DETAILED ACTION
This final Office action is responsive to Applicant’s amendment filed December 22, 2025. Claims 1-5 and 7-18 have been amended. Claim 6 is cancelled. Claims 1-5 and 7-18 are presented for examination.
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 Arguments
Applicant's arguments filed December 22, 2025 have been fully considered but they are not persuasive.
Preliminarily, it is noted that the claim amendments have overcome the previously-pending rejections under 35 U.S.C. § 112(b) and the rejection of claim 18 under 35 U.S.C. § 101. The claim interpretations under 35 U.S.C. § 112(f) have been updated to reflect the current claim language.
Regarding the art rejection, Applicant argues that “nowhere does Flores suggest counting a number of beacon IDs of beacon signals from moving and stationary objects to determine a moving object beacon signal strength and a stationary object beacon signal strength. Paragraphs 31, 39, 41, 46, 48, 49, and 54 of Flores merely describe defining whether a position has "strong signals" based on a predefined minimum received signal strength indicator (RSSI) from a predefined minimum number of beacons with no suggestion of counting the number of beacon IDs to determine the RSSI…Similarly, Han lacks any suggestion of beacon IDs, let alone counting the number of beacon IDs to determine a moving object and stationary object beacon signal strength…As such, Han and Flores do not teach, suggest, or disclose, an apparatus including "a beacon signal recognizer configured to determine a moving object beacon signal strength of beacon signals received from beacons installed on a moving object and a stationary object beacon signal strength of beacon signals received from beacons installed on a stationary object, wherein the beacon signal strength is a sum of a number of beacon IDs stored in the beacon signal management table, wherein the beacon signal recognizer is configured to determine the moving object beacon signal strength by counting the number of beacon IDs of beacon signals received from moving objects stored in the beacon signal management table and the stationary object beacon signal strength by counting the number of beacon IDs of beacon signals received from stationary objects stored in the beacon signal management table," as recited in amended claim 1.” (Page 10 of Applicant’s response)
The Examiner points out that, as explained in the rejection, Millman evaluates a signal strength of a corresponding signal source, including a beacon (Millman: ¶¶ 111, 130; claim 13). Like Millman, Flores assesses signal strength. Regarding the determination of a sum of the number of beacon IDs, Flores determines the relative signal quality at a location based on a total number of beacons with signal strength over a defined threshold, such as a predefined minimum RSSI (Flores: ¶¶ 31, 39, 46, 48, 49, 51, 54). Additionally, Han discloses that a signal strength sequence may be detected, using signal sources disposed at a stop (i.e., at a stationary object) or on a vehicle in the travel route (i.e., on a moving object) (Han: abstract, ¶¶ 42-45), thereby providing additional suggestion that Flores’ correlation of a number of detected beacons indicating a sufficiently strong signal strength can be applied to any type of beacon, including stationary and moving beacons. Flores simply provides Millman with an approach to assessing signal strength. The rejection is maintained.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“data storage unit” (to store…) in claim 1 [Support is found in Spec: p. 3 – “According to an aspect, the invention may include a data storage unit, which can store information storable in a beacon definition table, a beacon signal management table and/or a passenger status definition table. The data storage unit may preferably be an internal storage unit for storing, among others, the information described below in a database which is preferably structured as a table, another suitable data format or the like. The data storage may be provided with the user's mobile device, the apparatus or another remote location. The data storage may also be distributed over different storage places.”]
