DETAILED ACTION
This office action is responsive to the Amendments/Request for reconsideration filed on 12/03/2025 after Non-Final filed 09/16/2025. The application contains claims 1-20, all examined and rejected.
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 .
Response to Amendment
It is acknowledged that claims 1, 14 and 17 are amended.
Response to Arguments
Applicant’s arguments, see Pg. 7, filed 12/03/2025, with respect to amended claims 1, 14 and 17, as not being directed to an abstract idea have been fully considered and are persuasive. The rejection of 1-20 under 35 USC 101 has been withdrawn.
Applicant’s arguments with respect to claim(s) 1-20 being rejected under 35 USC 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 3, 4, 5, 7, 8, 13, 14, 15, 17, 18, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over JOKIOINEN (WO 2017129863 A1) in view of Zhao et al. (“Ontology-Based Driving Decision Making: A Feasibility Study at Uncontrolled Intersections”, 2017) further in view of Xu et al. (CN 107870621 A).
Regarding claim 1, JOKIOINEN discloses:
a computer-implemented method of controlling an aquatic vessel, at least by (Pg. 15 line 10 “autonomous operation for a vessel”)
the method comprising: receiving input data comprising a plurality of observations from a respective plurality of sensors associated with the aquatic vessel, at least by (Pg. 15 lines 25-37, which describe monitoring vessel surroundings, objects and obstacles (e.g. a plurality of observations) by receiving information from via multiple sensor(s) of the vessel “radar devices, image capture devices, vibration capture devices and/or audio capture devices of the vessel”)
populating a graph database with the plurality of observations of the input data, wherein the graph database is based on a formal ontology that defines concepts and relationships relating to the plurality of sensors, at least by (Pg. 16 lines 1-20, describes forming a route plan for the vessel based on obstacle data (e.g. plurality of observations of the input data) and generated route plan by utilizing at least one graph search (Pg. 15 lines 15-16), which describes the use of a graph)
and performing a query on the graph database to generate information comprising a control signal configured to control at least by (Pg. 16 lines 1-20, describes forming a route plan for the vessel based on obstacle data (e.g. plurality of observations of the input data) and generated route plan by utilizing at least one graph search (Pg. 15 lines 15-16) to avoid collision, “if any obstacles require a change in any of current route parameters of the vessel. If change(s) are required, the current route parameters of the vessel are changed accordingly, step 412. The route parameters of the vessel may comprise route offset and/or speed of the vessel. At step 414, routing instructions are generated. The generation of the routing instructions may comprise generating the routing instructions for use by a control computer of the vessel (e.g. a control signal)”, which describes querying a graph to generate a route plan to control the vessel according to the route plan (e.g. control signal), (in one interpretation) by controlling the vessel, controlling an engine, a propeller, and/or a warning device of the aquatic vessel would be incorporated.)
But JOKIOINEN fails to specifically describe: (a)populating a graph database with the plurality of observations of the input data, wherein the graph database is based on a formal ontology that defines concepts and relationships relating to the plurality of sensors; and (b) obtain a fix of the aquatic vessel using a Global Positioning System (GPS) device
However, Zhao describes the above limitation (a) at least by (Sec. 1 Paragraph 2 and Sec. 4, #1. “sensor data are converted into RDF stream data format with the ontology” where the ontology is further describes as “consists of concepts (classes) and the relationships (properties) among them”. Zhao also describes the above limitation (b) at least by (Sec. 4.1, “geo:lat and geo:long to represent the latitude and longitude information from the GPS sensor”
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
Also, JOKIOINEN and Zhao fails to specifically describe: cause the aquatic vessel to rise or dive, cause the aquatic vessel to maintain a minimum distance from a vessel or an object detected by at least one of the sensors.
However, Xu describes the above limitation at least by (Claims 4-6, which describes threshold hold value related to distance from different locations of the vessel to an obstacle that when exceeded, collision avoidance action is triggered that adjusts the vessel vertically (rise or dive) to maintain a minimum distance between the vessel and the obstacle.
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN and Zhao with Xu ability to control a vessel autonomously in aquatic environments by improving the accuracy of the obstacle recognition (Xu, abstract).
