating agent-based model analysis. Expert Systems with Applications, 190, p.116156) – discloses recent increases in the operational and information gathering capabilities of small unmanned aircraft systems (sUAS) have made their deployment with small units of infantry attractive. Determining the potential impacts of sUAS deployment on infantry combat effectiveness and effectively disseminating that information to decision making warfighters is imperative. This work presents an analysis of data generated by a Monte-Carlo simulation of 137,000 unique simulations of a static-defense scenario wherein defending units deploy sUAS in an information, surveillance, and reconnaissance role to aid in detecting, tracking, and targeting attacking units with indirect fires. The relationships between the number of UAVs deployed, the patrol method for those UAVs, and 40 combat effectiveness metrics are explored using a correlation matrix and other graphical methods. A set of eight principles for effective sUAs deployment in the aforementioned scenario are distilled from the simulation data and presented for further testing and validation (see at least Abstract).
Grossman (CN 108140057 B) – discloses this virtual network participant both real and simulated or "army" avatar makes network defense to the scene simulation and virtual reality environment for participation and cooperation. by simulating multiple course of action (COA), influence of defensive strategy, action and incorporated into the information sharing operation understanding and decision-making process in the virtual environment for enhanced visualization support more completely and quickly to enable such a real-time collaboration (see at least Description).
Mittal (Mittal, V. and Davidson, A., 2020. Combining wargaming with modeling and simulation to project future military technology requirements. IEEE Transactions on Engineering Management, 68(4), pp.1195-1207)) - Wargaming is typically done as part of the Military decision making process, which generates, analyzes, and compares different courses of action before finalizing a plan [24]. During the wargame, the staff officers break up each course of action into phases. After each phase, the intelligence officer, role-playing as the enemy, discusses what the enemy would do to react to that phase. This reaction must then be accounted for every subsequent phase, until the mission reaches an end-state. This process is repeated for each course of action to identify the one with the highest likelihood of success (see at least Page 1198, IV. Military Wargaming).
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/MARJORIE PUJOLS-CRUZ/Examiner, Art Unit 3624
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