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 .
Response to Amendment/Remarks
This communication is considered fully responsive to the amendment filed on 07/01/2026.
Claims 1-20 are pending and are examined in this office action.
No claim have been amended.
No new claim has been added, and no claim has been canceled.
Response to Arguments
Applicant's arguments filed 07/01/2026 have been fully considered but they are not persuasive.
Applicant’s Argument: Regarding independent claim 1:
Applicant argues in substance “Applicant submits that Schaefermeier does not teach or suggest, inter alia, configuring a WiFi network based on a determined configuration derived from layout information. Rather, Schaefermeier is directed to deriving topological indoor maps from WiFi signal strength information. Schaefermeier explains that its method uses WiFi signal strength distributions, dimension reduction, and clustering, and that it is intended for settings in which users carry mobile devices and follow their normal routine, such as short-lived indoor events including conferences. Schaefermeier further emphasizes that "neither special user behavior nor technical changes of the WiFi infrastructure are required" and that its approach should work "without any additional infrastructure at the physical locations." Thus, Schaefermeier uses existing WiFi signal observations as inputs to infer a topological representation of a venue. It does not determine a WiFi network configuration from spatial layout and architectural details, and it does not configure the WiFi network based on that determined configuration to enable optimized network connectivity across all areas of the location.
Adame does not cure such deficiencies. Adame is directed to channel-load-aware AP/Extender selection in Home WiFi networks. Adame determines AP/Extender association decisions using a metric that considers RSSI and the load of access and backhaul wireless links for potential STA-AP/Extender connections. Such disclosure concerns selection among APs/Extenders in an existing multi-AP/extender environment to improve throughput and delay. Adame does not teach determining layout information comprising indicators of a spatial layout and architectural details of a location from collected WiFi data, determining a WiFi network configuration based on that layout information, or configuring the WiFi network based on such a layout-derived configuration. At most, Adame addresses association decisions and performance optimization in an already-deployed network; it does not provide the missing layout-to- configuration-to-network-configuration relationship recited in the independent claims.” ( see REMARKs).
Examiner’s Response:
The examiner respectfully disagrees.
The claims and only the claims form the metes and bounds of the invention. “Office personnel are to give claims their broadest reasonable interpretation in light of the supporting disclosure. In re Morris, 127 F.3d 1048, 1054-55, 44 USPQ2d 1023, 1027-28 (Fed. Cir. 1997). Limitations appearing in the specification but not recited in the claim are not read into the claim. In re Prater, 415 F.2d 1393, 1404-05, 162 USPQ 541, 550-551 (CCPA 1969)” (MPEP p 2100-8, c 2, I 45-48; p 2100-9, c 1, l 1-4). The Examiner has full latitude to interpret each claim in the broadest reasonable sense. The Examiner will reference prior art using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning
The claims merely recites, inter alia, Access Point (AP)…“determining, based on the layout information, a configuration of the WiFi network; and
configuring, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location” without further detail.
The applicant admitted that “Schaefermeier is directed to deriving topological indoor maps from WiFi signal strength information. Schaefermeier explains that its method uses WiFi signal strength distributions, dimension reduction, and clustering, and that it is intended for settings in which users carry mobile devices and follow their normal routine, such as short-lived indoor events including conferences” (see above).
According to the applicant’s own specification, AMURU et al. (US 20250254536 A1) , the applicant describes ”a spatial layout and architectural detail of the location” limitation in following paragraphs 0075-0076 which are reproduce here.
“[0075] Thus, in Step 320, engine 200 can, based on the AI/ML analysis of the WiFi data from Step 318, determine layout information of the location. The layout information can include, but is not limited to, size (e.g., square footage), shape, geographic location, dimensions, number of floors, number of rooms, and the like. As discussed herein, the layout information ensures that the front haul and back haul links between the AP device(s) and connected set of devices have WiFi metrics (e.g., capacity, coverage, and the like) satisfying corresponding connectivity thresholds.
