DETAILED ACTION
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 .
Priority
The present application, filed 19 March 2025, is a continuation of U.S. Patent App. No. 17/972,799, filed 25 October 2022, which is a continuation of U.S. Patent App. No. 16/836,416, filed 31 March 2020.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 19 March 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-16 and 18-20 of U.S. Patent No. 12,281,902 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because the present claims would be obvious in view of the reference application. See the table below for further details, wherein the differences between the present application and the reference patent are bolded.
Present Application
U.S. Patent No. 12,281,902
1. A system, comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
obtaining, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility;
generating, based on the 3D position data, a plurality of traces of movement of the plurality of mobile devices operating within the facility;
comparing the plurality of traces of movement of the plurality of mobile devices with a map of the facility to obtain a comparison; and
identifying, based on the comparing, a hidden room in the facility.
1. A system, comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
obtaining position data of a plurality of mobile devices operating within a predetermined area;
generating a plurality of traces of movement of the plurality of mobile devices operating within the predetermined area;
comparing the plurality of traces of movement of the plurality of mobile devices with a map of the predetermined area to obtain a comparison; and
identifying a subspace of the predetermined area according to the comparison, wherein the identifying the subspace comprises generating a graphical representation of the predetermined area, generating a graphical representation of the plurality of traces of movement of the plurality of mobile devices within the predetermined area to obtain a plurality of tracks, and combining the graphical representation of the predetermined area and the plurality of tracks to obtain a combined graphical representation;
wherein the predetermined area comprises a building and wherein the subspace comprises a hidden room in the building.
2. The system of claim 1, further comprising: determining elevation data of the plurality of mobile devices according to the barometric pressure readings, wherein the generating the plurality of traces of movement is based on the 3D position data and the elevation data.
2. The system of claim 1, further comprising: obtaining ambient barometric pressure data from the plurality of mobile devices operating within the predetermined area, determining elevation data of the plurality of mobile devices according to the ambient barometric pressure data, wherein the generating the plurality of traces of movement is based on the position data and the elevation data.
3. The system of claim 2, wherein the determining the elevation data further comprises: comparing the barometric pressure readings to a reference barometric pressure value to obtain barometric pressure differential data, wherein the determining the elevation data is based on the barometric pressure differential data.
3. The system of claim 2, wherein the determining the elevation data further comprises: comparing the ambient barometric pressure data to a reference barometric pressure value to obtain barometric pressure differential data, wherein the determining the elevation data is based on the barometric pressure differential data.
4. The system of claim 1, further comprising: identifying a subspace of the facility that lacks traces of movement of the plurality of mobile devices.
4. The system of claim 1, further comprising: identifying a subspace of the predetermined area lacks traces of movement of the plurality of mobile devices.
5. The system of claim 4, wherein the identifying the subspace of the facility further comprises identifying an undefined subspace of the facility responsive to the map of the facility lacking a defined feature corresponding to the subspace.
5. The system of claim 4, wherein the identifying the subspace of the predetermined area further comprises identifying an undefined subspace of the predetermined area responsive to the map of the predetermined area lacking a defined feature corresponding to the subspace.
6. The system of claim 1, wherein the obtaining the 3D position data of the plurality of mobile devices operating within the facility comprises: receiving the 3D position data from the plurality of mobile devices operating within the facility.
6. The system of claim 1, wherein the obtaining the position data of the plurality of mobile devices operating within the predetermined area comprises: obtaining 3D position data of the plurality of mobile devices operating within the predetermined area.
7. The system of claim 1, wherein the identifying the hidden room further comprises: determining a subspace of the facility that lacks any intersection with the plurality of traces of movement of the plurality of mobile devices within the facility;
comparing the subspace to the map of the facility; and
identifying an undefined area responsive to the map of the facility lacking a defined feature corresponding to the subspace.
7. The system of claim 6, wherein the identifying the subspace further comprise: determining the subspace of the predetermined area lacks any intersection with the graphical representation of the plurality of traces of movement of the plurality of mobile devices within the predetermined area;
comparing the subspace to the map of the predetermined area; and
identifying an undefined area responsive to the map of the predetermined area lacking a defined feature corresponding to the subspace.
8. The system of claim 1, wherein the operations further comprise:
determining an identity of a mobile device of the plurality of mobile devices, wherein the mobile device is distinguishable from other mobile devices of the plurality of mobile devices according to the identity; and
storing a historical record of positions of the mobile device of the plurality of mobile devices operating within the facility.
8. The system of claim 1, wherein the operations further comprise:
determining an identity of a mobile device of the plurality of mobile devices, wherein the mobile device is distinguishable from other mobile devices of the plurality of mobile devices according to the identity; and
storing a historical record of positions of the mobile device of the plurality of mobile devices operating within the predetermined area.