“a beacon translator” (to read…and to write…) in claim 1
“a beacon signal recognizer” (to determine...) in claim 1
“a passenger status generator” (to determine…) in claim 1
“the passenger status generator” (to determine…) in claim 2
“the passenger status generator” (to determine…) in claim 3
“the beacon ID translator” (to periodically sample…) in claim 8
“the beacon signal recognizer” (to determine…) in claim 9
“the beacon signal recognizer” (to reset) in claim 10
“the beacon signal recognizer” (to reset) in claim 11
“the beacon signal recognizer” (to store…) in claim 13
“the passenger status generator” (to store…) in claim 14
“a journey validator” (to store…) in claim 15
[Support for the various terms cited above is found in Spec: pp. 23-24 – “The present disclosure may be embodied in many different forms, including, but in no way limited to, computer program logic for use with a processor (e.g., a microprocessor, microcontroller, digital signal processor, or general purpose computer), programmable logic for use with a programmable logic device (e.g., a Field Programmable Gate Array (FPGA) or other PLD), discrete components, integrated circuitry (e.g., an Application Specific Integrated Circuit (ASIC)), or any other means including any combination thereof Computer program logic implementing some or all of the described functionality is typically implemented as a set of computer program instructions that is converted into a computer executable form, stored as such in a computer readable medium, and executed by a microprocessor under the control of an operating system. Hardware-based logic implementing some or all of the described functionality may be implemented using one or more appropriately configured FPGAs.”]
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-5, 7-8, and 13-18 are rejected under 35 U.S.C. 103 as being unpatentable over Millman et al. (US 2016/0094950) in view of Han et al. (US 2020/0279203 in view of Flores et al. (US 2021/0216906).
[Claim 1] Millman discloses an apparatus for determination of a passenger status, which is configured to receive a beacon signal including a beacon ID from a mobile device of the passenger which the mobile device received from a beacon (¶ 34 – “For example, mobile device 102 can pass station 1 at a given time. While passing station 1, a wireless receiver of mobile device 102 may detect RF signals of one or more wireless access points (APs). Mobile device 102 can determine a received signal strength indication (RSSI) for each detected signal and an identifier of each AP. Mobile device 102 can match the identifiers of the APs, the RSSIs, or both to the location fingerprint data and identify a station that has a location fingerprint data that matches the identifiers of APs or RSSIs. For example, the location fingerprint data can include a station “Station 1” associated with a media access control (MAC) address X identifying an AP that is detectable at “Station 1.” Mobile device 102 can detect an RF signal including MAC address X. By matching the MAC address in the location fingerprint data and the detected RF signal, mobile device 102 can determine that mobile device 102 passed station “Station 1.””; ¶ 36 – “Mobile device 102 can display user interface 104 to a user. User interface 104 can include prompt 106. Prompt 106 can include recommendation 108 indicating a next train for a user carrying mobile device 102 to take.”), comprising:
a data storage unit configured to store information in a beacon definition table, a beacon signal management table and a passenger status definition table (¶ 118 – “For example, the location server, or sampling device, can determine that the mobile device entered an underground station upon determining an increase in air pressure, a decrease in light, and a loss of GPS signals. The last known location, according to the GPS signals, can match a location of the first station as stored in a location database. The location server can then determine that a radio receiver of the sampling device detected a signal pattern of RSSIs of one or more access points that matches a location fingerprint associated with the first platform by matching the signal patterns with location fingerprints of various parts of the first station.”; fig. 5A; ¶ 56 – “FIG. 5A illustrates exemplary techniques of determining location fingerprint data from signal profiles. A location server, e.g., location server 214, can receive measurements from one or more sampling devices, e.g., sampling device 202. The location server can determine signal profiles 502, 504, and 506 from the received measurements. Signal profile 502 can be associated with a first station, Station 1. Signal profiles 504 and 506 can be associated with a first platform and a second platform of a second station, Station 2, respectively. Signal profiles 504 and 506 can correspond to a same set of signal sources. Signal profile 502 can correspond to a different set of signal sources.”; ¶ 57 – “The location server can determine location fingerprint data 508 from signal profiles 502, 504, and 506. Location fingerprint data 508 can include location fingerprints 510, 512, and 514, corresponding to signal profiles 502, 504, and 506, respectively. The location server can