[0076] Accordingly, the layout (or floorplan) of a location can be configured as a data structure (or other type of electronic file), which provides a visual representation of the spatial layout and architectural details of a specific location. According to some embodiments, the layout can include information, such as, but not limited to, the arrangement of rooms, walls, doors, floors, windows and other structural elements within the space. The layout can also indicate the dimensions of rooms, the positioning of furniture, elevations of/within the location and the locations of amenities/fixtures (e.g., electrical outlets and plumbing fixtures), and the like. For example, when an elevation angle of a WiFi signal is at or above a threshold, engine 200 can determine the device's movement to correspond to a particular floor (e.g., first or second floor, for example), as discussed herein.“
As per Fig. 3, fig. 5-6 and page 2 paragraphs 2, page 3 paragraph 2, page 9 paragraph 2, page 12 section 5.3, to section 5.5-5.6 of Schaefermeier ( which is cited by the examiner as shown in original rejection, as well as other paragraphs mentioned here) , one or more Wifi enable Access Points (APs) provides Wifi connection to one Wifi Enabled SmartPhone ( ==device in claim). Aforesaid one or more APs automatically collects signal strengths measure from Wifi Enabled SmartPhone. By the signal strength measurement values, aforesaid one or more APs creates Wifi Layout/topological Map of floor plans of the building and embedded and clustered Wifi Segments ( Page 12) for the Wifi network.
Fig. 3-4 has layout with strong and weak WiFi connection of a Map/Layout of a floor plan to connect an application of a WiFi enabled device (See Fig. 3 Fig. 4, Section 5.3). Section 5.5 of Schaefermeier shows that
“Our choice leads to slightly different positions being incorporated in the oven all estimate. Based on these representations of our final locations, we can achieve localization for new WiFi observations in our abstract topological map. More specifically, for a WiFi observation, i.e., a
vector of RSSI values over all APs, we can achieve localization through maximum likelihood [30]. The inferred locations of devices can be, e.g,, used for creating alive view of a topological map at some venue, such as a conference or workshop.”
Base on that information of one or more APs , aforesaid WiFi enable Smartphone can optimized network connection by creating a live view of a layout of map of a conference room or workshop place ( Section 5.5, Section 5.6) .
ADAME also discloses, configure, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location” ( "Evaluation of the channel load aware AP/Extender selection mechanism by simulation, studying the performance gains of using Extenders along with the
proposed solution. We focus on understanding how the number of Extenders and their position, the fraction of STAs supporting IEEE 802.l lk/v, and the load of the access and backhaul links, impact on the system performance in terms of throughput and delay."; page 2, right column, paragraph 7 ; … “ Extenders must be located at a distance (in RSSI terms) large enough to stimulate the association of farther STAs while maintaining high data rate in its backhaul connection to the AP. Also, we confirm that connecting Extenders through other Extenders not only increases the network coverage, but also the network's operational range in terms of admitted traffic load.", page 2 left column paragraph 2).
Thus claim limitation as written, clearly is taught by cited prior arts.
Applicant’s Argument and Examiner Answer:
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, Schaefermeier teaches “Schaefermeier is directed to deriving topological indoor maps from WiFi signal strength information. Schaefermeier explains that its method uses WiFi signal strength distributions, dimension reduction, and clustering, and that it is intended for settings in which users carry mobile devices and follow their normal routine, such as short-lived indoor events including conferences” (admitted by the applicant as shown above).
Adame teaches extent AP wifi connects with STAs with improved algorithm than traditional RSSI-base or signal strength based WiFi association ” (abstract). Thus, both Schaefermeier and Adame teaches measuring signal Wifi strength among the AP and STAs and aforesaid AP provide best Wifi connection for the STAs. Thus, Schaefermeier and Adame can easily be combined to provide best WiFi connection.
Regarding all dependent claims: the applicant alleges that all dependent claims are allowable since they depend from all the independent claims above. The examiner respectfully disagrees in view of the above explanation of independent claims. Thus the rejection is deemed proper.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Schaefermeier et al. (article titled "Topological Indoor Mapping through WiFi Signals" (hereinafter 'Schaeferrneier', provided in IDS ) in view of Adame et al ( article titled "Channel Load Aware AP/ Extender Selection in Home WiFi Networks Using IEEE 802.11 k/v" (hereinafter 'Adame', provided in IDS).