9. The system of claim 8, wherein individual tracks of a plurality of tracks of the plurality of mobile devices operating within the facility are distinguishable according to identities of the plurality of mobile devices.
9. The system of claim 8, wherein individual tracks of a plurality of tracks of the plurality of mobile devices operating within the predetermined area are distinguishable according to identities of the plurality of mobile devices.
10. The system of claim 9, wherein the operations further comprise:
detecting a request for authorization, wherein authorization permits access to a subspace of the facility;
associating the mobile device with the request for authorization; and
evaluating the request for authorization according to an identity of the mobile device to obtain an evaluation result, wherein authorization is granted or denied responsive to the evaluation result.
10. The system of claim 9, wherein the operations further comprise:
detecting a request for authorization, wherein authorization permits access to a subspace of the predetermined area;
associating the mobile device with the request for authorization; and
evaluating the request for authorization according to an identity of the mobile device to obtain an evaluation result, wherein authorization is granted or denied responsive to the evaluation result.
11. The system of claim 10, wherein the operations further comprise:
identifying an identity of an authorized mobile device according to the request for authorization;
comparing the identity of the mobile device to the identity of an authorized mobile device to obtain an identity comparison; and
initiating an alarm signal responsive to the identity comparison indicating a mismatch.
11. The system of claim 10, wherein the operations further comprise:
identifying an identity of an authorized mobile device according to the request for authorization;
comparing the identity of the mobile device to the identity of an authorized mobile device to obtain an identity comparison; and
initiating an alarm signal responsive to the identity comparison indicating a mismatch.
12. The system of claim 1, wherein the obtaining the 3D position data and the generating the plurality of traces of movement are repeated periodically.
12. The system of claim 1, wherein the obtaining the position data and the generating the plurality of traces of movement are repeated periodically.
13. The system of claim 1, wherein the 3D position data comprises geolocation coordinates.
13. The system of claim 1, wherein the position data comprises geolocation coordinates.
14. A method, comprising:
obtaining, by a processing system including a processor, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility;
generating, by the processing system and based on the 3D position data, a graphical representation of patterns of movement of the plurality of mobile devices operating within the facility;
generating, by the processing system, a graphical representation of the facility;
comparing, by the processing system, the graphical representation of patterns of movement of the plurality of mobile devices with the graphical representation of the facility to obtain a comparison; and
identifying, by the processing system, a hidden room in the facility.
14. A method, comprising:
obtaining, by a processing system including a processor, position data of a plurality of mobile devices operating within a facility;
generating, by the processing system and based on the position data, a graphical representation of patterns of movement of the plurality of mobile devices operating within the facility;
generating, by the processing system, a graphical representation of the facility;
comparing, by the processing system, the graphical representation of patterns of movement of the plurality of mobile devices with the graphical representation of the facility to obtain a comparison; and
identifying, by the processing system, a feature of the facility based on the comparison, wherein the feature comprises a hidden room in the facility.
15. The method of claim 14, further comprising:
comparing, by the processing system, the barometric pressure readings to a reference barometric pressure reading to obtain barometric pressure differences; and determining, by the processing system, height values according to the barometric pressure differences, wherein the graphical representation of patterns of movement is based on the 3D position data and the height values.
15. The method of claim 14, further comprising: obtaining, by the processing system, barometric pressure readings corresponding to the plurality of mobile devices operating within the facility;
comparing, by the processing system, the barometric pressure readings to a reference barometric pressure reading to obtain barometric pressure differences; and determining, by the processing system, height values according to the barometric pressure differences, wherein the graphical representation of patterns of movement is based on the position data and the height values.
16. The method of claim 15, further comprising: combining, by the processing system, the graphical representation of patterns of movement of the plurality of mobile devices within the facility with patterns of movement of other mobile devices within the facility to obtain a cumulative record of movement.
16. The method of claim 15, further comprising: combining, by the processing system, the graphical representation of patterns of movement of the plurality of mobile devices within the facility with patterns of movement of other mobile devices within the facility to obtain a cumulative record of movement.
17. The method of claim 16, wherein the 3D position data comprises geolocation coordinates.
13. The system of claim 1, wherein the position data comprises geolocation coordinates.
18. A non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:
obtaining, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a building;
generating a graphical representation of a plurality of traces of movement of the plurality of mobile devices operating within the building;
generating a graphical representation of the building;
comparing the graphical representation of the plurality of traces of movement of the plurality of mobile devices with the graphical representation of the building to obtain a comparison; and
identifying, based on the comparison, a hidden room in the building.