designate location fingerprints 510, 512, and 514 as location fingerprints of the first station, the first platform of the second station, and the second platform of the second station, respectively. The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 48 – “Being carried by the surveyor, sampling device 202 can move on platform 302 in a random pattern or following a pre-specified pattern, e.g., following path 306. While moving, sampling device 202 can record measurements of signals detected by sampling device 202, e.g., RF signals from signal source 206. In addition, in some implementations, sampling device 202 can record readings from sensors other than RF receivers. For example, sampling device 202 can record sound level, air pressure level, or magnetic field. Sampling device 202 can associate the measurements with an identifier. A gradual increase in sound level, air pressure level, and magnetic field disturbance may indicate that a train is approaching the station where platform 302 is located. Likewise, a gradual decrease in those readings may indicate that a train is departing the station. Sampling device 202 can associate the readings with the signal measurements. Sampling device 202 can submit the measurements and associated readings to a location server.”; ¶¶ 94-100 – The various pieces of information of interest are stored in databases, i.e., tables.; ¶ 107 – “The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source.” The signal source can be a beacon.; ¶ 34 – The various access points (APs) are also examples of beacons.),
wherein the beacon definition table is configured to store a beacon ID, a position ID indicating a location of a beacon and an attribute indicating whether a beacon is installed on a moving object or a stationary object (¶ 107 -- The signal source can be a beacon.; ¶¶ 34, 67 – The various access points (APs) are also examples of beacons.; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 38 – “Mobile device 102 can move location marker 112 along a route of the transmit system, even when GPS signals are unavailable, upon determining that (1) mobile device 102 left Station 1, (2) a motion sensor indicates that mobile device 102 is moving, and (3) a barometer reading indicates that mobile device 102 is underground.”; ¶ 34 – “For example, mobile device 102 can pass station 1 at a given time. While passing station 1, a wireless receiver of mobile device 102 may detect RF signals of one or more wireless access points (APs). Mobile device 102 can determine a received signal strength indication (RSSI) for each detected signal and an identifier of each AP. Mobile device 102 can match the identifiers of the APs, the RSSIs, or both to the location fingerprint data and identify a station that has a location fingerprint data that matches the identifiers of APs or RSSIs. For example, the location fingerprint data can include a station “Station 1” associated with a media access control (MAC) address X identifying an AP that is detectable at “Station 1.” Mobile device 102 can detect an RF signal including MAC address X. By matching the MAC address in the location fingerprint data and the detected RF signal, mobile device 102 can determine that mobile device 102 passed station “Station 1.””; ¶ 36 – “Mobile device 102 can display user interface 104 to a user. User interface 104 can include prompt 106. Prompt 106 can include recommendation 108 indicating a next train for a user carrying mobile device 102 to take.” Station, business, platform, etc. identifications are examples of indicators of access points/beacons that are stationary objects.; ¶ 107 -- “The sensor readings can include readings from at least one of an accelerometer, a magnetometer, a barometer, a gyroscope, a light sensor, a sound pressure sensor, or a radio receiver coupled to the sampling device. In some implementations, the sensor readings are measurements of strength of radio RF signals of a signal source that are detectable at the portion of the transit system. The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source. The identifiers can be MAC addresses of the signal sources.”; ¶ 114 – “The location server can obtain (1402) sensor readings that are taken by a sampling device in a transit system that includes a route, stations on the route, and one or more platforms at each station. Each sensor reading can be associated with a timestamp and a tag indicating on which portion of the transit system the reading was taken. The sensor readings can be readings of inertial sensor indicating motion states of the sampling device. The inertial sensor can include an accelerometer or a gyroscope.”; ¶ 51 – “The signal measurements can be associated with one or more identifiers of one or more signal sources. An identifier of a signal source can be a MAC address of the signal source, or any other identifier that can uniquely identify the signal source. In some implementations, the sampling device can associate other sensor readings with the signal measurements. The sampling device can collect the signal measurements repeatedly for a pre-specified period of time, e.g., five minutes. The sampling device may be moving, so each time the sampling device takes measurements from multiple signal sources that are in fixed locations, the values of the measurements may be different from measurements of an earlier time.”), and