Examiner’s note: in what follows, references are drawn to SCHAEFERMEIER unless otherwise mentioned.
With respect to independence claim:
Regarding claim 1, Schaefermeier a method ("Hence, our method derives graphs from RSSI data, in which nodes represent (important) locations, e.g., seminar rooms or a refreshments table, and edges represent transitions between these locations (e.g., hallways or stairways).", Page 2, paragraphs 2) comprising the steps of:
identifying a device (==Wifi enabled smartphones or mobile phones or mobile devices or any Wifi enable devices) connected to an access point (AP) device (== Wifi enabled APs or simply APs) ("Task and Requirements: Our overall goal is to automatically infer topological maps of physical venues from signal strength measurements of WiFi access points (APs). Jn detail, in Ollr setup people shall carry WiFi enabled smartphones while conducting their business within a physical space, e.g., attending talks in a conference building. These smart phones, equipped with a topological navigation application, passively measure the different signal distributions at different places. A therefrom computed topological map should reflect a) which physical locations do exist, and b) how these locations are related to each other. Physical locations can be, e.g., a kitchen in an office or a seminar room in a conference building.", page 3 paragraphs 2; NOTE: Smartphones connects to APs in area like kitchen, office, seminar room based on signal strength from a location to the APs),
the AP device (==AP) ( providing a Wireless Fidelity (WiFi) network for a location ( Mobile phone connects to a AP of multiple APs using strong signal strength at a location; , "Formal Problem Definition: The data basis is constituted by timestamped WiFi observations, e.g., recorded by a smartphone. We draw on the relation between signal strength and physical distance io an AP. Each AP is uniquely identified through a basic service set identifier (BSSID)."; " We used 13 devices. For ground truth, we installed ESP323 (AP) modules in all the relevant rooms. These devices were configured as WiFi APs, such that their presence could be detected by the smartphones whenever they were nearby, The ground truth location for a stationary Wifi segment could then be determined through the ESP32 ·with the highest average signal strength ", Page 3 Paragraphs 5 & page 9 paragraph 2);
collecting WiFi data for the device communicated between the device (==any WiFi enable device or mobile phones ) and the AP device (==AP) ("We employ received signal strength indicator (RSSI) measurements that are often represented as vectors, where each component represents the RSSI of a specific AP measured at particular point in time [1]. In this work we grasp them as probability distributions of RSSI values that are conditioned on locations. …. it allows naturally for inferring localization of previously unseen measurements by maximum likelihood and determining a confidence that a measurement was made at a particular location. Hence name RSSI likelihoods.", page 3, paragraph 4; also “While walking to and staying at relevant location the smartphones collected WiFi data ( connected to APs) and sent it to a central server.” Page 9 paragraph 2);
analyzing the collected WiFi data ("Task and Requirements Our overall goal is to automatically infer topological maps of physical venues from signal strength measurements of WiFi access points (APs). Jn detail, in our setup people shall carry Wifi enabled smartphones while conducting their business within a physical space, e.g., attending talks in a conference building. These smartphones, equipped with a topological navigation application, passively measure the different signal distributions at different places. A therefrom computed topological map should reflect a) which physical locations do exist, and b) how these locations are related to each other Physical locations can be, e.g,, a kitchen in an office or a seminar room in a conference building."; Page 3, paragraph 2),
and determine, based on the analysis, layout information of the location, the layout information comprising indicators of a spatial layout and architectural details of the location (see fig. 3 and Fig. 6, also Page 12 Section 5.3: Generated MAPS: "Based on our method we generated topological maps for the SFN and office data set using MDS as depicted in Figures 3 and 6. For both cases, we show floor plans of the building and the embedded and clustered WiFi segments. For the office data set, we use 2d embeddings since the experiment was conducted in a single-floor building. As can be seen, the ground truth locations can be recovered. Moreover, we find that the topological relations between locations are accurately captured. In detail, one can infer the physical floor plan from this plot to some extent However, we find that in a few cases neighboring locations fail together into a single duster. This can be attributed to the underlying WiFi signals being similar when being close to the wall between two rooms. We also observed that the layout of the WiFi APs within buildings contributes to the performance."; Page 12, section 5.3; NOTE: Layout detail MAPS of the location based on analysis);
determine, based on the layout information, a configuration of the WiFi network
( see fig. 5: Localize signal strength of a WiFI network, "….. an overall RSSI likelihood by averaging over the estimated densities for each WiFi segment (Figure 5), An alternative method would have been a kernel density estimation over the samples from the WiFi segments. We favor the first method to avoid single, very long segments dominating !he overall estimation. Our choice leads to slightly different positions being incorporated in the overall estimate. Based 0n these representations of our final locations, we can achieve localization for new WiFi observations in our abstract topological map. More specifically, for a WiFi observation, ie., a vector of RSSI values over the APs, we can achieve localization through maximum likelihood [30]. The inferred locations of devices can be, e.g., used for creating a live view of a topological map at some venue, such as a conference or workshop.", page 14,section 5.5 paragraph 2).