18. A non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations, the operations comprising:
obtaining position data of a plurality of mobile devices operating within a building;
generating a graphical representation of a plurality of traces of movement of the plurality of mobile devices operating within the building;
generating a graphical representation of the building;
comparing the graphical representation of the plurality of traces of movement of the plurality of mobile devices with the graphical representation of the building to obtain a comparison; and
identifying a feature of the building according to the comparison, wherein the feature comprises a hidden room.
19. The non-transitory, machine-readable medium of claim 18, further comprising: identifying that a subspace of the building lacks traces of movement of the plurality of mobile devices, wherein the identifying the hidden room comprises identifying an undefined space of the building.
19. The non-transitory, machine-readable medium of claim 18, further comprising: identifying that a subspace of the building lacks traces of movement of the plurality of mobile devices, wherein the identifying the feature comprises identifying an undefined space of the building.
20. The non-transitory, machine-readable medium of claim 19, wherein the 3D position data comprises geolocation coordinates.
20. The non-transitory, machine-readable medium of claim 19, wherein the position data comprises geolocation coordinates.
The examiner notes that the primary difference between claim sets is the inclusion of wherein the “position data” is “3D position data.” The examiner notes, however, that this difference would be obvious in view of the reference patent, considering that claim 6 of the reference patent discloses wherein the position data is 3D position data.
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 1-13 are rejected under 35 U.S.C. 101 because they are directed towards an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-13 are directed towards a “system” (i.e., a machine). Therefore, claims 1-13 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite a mental process (emphasized below) and will be used as the representative claim for the remainder of the 35 U.S.C. 101 rejection. Claim 1 recites:
A system, comprising:
A processing system including a processor; and
A memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
Obtaining, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility;
Generating, based on the 3D position data, a plurality of traces of movement of the plurality of mobile devices operating within the facility;
Comparing the plurality of traces of movement of the plurality of mobile devices with a map of the facility to obtain a comparison; and
Identifying, based on the comparing, a hidden room in the facility.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process”, because under its broadest reasonable interpretation, the claim covers actions capable of being performed in the human mind. Specifically, the examiner asserts that “generating a plurality of traces,” amounts to mentally plotting positions, while “comparing the plurality of traces,” and “identifying … a hidden room,” amount to making a mental comparison and determination, respectively. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra-solution activity, or generally linking the use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application”.
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations”, while the bolded portions continue to represent the “abstract idea”):
A system, comprising:
A processing system including a processor; and
A memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
Obtaining, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility;
Generating, based on the 3D position data, a plurality of traces of movement of the plurality of mobile devices operating within the facility;
Comparing the plurality of traces of movement of the plurality of mobile devices with a map of the facility to obtain a comparison; and
Identifying, based on the comparing, a hidden room in the facility.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the limitations of “a processing system,” and “a memory…,” the examiner asserts that these limitations amount to an apply-it level integration of a generic “processor” and “memory” in performing the mental process indicated above.
Regarding the limitation of “obtaining … 3d position data…,” the examiner asserts that this limitation amounts to insignificant, extra-solution activity in the form of mere data gathering.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitations do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above, with respect to determining that the claim does not integrate the abstract idea into a practical application. Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, and conventional activity in the field. The additional limitations of “obtaining … 3d position data…,” are well-understood, routine, and conventional activities because MPEP § 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Hence, independent claim 1 is not patent eligible.
Regarding dependent claim 2, dependent claim 2 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 2 merely recites a further mental process in the form of “determining elevation data,” which the examiner asserts could reasonably be performed in the human mind. Hence, dependent claim 2 is not patent eligible.
Regarding dependent claim 3, dependent claim 3 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 3 merely recites a further mental process in the form of “comparing barometric pressure readings to a reference barometric pressure value,” which the examiner asserts could reasonably be performed in the human mind. Hence, dependent claim 3 is not patent eligible.
Regarding dependent claim 4, dependent claim 4 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 4 merely recites a further mental process in the form of “identifying a subspace of the facility,” which the examiner asserts could reasonably be performed in the human mind. Hence, dependent claim 4 is not patent eligible.
Regarding dependent claim 5, dependent claim 5 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 5 merely describes the mental process of “identifying a subspace of the facility” of claim 4. Hence, dependent claim 5 is not patent eligible.
Regarding dependent claim 6, dependent claim 6 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 6 merely recites further insignificant, extra-solution activity in the form of “receiving the 3D position data from the plurality of mobile devices,” which, as indicated above, is well-understood, routine, and conventional activity. Hence, dependent claim 6 is not patent eligible.
Regarding dependent claim 7, dependent claim 7 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 7 merely recites further mental processes in the form of “determining a subspace…,” “comparing the subspace to the map of the facility,” and “identifying an undefined area,” all of which can reasonably be performed in the human mind. Hence, dependent claim 7 is not patent eligible.