As per claim 2, claim 1 is incorporated and JOKIOINEN fails to describe:
wherein performing the query comprises performing a plurality of queries on the graph database and generating the information based on a result of a final query of the plurality of queries
However, Zhao the above limitation at least by (Sec 4.2 which describes performing multiple SPARQL queries on the knowledge base (e.g. graph database) and forming “decision result inferred using the SWRL rule reasoner” (e.g. generating the information based on a result of a final query of the plurality of queries))
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 3, claim 1 is incorporated and JOKIOINEN fails to describe:
wherein the formal ontology is used to produce a database schema of the graph database
However, Zhao the above limitation at least by (Sec. 3, “description of the knowledge base using Vocabulary of Interlinked Datasets (VoID) and some of the statistical information are described in Table 1. VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets”))
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 4, claim 3 is incorporated and JOKIOINEN fails to describe:
wherein the database schema is produced by generating a knowledge graph structure based on the formal ontology, and wherein the formal ontology is encoded in Resource Description Format (RDF)
However, Zhao the above limitation at least by (Sec. 3, “description of the knowledge base using Vocabulary of Interlinked Datasets (VoID) and some of the statistical information are described in Table 1. VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets”))
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 5, claim 1 is incorporated and JOKIOINEN fails to describe:
wherein populating the graph database comprises adding a plurality of nodes containing the respective plurality of observations to the graph database
However, Zhao the above limitation at least by (Sec. 1 Paragraph 2 and Sec. 4, #1. “sensor data are converted into RDF stream data format with the ontology” where the ontology is further describes as “consists of concepts (classes) and the relationships (properties) among them… An instance is described by a collection of RDF triples in the form of <subject, property, object>, where property is also called predicate” as such the added nodes are the concepts and/or subject and object).
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 7, claim 4 is incorporated and JOKIOINEN fails to describe:
wherein populating the graph database comprises converting the input data to RDF
However, Zhao the above limitation at least by (Sec. 1 Paragraph 2 and Sec. 4, #1. “sensor data are converted into RDF stream data format with the ontology” where the ontology is further describes as “consists of concepts (classes) and the relationships (properties) among them… An instance is described by a collection of RDF triples in the form of <subject, property, object>, where property is also called predicate” as such the added nodes are the concepts and/or subject and object).
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 8, claim 7 is incorporated and JOKIOINEN fails to describe:
wherein converting the input data comprises adjusting at least part of a data structure of the input data to match at least part of a data structure of the graph database based on the formal ontology,
However, Zhao the above limitation at least by (Sec. 1 Paragraph 2 and Sec. 4, #1. “sensor data are converted into RDF stream data format with the ontology”)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion).
As per claim 13, claim 1 is incorporated and JOKIOINEN further describes:
wherein a result of the query performed on the graph database is used to determine a situation of the aquatic vessel, and the method further comprises outputting the information configured to control the aquatic vessel, the information configured to control the aquatic vessel comprising a signal for directly or indirectly controlling the aquatic vessel in response to the situation, at least by (see Pg. 8 lines 4-8, discloses collision avoidance instructions provided to the control computer of the vessel).
As per claim 15, claim 14 is incorporated and JOKIOINEN further describes:
An aquatic vessel control system comprising the computer program product according to claim 14, and at least one processor configured to execute the instructions, at least by (see Pg. 8 lines 4-8, discloses collision avoidance instructions provided to the control computer of the vessel).
Claim(s) 14, 17, 18, 19 recite equivalent claim limitations as claim(s) 1, 2 and 4 above, except that they set forth the claimed invention as a computer program product including one or more non- transitory computer readable medium, as such they are rejected for the same reasons as applied hereinabove.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over JOKIOINEN, Zhao and Xu further in view of Slepian et al. (US 20180211730 A1).
As per claim 6, claim 5 is incorporated and JOKIOINEN fails to describe:
wherein receiving the input data comprises receiving a data stream comprising the input data, and wherein populating the graph database comprises periodically populating the graph database with the observations of the input data,
However, Zhao the above limitation at least by (Sec. 1 Paragraph 2 and Sec. 4, #1. “sensor data are converted into RDF stream data format with the ontology” where the ontology is further describes as “consists of concepts (classes) and the relationships (properties) among them”.
Furthermore Slepian, discloses: periodically populating the graph database, at least by (paragraph [0096] “analytic engine capable of receiving and processing the … data to … periodically update the knowledgebase… comprising at least one sensor”)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN with Zhao’s ontology-based knowledge base to improve the decision-making system to deal with more complicated obstacles (Zhao, Sec. 6 Conclusion), and also Slepian abilty to periodically update the knowledgebase to improve the accuracy of the system (Slepian, Para. 0080).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over JOKIOINEN, Zhao and Xu further in view of Cardasis et al. (US 20220414613 A1).