While Schaefermeier teaches “determine, based on the layout information, a configuration of the WiFi network” , Schaefermeier does not expressively disclose “configure, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location”.
ADAME, in the same field of endeavor, discloses: archivable performance gain using secondary APS/extender in home Wifi networks (abstract). ADAME also discloses,
configure, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location” ( "Evaluation of the channel load aware AP/Extender selection mechanism by simulation, studying the performance gains of using Extenders along with the
proposed solution. We focus on understanding how the number of Extenders and their position, the fraction of STAs supporting IEEE 802.l lk/v, and the load of the access and backhaul links, impact on the system performance in terms of throughput and delay."; page 2, right column, paragraph 7 ; … “ Extenders must be located at a distance (in RSSI terms) large enough to stimulate the association of farther STAs while maintaining high data rate in its backhaul connection to the AP. Also, we confirm that connecting Extenders through other Extenders not only increases the network coverage, but also the network's operational range in terms of admitted traffic load.", page 2 left column paragraph 2).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of SCHAEFERMEIER to include configure, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location as taught by ADAME. The suggestion/motivation would be to improves the coverage, higher throughput capacity and lower delays (ADAME {Page 15, left column, para 1}).
Regarding claim 13, SCHAEFERMEIER teaches,
A system comprising (see fig. 1 : system ) :
a processor (system must have a processor ) configured to:
identify a device connected to an access point (AP) device, the AP device providing a Wireless Fidelity (WiFi) network for a location;
collect WiFi data for the device communicated between the device and the AP device;
analyze the collected WiFi data, and determine, based on the analysis, layout information of the location, the layout information comprising indicators of a spatial layout and architectural details of the location;
determine, based on the layout information, a configuration of the WiFi network; and
configure, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location (Regarding rest of claim 13, the claim is interpreted and rejected for the same reason as set forth in claim 11)..
Regarding claim 20, SCHAEFERMEIER teaches,
A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions that when executed by a processor, perform a method comprising:
identifying a device connected to an access point (AP) device, the AP device providing a Wireless Fidelity (WiFi) network for a location;
collecting WiFi data for the device communicated between the device and the AP device;
analyzing the collected WiFi data, and determining, based on the analysis, layout information of the location, the layout information comprising indicators of a spatial layout and architectural details of the location;
determining, based on the layout information, a configuration of the WiFi network; and
configuring, based on the determined configuration, the WiFi network, the configuration comprising functionality enabling optimized network connectivity across all areas of the location (Regarding claim 20, the claim is interpreted and rejected for the same reason as set forth in claim 13).
With respect to independence claim:
Regarding claim 2, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 1, wherein the WiFi data comprises at least one of received signal strength indictor (RSSI) data, signal to noise ratio (SNR) data, wireless channel information, ranging information, channel utilization, latency ,roaming, authentication, retry rates, throughput and bandwidth ( "… received signal strength indicator (RSSI) measurements that are often represented as vectors, where each component represents the RSSI of a specific AP measured at particular point ….. we grasp 1hem as probability distribution; of RSSI values that. are conditioned on !oca1ions. … determining a confidence that a measurement was made at a particular location. ….”: Page 3 para 4. )..