Regarding dependent claim 8, dependent claim 8 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 8 merely recites a further mental process in the form of “determining an identity of a mobile device,” and further recites additional insignificant, extra-solution activity in the form of “storing a historical record of positions…,” which has been shown to be well-understood, routine, and conventional activity when claimed in a generic manner. Hence, dependent claim 8 is not patent eligible.
Regarding dependent claim 9, dependent claim 9 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 9 merely provides a description of the mobile device tracks, which does not bring the claim into patent eligibility. Hence, dependent claim 9 is not patent eligible.
Regarding dependent claim 10, dependent claim 10 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 10 merely recites further insignificant, extra-solution activity in the form of “detecting a request for authorization,” which the examiner asserts amounts to mere data gathering/transmission, and further recites additional mental processes in the form of “associating the mobile device,” and “evaluation the request,” both of which could reasonably be performed in the human mind. Hence, dependent claim 10 is not patent eligible.
Regarding dependent claim 11, dependent claim 11 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 11 merely recites additional mental processes in the forms of “identifying an identity,” and “comparing the identity,” and recites further insignificant, extra-solution activity in the form of “initiating an alarm signal,” which the examiner asserts amounts to merely sending an alarm signal, which amounts to mere data transmission. Hence, dependent claim 11 is not patent eligible.
Regarding dependent claim 12, dependent claim 12 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 12 merely recites that the insignificant, extra-solution activity of “obtaining the 3d position data” is performed periodically, which is insufficient to bring the claims into eligibility. Hence, dependent claim 12 is not patent eligible.
Regarding dependent claim 13, dependent claim 13 does not include additional limitations that would cause the claim to be patent eligible. Specifically, dependent claim 13 merely describes the kind of data being acquired. Hence, dependent claim 13 is not patent eligible.
The examiner notes that claims 14-20 are patent eligible, because the limitation of “generating … a graphical representation of patterns of movement of the plurality of mobile devices” is not capable of being performed in the human mind.
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.
Claims 1-7 and 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Vande Velde (US 20130297198 A1), hereafter Vande Velde, in view of Raman (US 20150119082 A1), hereafter Raman.
Regarding claim 1, Vande Velde discloses a system, comprising:
A processing system including a processor (0041, an apparatus for generating map data representing the inside of a building and/or an enclosed and/or covered area, comprising a processor (154, 230) operable to acquire location related data that has been generated by a plurality of mobile devices (200) using at least one non-GPS navigation sensor (205-220) and at least one GPS sensor (225), the apparatus being operable to aggregate the location related data; and determine the map data from the aggregated location related data.); and
A memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations (0042-0043, a computer program element comprising computer program code means to make a computer execute the method as set forth above in relation to the first or third aspects of the invention or to implement the apparatus as set forth in the second or fourth aspects of invention. The computer program element may be embodied on a computer readable medium), the operations comprising:
Obtaining, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility (0059, the mobile device 200 may be equipped or equipable with one or more sensors such as pedometers 205, compasses 210, pressure sensors 215 such as barometers, gyroscopes 220, inclinometers and the like. The mobile device 200 is also equipped or equipable with a GPS sensor 225 for use when sufficient signal 108 from GPS satellites 102 is available. The GPS 225 and/or non-GPS 205, 210, 215, 220 sensors may optionally be built into the mobile device 200 or may be connected to the mobile device 200, for example as part of a retrofit or as a plug-in or accessory. The GPS sensor 225 and non-GPS sensors 205, 210, 215, 220 are operably coupled to a processor 230. The mobile device 200 further comprises communications apparatus 235, which includes a transmitter 166 and receiver 168 for communicating with other devices and/or a server 150. The mobile device 200 also comprises a memory 240 for storing navigational data derived from the non-GPS sensors or GPS location data derived from the GPS sensor 225, estimated location data derived from the navigational data and/or aggregated routes derived from the estimated location data and any data required in order to determine the estimated location data from the navigational data, such as an average user stride length);
Generating, based on the 3D position data, a plurality of traces of movement of the plurality of mobile devices operating within the facility (0086, The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7. The aggregated route trace 705 from the mobile device 200 is then, for example, communicated to the server 150 via the communication channel 152, whereupon it may be further aggregated with route traces or aggregated route traces 705 for the particular building that have been determined and supplied by other mobile devices 200.);
Comparing the plurality of traces of movement of the plurality of mobile devices with a map of the facility to obtain a comparison (0028, The method may comprise comparing the GPS and/or non-GPS location data to predetermined map data, which may comprise building footprint data, and determining whether the location data is from internally or externally of the building and/or an enclosed and/or covered area. The method may comprise separating data representing the interior of the building and/or enclosed and/or covered area from data representing the exterior of the building and/or an enclosed and/or covered area. The method may comprise processing the interior data separately from the exterior data. The exterior data may comprise the GPS data. The Interior data may comprise the location related data derived from the non-GPS sensors.); and
Identifying, based on the comparing, a subspace in the facility (0089, Patterns in the estimated location data and/or the navigation data obtained from one or more of the non-GPS sensors and/or GPS location data may be analysed to identify features, for example, by using statistical analysis and/or by comparison with predetermined signatures or typical patters and/or by comparison with templates or profiles or the like. For example, as detailed above, up/down ramps and stairs may be determined by using pressure data and/or identifying tight turns using compass data.).