As per claim 9, claim 1 is incorporated and JOKIOINEN further describes:
wherein the ontology is based on a Sensor, Observations, Sample and Actuator (SOSA) framework and further includes at least one additional class not included in the SOSA framework, at least by (Sec. 4.1 describes ontology based on Subject, Property, Object, Timestamp, but does not specifically describe SOSA.)
However, Cardasis et al. (US 20220414613 A1) teaches the above limitations at least by (paragraph [0012, 0067], “Many ontology frameworks are available for adaptation and use with the present teachings. For example, the “Sensor, Observation, Sample, and Actuator” (SOSA) ontologies have been developed by the World Wide Web Consortium (W3C) to provide flexible but coherent perspectives for representing the entities, relations, and activities involved in sensing, sampling and actuation.”)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN, Zhao and Xu with Cardasis the ability to provide flexible but coherent perspectives for representing the entities, relations, and activities involved in sensing, sampling and actuation).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over JOKIOINEN, Zhao, Xu and Cardasis further in view of Baughman (US 12093293 B2).
As per claim 10, claim 9 is incorporated and JOKIOINEN, Zhao, Xu and Cardasis fails to describes:
wherein the at least one additional class comprises one or more classes representing uncertainty of the observations
However, Baughman teaches the above limitations at least by (col. 8 lines 43-65, which describes confidence level related to the sensor data feeds associated concepts (e.g. one or more classes) where the confidence level represents uncertainty of the observations)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN, Zhao, Xu and Cardasis with the ability to determine a confidence level associated with the detected correlations provided by Baughman to assure that the ontology adequately represent high correlated concepts (Baughman, col. 9 lines 1-3).
Claim(s) 11, 12, 16 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over JOKIOINEN, Zhao and Xu and Massarella (US 20160140153 A1).
As per claim 11, claim 1 is incorporated and JOKIOINEN, Zhao and Xu fails to describes:
further comprising building a time tree for the graph database that splits the observations into pre-determined periods of time, at least by (Pg. 3 Para. 2, where time class provides the continuous time of the observed behavior, but fails to specifically describe time tree for the graph database that splits the observations into pre-determined periods of time)
However, Massarella teaches the above limitations at least by (at least by (paragraph [0069-0070] which describes a time tree index, with a set of time tree nodes representing a particular time period among the series of time pointing to corresponding data record that includes measured data, “time tree branch nodes T.sub.2 . . . T.sub.m−1 and time tree leaf nodes T.sub.M. Each time tree node T.sub.m corresponds to a time period such as, for example, a year, a day, an hour, a minute, a second, a milliseconds, a microsecond, a nanosecond, a picosecond or ranges thereof” describes time tree for the graph database that splits the observations into pre-determined periods of time)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN, Zhao and Xu with Massarella time tree index to improve data access efficiency (Massarella, para. 0183).
As per claim 12, claim 11 is incorporated and JOKIOINEN, Zhao and Xu fails to describes:
wherein a timestamp included in the input data for each said observation is used to generate a new branch for each observation in the time tree,
However, Massarella (US 20160140153 A1) teaches the above limitations at least by (at least by (paragraph [0069-0070] which describes a time tree index, with a set of time tree nodes representing a particular time period among the series of time pointing to corresponding data record that includes measured data, “time tree branch nodes T.sub.2 . . . T.sub.m−1 and time tree leaf nodes T.sub.M. Each time tree node T.sub.m corresponds to a time period such as, for example, a year, a day, an hour, a minute, a second, a milliseconds, a microsecond, a nanosecond, a picosecond or ranges thereof” describes time tree for the graph database that splits the observations into pre-determined periods of time)
Therefore, before the effective filing date of the invention it would have been obvious to one of ordinary skill in the art to modify JOKIOINEN, Zhao and Xu with Massarella time tree index to improve data access efficiency (Massarella, para. 0183).
Claim(s) 16 and 20 recite equivalent claim limitations as claim(s) 11 above, except that they set forth the claimed invention as a computer program product including one or more non- transitory computer readable medium, as such they are rejected for the same reasons as applied hereinabove.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
HOMOCEANU (US 20200166947 A1), Abstract.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/DENNIS TRUONG/Primary Examiner, Art Unit 2152 2/11/2026