Regarding claim 3, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 2, further comprising:
collecting RSSI data for the device;
analyzing the RSSI data; and
performing the collection of the WiFi data based on the analysis of the RSSI data ( combine an segments from a cluster into an overall RSSI likelihood by averaging over the estimated densities for each WiFi segment (Figure 5). An alternative method would have been a kernel density estimation over the samples from the WiFi segments. We favor the first method to avoid single, very long segments dominating the overall estimation. Our choice leads to slightly different positions being incorporated in the overall estimate. Based on these representations of our final locations, we can achieve localization for new WiFi observations in our abstract topological map. More specifically, for a WiFi observation, i.e., a vector of RSSI values over all APs, we can achieve localization through maximum likelihood [30]. The inferred locations of devices can be, e.g., used for creating a live view of a topological map at some venue, such as a conference or workshop.": Page 14, para 2).
Regarding claim 4, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 1, wherein the layout information comprises information related to at least one of arrangement of rooms, walls, doors, floors, windows, dimensions of rooms, positioning of furniture, elevations within the location, and locations of amenities and fixtures ( "… in our setup people shall carry WiFi enabled smartphones while conducting their business within a physical space, e.g., attending talks in a conference building. These smartphones, equipped with a topological navigation application, passively measure the different signal distributions at different places. A therefrom computed topological map should reflect a) which physical locations do exist, and b) how these locations are related to each other. Physical locations can be, e.g., a kitchen in an office or a seminar room in a conference building."( page 3, paragraph 2).
Regarding claim 5, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, ADAME teaches,
The method of claim 1, further comprising:
determining, based on the analysis, network coverage details for each area within the location, the coverage details providing indicators of whether coverage holes exist respective to each area, wherein the determination of the configuration of the WiFi network is based on the determined network coverage details (("Evaluation of the channel load aware AP/Extender selection mechanism. by simulation, studying the performance gains of using Extenders
along with the proposed solution. We focus on understanding how the number of Extenders and their position, the fraction of STAs supporting IEEE 802.1lk/v, and the load of the access and backhaul links, impact on the system. performance in terms of 1hroughput and delay."; page 2, right column, paragraph 2); " Placement of Extenders: We observe that Extenders must be located at a distance (in RSSI terms) large enough to stimulate the association of farther STAs while maintaining high data rate in its backhaul connection to tee .AP. Also, we confirm that connecting Extenders through other Extenders not only increases !he network coverage, but also the network's operational range in terms of admitted traffic load.": Page 2 right col. Par 2).
Regarding claim 6, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, ADAME,
The method of claim 1, wherein the configuration of the WiFi network corresponds to a network topology, wherein the network topology provides an indicator of a required number of AP devices and positions of the AP devices within the location to ensure that coverage holes are not present within connectivity of the WiFi network ("Testbed ill was designed to analyze the perfom1ance of a network that consisted of one AP and one Extender, considering only the RSSI-based association mechanism. The device placement for this experiment can be found in Figure 14a, Two cases were considered: the first one was the deployment without the Extender, meaning that all STAs were forced to associate to the AP. The second case did consider the Extender, allowing STAs to associate to either the AP or the Extender. The association for each case can be found in Table 7, as well as the RSSI of each STA for both the AP and the Extender.": fig 14, page 14, left column, paragraph 2). .
Regarding claim 7, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, ADAME teaches,
The method of claim 1, wherein the configuration of the WiFi network provides a network implementation for front haul and back haul links between the device and the AP device with WiFi connectivity metrics satisfying connectivity thresholds ("Evaluation of the channel load aware AP/ Extender selection mechanism by simulation, studying the performance gains of using Extenders along with the proposed solution. We focus on understanding how the number of Extenders and their position, the fraction of STAs supporting IEEE 802.l lk/v, and the load of the access and backhaul links, impact on the system performance in terms of throughput and delay." : page 2, left column, paragraph 9).