Vande Velde fails to explicitly disclose, however, wherein the subspace is a hidden room.
Raman, however, in an analogous field of endeavor, does teach wherein the subspace is a hidden room (0051, For example, in step 503, the positioning platform 105 predicts one or more unused spaces within the physical space based on the crowd-sourcing, the location data, the other location data, or a combination thereof. More specifically, the positioning platform 105 applies predictive models to score and classified sensor data that meet conditions for classification as a feature such as a whether an area of a physical space is unused. Unused, for instance, refers to areas or regions (e.g., represented by Voronoi polytopes) of the interior volume of the physical space that have little or no location traces. These unused areas can represent obstructions or physical features that obstruct or prevent user movement.).
Vande Velde and Raman are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the unused room determination of Raman in order to provide a means of classifying a space on a generated map. The motivation to combine is to allow the system to identify spaces that may not be apparent on a map of the building.
Regarding claim 2, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde teaches it further comprising:
Determining elevation data of the plurality of mobile devices according to the barometric pressure readings (0078, A pressure sensor such as a barometer can be used in order to determine navigation data representative of pressure data, which may be used to estimate a height or level.), wherein the generating the plurality of traces of movement is based on the 3D position data and the elevation data (0086, Once the floors or levels have been identified, then the floor plans can be determined by separating the estimated location data by floor or level. The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7.).
Regarding claim 3, the combination of Vande Velde and Raman teaches the system of claim 2, and Vande Velde further teaches wherein the determining the elevation data further comprises:
Comparing the barometric pressure readings to a reference barometric pressure value to obtain barometric pressure differential data, wherein the determining the elevation data is based on the barometric pressure differential data (0032, The method may comprise using the determination of when the mobile device has entered the building and/or a number of turns determined by the compass in order to calibrate a height sensor, such as a barometric sensor. The method may comprise determining a ground floor pressure using the pressure sensor when a GPS and/or estimated location of the device is determined to have crossed a perimeter or footprint of the building.).
Regarding claim 4, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde teaches it further comprising:
Identifying a subspace of the facility that lacks traces of movement of the plurality of mobile devices (0087, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image.).
Regarding claim 5, the combination of Vande Velde and Raman teaches the system of claim 4, and Vande Velde further teaches wherein the identifying the subspace of the facility further comprises identifying an undefined subspace of the facility responsive to the map of the facility lacking a defined feature corresponding to the subspace (0087, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image.).
Regarding claim 6, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde further teaches wherein the obtaining the 3D position data of the plurality of mobile devices operating within the facility comprises:
Receiving the 3D position data from the plurality of mobile devices operating within the facility (0087, The aggregated route trace 705 from the mobile device 200 is then, for example, communicated to the server 150 via the communication channel 152, whereupon it may be further aggregated with route traces or aggregated route traces 705 for the particular building that have been determined and supplied by other mobile devices 200.).
Regarding claim 7, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde further teaches wherein the identifying the subspace further comprises:
Determining a subspace of the facility that lacks any intersection with the plurality of traces of movement of the plurality of mobile devices within the facility (0087, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image.);
Comparing the subspace to the map of the facility (Figs. 7 and 8, graphical representation of traces overlaid on top of a floorplan to create a combined graphical representation); and
Identifying an undefined area responsive to the map of the facility lacking a defined feature corresponding to the subspace (0087, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image.).
Regarding claim 12, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde further teaches wherein the obtaining the 3D position data and the generating the plurality of traces of movement are repeated periodically (0086, Once the floors or levels have been identified, then the floor plans can be determined by separating the estimated location data by floor or level. The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7.).
Regarding claim 13, the combination of Vande Velde and Raman teaches the system of claim 1, and Vande Velde further teaches wherein the 3D position data comprises geolocation coordinates (0023, The known location may be determined using the GPS location data. The method may comprise referencing and/or calibrating the estimated location data using GPS location data, such as a most recent GPS location, which may comprise automatic re-referencing or re-calibration of the non-GPS location data upon receiving new GPS location data. The most recent GPS location data may comprise GPS location data having an accuracy above a predetermined accuracy threshold.).
Claims 17 and 20 are similar in scope to claim 13, and are similarly rejected.
Regarding claim 14, Vande Velde discloses a method, comprising:
Obtaining, by a processing system including a processor, using a combination of GPS data and barometric pressure readings, 3D position data of a plurality of mobile devices operating within a facility (0059, the mobile device 200 may be equipped or equipable with one or more sensors such as pedometers 205, compasses 210, pressure sensors 215 such as barometers, gyroscopes 220, inclinometers and the like. The mobile device 200 is also equipped or equipable with a GPS sensor 225 for use when sufficient signal 108 from GPS satellites 102 is available. The GPS 225 and/or non-GPS 205, 210, 215, 220 sensors may optionally be built into the mobile device 200 or may be connected to the mobile device 200, for example as part of a retrofit or as a plug-in or accessory. The GPS sensor 225 and non-GPS sensors 205, 210, 215, 220 are operably coupled to a processor 230. The mobile device 200 further comprises communications apparatus 235, which includes a transmitter 166 and receiver 168 for communicating with other devices and/or a server 150. The mobile device 200 also comprises a memory 240 for storing navigational data derived from the non-GPS sensors or GPS location data derived from the GPS sensor 225, estimated location data derived from the navigational data and/or aggregated routes derived from the estimated location data and any data required in order to determine the estimated location data from the navigational data, such as an average user stride length);
Generating, by the processing system and based on the 3D position data, a graphical representation of patterns of movement of the plurality of mobile devices operating within the facility (0086, Once the floors or levels have been identified, then the floor plans can be determined by separating the estimated location data by floor or level. The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7. See also Figs. 7 and 8.);
Generating, by the processing system, a graphical representation of the facility (0086, Once the floors or levels have been identified, then the floor plans can be determined by separating the estimated location data by floor or level. The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7. See also Figs. 7 and 8.);
Comparing, by the processing system, the graphical representation of the facility to obtain a comparison (0028, The method may comprise comparing the GPS and/or non-GPS location data to predetermined map data, which may comprise building footprint data, and determining whether the location data is from internally or externally of the building and/or an enclosed and/or covered area. The method may comprise separating data representing the interior of the building and/or enclosed and/or covered area from data representing the exterior of the building and/or an enclosed and/or covered area. The method may comprise processing the interior data separately from the exterior data. The exterior data may comprise the GPS data. The Interior data may comprise the location related data derived from the non-GPS sensors.); and
Identifying, by the processing system, a subspace in the facility (0089, Patterns in the estimated location data and/or the navigation data obtained from one or more of the non-GPS sensors and/or GPS location data may be analysed to identify features, for example, by using statistical analysis and/or by comparison with predetermined signatures or typical patters and/or by comparison with templates or profiles or the like. For example, as detailed above, up/down ramps and stairs may be determined by using pressure data and/or identifying tight turns using compass data.).
Vande Velde fails to disclose, however, wherein the subspace is a hidden room.
Raman, however, in an analogous field of endeavor, does teach wherein the subspace is a hidden room (0051, For example, in step 503, the positioning platform 105 predicts one or more unused spaces within the physical space based on the crowd-sourcing, the location data, the other location data, or a combination thereof. More specifically, the positioning platform 105 applies predictive models to score and classified sensor data that meet conditions for classification as a feature such as a whether an area of a physical space is unused. Unused, for instance, refers to areas or regions (e.g., represented by Voronoi polytopes) of the interior volume of the physical space that have little or no location traces. These unused areas can represent obstructions or physical features that obstruct or prevent user movement.).
Vande Velde and Raman are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the unused room determination of Raman in order to provide a means of classifying a space on a generated map. The motivation to combine is to allow the system to identify spaces that may not be apparent on a map of the building.
Claim 18 is similar in scope to claim 14, and is similarly rejected.