Regarding claim 8, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 1, further comprising:
determining that the device is active within the location, wherein the active determination corresponds to at least one of activity on the WiFi network and movement within the location, wherein the collection of WiFi data is based on the active determination ("Formal Problem Definition The data basis is constituted by timestamped WiFi observations, e.g., recorded by a sma,.'1pbone. We draw on the relation between signal strength and physical distance to an AP. Each AP is uniquely identified through a basic service set identifier {BSSlD).: page 3, paragraph 5 "; "Task and Requirements Our overall goal is to automatically infer topological maps of physical venues from signal strength measurements of WiFi access points (APs). In detail, in our setup people shall carry WiFi enabled smartphones while conducting their business within a physical space, e.g., attending talks in a conference building. These smartphones, equipped with a topological navigation application, passively measure the different signal distributions at different places. A therefrom computed topological map should reflect a) which physical locations do exist, and b) how these locations are related to each other. Physical locations can be, e.g., a kitchen in an office or a seminar room in a conference building.": page 3, paragraph 2).
Regarding claim 9, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 1, wherein the identified device is part of a set of devices connected to the AP device, wherein the steps are performed for each other device in the set of devices ("Formal Problem Definition The data basis is constituted by timestamped WiFi observations, e.g., recorded by a smartphone. We draw on the relation between signal strength and physical distance to an AP. Each AP is uniquely identified through a basic service set identifier (BSSID)." page 3, paragraph 5; "Task and Requirements Our overall goal is to automatically infer topological maps of physical venues from signal strength measurements of WiFi access points (APs), In detail, in our se111p people shall carry WiFi enabled smartphones while conducting their business within a physical space, e.g., attending talks in a conference building. These smartphones, equipped with a topological navigation application, passively measure 1he different signal distribu1ions at different places. A therefrom computed topological map should reflect a) which physical locations do exist, and b) how these locations are related to each other. Physical locations can be, e.g., a kitchen in an office or a seminar room in a conference building."; page 3, paragraph 2).
Regarding claim 10, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, SCHAEFERMEIER teaches,
The method of claim 1, wherein the device is a mobile device of a user ( Wifi enabled smartphone or Wifi enable mobile device or any Wifi enable de vice with topological navigation application: [abstract]; Page 2, paragraph 2).
Regarding claim 11, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, ADAME teaches,
The method of claim 1, wherein the steps are performed by a cloud ( “ In a real implementation, all computation associated with this mechanism would be executed in the AP, as it is the single, centralized element in the architecture with a global vision of the network. Alternatively, computation tasks could be assumed by an external network controller nm into a server, either directly connected to the AP or placed in a remote, cloud-based location”: Page 6 right column paragraph 8).
Regarding claim 12, SCHAEFERMEIER in view of ADAME teaches the invention of claim 1 as set forth above. Further, ADAME teaches,
The method of claim 1, wherein the location corresponds to a home of a user ( “use of Extenders in next-generation Home WiFi networks ”: Page 2 right column paragraph 7).
Regarding claim 14, the claim is interpreted and rejected for the same reason as set forth in claim 2.
Regarding claim 15, the claim is interpreted and rejected for the same reason as set forth in claim 3.
Regarding claim 16, the claim is interpreted and rejected for the same reason as set forth in claim 4.
Regarding claim 17, the claim is interpreted and rejected for the same reason as set forth in claim 5.
Regarding claim 18, the claim is interpreted and rejected for the same reason as set forth in claim 6.
Regarding claim 19, the claim is interpreted and rejected for the same reason as set forth in claim 7.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to M MOSTAZIR RAHMAN whose telephone number is (571)272-4785. The examiner can normally be reached 8:30am-5:00pm PST.
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, Derrick Ferris can be reached at 571-272-3123. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/M Mostazir Rahman/Examiner, Art Unit 2411
/DERRICK W FERRIS/Supervisory Patent Examiner, Art Unit 2411
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