Regarding claim 15, the combination of Vande Velde and Raman teaches the method of claim 14, and Vande Velde teaches it further comprising:
Comparing, by the processing system, the barometric pressure readings to a reference barometric pressure reading to obtain barometric pressure differences (0032, The method may comprise using the determination of when the mobile device has entered the building and/or a number of turns determined by the compass in order to calibrate a height sensor, such as a barometric sensor. The method may comprise determining a ground floor pressure using the pressure sensor when a GPS and/or estimated location of the device is determined to have crossed a perimeter or footprint of the building.); and
Determining, by the processing system, height values according to the barometric pressure differences (0078, A pressure sensor such as a barometer can be used in order to determine navigation data representative of pressure data, which may be used to estimate a height or level.), wherein the graphical representation of patterns of movement is based on the 3D position data and the height values (0086, Once the floors or levels have been identified, then the floor plans can be determined by separating the estimated location data by floor or level. The estimated location data associated with a particular floor or level, and optionally location data derived from the GPS sensor 225 if applicable, is used to generate floor plans for the building, as indicated in step 415 of FIG. 4. This comprises aggregating the estimated location data for each floor or level and using this to determine navigable locations on that floor or level. In an embodiment, estimated location data stored on the mobile device 200, which can be estimated location data collected over an extended period of time, is aggregated together to provide an aggregated route trace, as shown in FIG. 7.).
Regarding claim 16, the combination of Vande Velde and Raman teaches the method of claim 15, and Vande Velde teaches it further comprising:
Combining, by the processing system, the graphical representation of patterns of movement of the plurality of mobile devices within the facility with patterns of movement of other mobile devices within the facility to obtain a cumulative record of movement (0087, In general, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image. See also Figs. 7 and 8.).
Regarding claim 19, the combination of Vande Velde and Raman teaches the non-transitory, machine-readable medium of claim 18, and Vande Velde teaches it further comprising:
Identifying that a subspace of the building lacks traces of movement of the plurality of mobile devices, wherein the identifying the hidden room comprises identifying an undefined space of the building (0087, the aggregated data is subjected to statistical processing by the server in order to determine pathways or routes that users navigate to. The aggregated or further aggregated route traces for a particular building formed from the estimated location data are indicative of areas of the building that are navigable, such as corridors and rooms. Corridors and public areas that are intensively used may be particularly visible from this aggregated or further aggregated route trace data 705, as shown in FIG. 7. For example, it is possible to identify main corridors or halls, or other connections between entrances and exits. If preferred, an inverse or negative of the aggregated or further aggregated route trace data may be taken. The inverse or negative maybe indicative of walls or obstacles and results in a map image much more akin to a conventional map image.).
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Vande Velde in view of Raman, and further in view of Verteletskyi (US 20190172165 A1), hereafter Verteletskyi.
Regarding claim 8, the combination of Vande Velde and Raman teaches the system of claim 1, but fails to explicitly teach wherein the operations further comprise:
Determining an identity of a mobile device of the plurality of mobile devices, wherein the mobile device is distinguishable from other mobile devices of the plurality of mobile devices according to the identity; and
Storing a historical record of positions of the mobile device of the plurality of mobile devices operating within the facility.
Verteletskyi, however, in an analogous field of endeavor, does teach:
Determining an identity of a mobile device of the plurality of mobile devices, wherein the mobile device is distinguishable from other mobile devices of the plurality of mobile devices according to the identity (0086, when the previous occupant enters the building 104 or a certain zone, the occupant management module 202 can identify the corresponding user device 152 as part of a regular communication maintenance function (e.g., device scanning process). The occupant management module 202 can compare the user device 152 (e.g., a device/communication identifier of the device) to the allowed occupant list 211 (e.g., a device list therein) and/or the occupant history to identify the device user as a previous occupant. The occupant management module 202 can identify the occupant history 218 of the identified previous occupant and use preference parameters in the previous (e.g., most recent) reservation request to autonomously generate the space assignment request 452 for the current time.); and
Storing a historical record of positions of the mobile device of the plurality of mobile devices operating within the facility (0082, the control module 102 can track the current location 220 of one or more mobile devices (e.g., the user devices 152) over time. For example, the control module 102 can store the current location 220 with corresponding time stamp to determine the location history 222 of FIG. 2 of each user device. Using the location history 222 of one or more devices, the control module 102 can estimate pathways 442 (e.g., corridors, walkways, hallways, etc.) that occupants can traverse to and/or from the various occupant spaces. For example, the control module 102 can estimate the pathways 442 as portions of the space that include a sequence of locations that are determined within a movement-determination threshold (e.g., representative of an occupant walking). Also, the control module 102 can estimate the pathways 442 when one or more users traverse through the determined space with a predetermined frequency and/or more than a threshold number of occurrences over a predetermined period. In some embodiments, the control module 102 can use information provided by one or more occupants and/or building administrators.).
Vande Velde, Raman, and Verteletskyi are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the individual position records of Verteletskyi in order to provide a means of storing mobile device traces. The motivation to combine is to allow the system to identify the user associated with a trace, in order to differentiate them from other users or devices.
Regarding claim 9, the combination of Vande Velde, Raman, and Verteletskyi teaches the system of claim 8, and Verteletskyi further teaches wherein individual tracks of a plurality of tracks of the plurality of mobile devices operating within the facility are distinguishable according to identities of the plurality of mobile devices (0082, the control module 102 can track the current location 220 of one or more mobile devices (e.g., the user devices 152) over time. For example, the control module 102 can store the current location 220 with corresponding time stamp to determine the location history 222 of FIG. 2 of each user device. Using the location history 222 of one or more devices, the control module 102 can estimate pathways 442 (e.g., corridors, walkways, hallways, etc.) that occupants can traverse to and/or from the various occupant spaces. For example, the control module 102 can estimate the pathways 442 as portions of the space that include a sequence of locations that are determined within a movement-determination threshold (e.g., representative of an occupant walking). Also, the control module 102 can estimate the pathways 442 when one or more users traverse through the determined space with a predetermined frequency and/or more than a threshold number of occurrences over a predetermined period. In some embodiments, the control module 102 can use information provided by one or more occupants and/or building administrators.).
Vande Velde, Raman, and Verteletskyi are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the individual position records of Verteletskyi in order to provide a means of distinguishing users from one another. The motivation to combine is to allow the system to identify and track the user associated with a trace.
Claims 10 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Vande Velde in view of Raman and Verteletskyi, and further in view of Mendez (US 20210025717 A1), hereafter Mendez.
Regarding claim 10, the combination of Vande Velde, Raman, and Verteletskyi teaches the system of claim 9, but fails to explicitly teach wherein the operations further comprise:
Detecting a request for authorization, wherein authorization permits access to a subspace of the facility;
Associating the mobile device with the request for authorization; and
Evaluating the request for authorization according to an identity of the mobile device to obtain an evaluation result, wherein authorization is granted or denied responsive to the evaluation result.
Mendez, however, in an analogous field of endeavor, does teach:
Detecting a request for authorization, wherein authorization permits access to a subspace of the facility (0232, The system could also require the portable device and/or a user of the portable device to be authenticated, with the navigation information then being selected and provided based upon the user's/device's privilege level. For example, the level of (and/or level of detail of) navigation information that is provided could be based (dependent) on, e.g., the authentication and/or access privileges of the device/user in question.);
Associating the mobile device with the request for authorization (0232, The system could also require the portable device and/or a user of the portable device to be authenticated, with the navigation information then being selected and provided based upon the user's/device's privilege level. For example, the level of (and/or level of detail of) navigation information that is provided could be based (dependent) on, e.g., the authentication and/or access privileges of the device/user in question.); and
Evaluating the request for authorization according to an identity of the mobile device to obtain an evaluation result, wherein authorization is granted or denied responsive to the evaluation result (0232, The system could also require the portable device and/or a user of the portable device to be authenticated, with the navigation information then being selected and provided based upon the user's/device's privilege level. For example, the level of (and/or level of detail of) navigation information that is provided could be based (dependent) on, e.g., the authentication and/or access privileges of the device/user in question.).
Vande Velde, Raman, Verteletskyi, and Mendez are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the authentication of Mendez in order to provide a means of distinguishing authorized users. The motivation to combine is to ensure that unauthorized users do not enter a potentially restricted area.
Regarding claim 11, the combination of Vande Velde, Raman, Verteletskyi, and Mendez teaches the system of claim 10, and Mendez further teaches wherein the operations further comprise:
Identifying an identity of an authorized mobile device according to the request for authorization (0234, It would also, for example, be possible to trigger an alert if a portable device/user is determined to enter an area that is restricted to them. For example, a device/user entering a secure area could be flagged to the system.);
Comparing the identity of the mobile device to the identity of an authorized mobile device to obtain an identity comparison (0234, It would also, for example, be possible to trigger an alert if a portable device/user is determined to enter an area that is restricted to them. For example, a device/user entering a secure area could be flagged to the system.); and
Initiating an alarm signal responsive to the identity comparison indicating a mismatch (0234, It would also, for example, be possible to trigger an alert if a portable device/user is determined to enter an area that is restricted to them. For example, a device/user entering a secure area could be flagged to the system.).
Vande Velde, Raman, Verteletskyi, and Mendez are analogous because they are in a similar field of endeavor, e.g., mobile device navigation systems. It would have been obvious to a person having ordinary skill in the art before the effective filing date of the present invention, with a reasonable expectation of success, to have included the authentication of Mendez in order to provide a means of distinguishing authorized users. The motivation to combine is to ensure that unauthorized users do not enter a potentially restricted area.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BLAKE A WOOD whose telephone number is (571)272-6830. The examiner can normally be reached M-F, 8:00 AM to 4:30 PM Eastern.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Worden can be reached at (571) 272-4876. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BLAKE A WOOD/ Examiner, Art Unit 3658
Prosecution Insights