the beacon signal management table is configured to store the beacon ID of each beacon signal received from the mobile device and a time stamp (¶ 107 -- “The sensor readings can include readings from at least one of an accelerometer, a magnetometer, a barometer, a gyroscope, a light sensor, a sound pressure sensor, or a radio receiver coupled to the sampling device. In some implementations, the sensor readings are measurements of strength of radio RF signals of a signal source that are detectable at the portion of the transit system. The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source. The identifiers can be MAC addresses of the signal sources.”; ¶¶ 114, 116 – The sensor readings are associated with timestamps.; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 63 – “A sampling device, e.g., sampling device 202 of FIG. 2, can be programmed to record signal measurements of a portion of a transit system between two stations while the sampling device travels on a train that runs from a first station to a second station. A location server, e.g., location server 214, can determine a time-based location fingerprint for the portion of the transit system.”; ¶¶ 51-52 – Relevant data is gathered, including sensor readings (which may include a time stamp, as seen in ¶¶ 114, 116), and forwarded to the location server.; figs. 11-13, ¶¶ 73, 77, 94-97, 116 – It is understood that the location server must have access to time-related information in order to determine the dwell time and activities related to motion, thereby implying that the time stamp information is recorded in association with beacon information. Data is stored in various databases, i.e., tables.), and
the passenger status definition table is configured to store information about a previous or current passenger status and a beacon signal strength (¶¶ 53-58 – A signal profile is compared to a location fingerprint. A histogram may be used to generate a distribution of signal measurements.; ¶ 94 – “Fingerprint construction module 1104 is a component of location server 214 programmed to determine patterns, if any, from the signal profiles submitted by survey interface module 1102 and select, from multiple statistical tools, an algorithm that is most efficient in determining a location fingerprint. Using that algorithm, fingerprint construction module 1104 can generate a location fingerprint for each station of the transit system, for each platform of the station, and for each section of the transit system that is between two stations. Fingerprint construction module 1104 then stores the location fingerprints in location fingerprint database 516.”; ¶ 118 – “ For example, the location server, or sampling device, can determine that the mobile device entered an underground station upon determining an increase in air pressure, a decrease in light, and a loss of GPS signals. The last known location, according to the GPS signals, can match a location of the first station as stored in a location database. The location server can then determine that a radio receiver of the sampling device detected a signal pattern of RSSIs of one or more access points that matches a location fingerprint associated with the first platform by matching the signal patterns with location fingerprints of various parts of the first station.”);
wherein the apparatus further comprises:
a beacon ID translator configured to read the position ID and the attribute of the received beacon signal from the beacon definition table and to write the beacon ID and the time stamp of receipt of the beacon signal into the beacon signal management table (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 107 -- “The sensor readings can include readings from at least one of an accelerometer, a magnetometer, a barometer, a gyroscope, a light sensor, a sound pressure sensor, or a radio receiver coupled to the sampling device. In some implementations, the sensor readings are measurements of strength of radio RF signals of a signal source that are detectable at the portion of the transit system. The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source. The identifiers can be MAC addresses of the signal sources.”; ¶¶ 114, 116 – The sensor readings are obtained by the location server and associated with timestamps and tags.; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 63 – “A sampling device, e.g., sampling device 202 of FIG. 2, can be programmed to record signal measurements of a portion of a transit system between two stations while the sampling device travels on a train that runs from a first station to a second station. A location server, e.g., location server 214, can determine a time-based location fingerprint for the portion of the transit system.”; ¶¶ 51-52 – Relevant data is gathered, including sensor readings (which may include a time stamp, as seen in ¶¶ 114, 116), and forwarded to the location server.; figs. 11-13, ¶¶ 73, 77, 94-97, 116 – It is understood that the location server must have access to time-related information in order to determine the dwell time and activities related to motion, thereby implying that the time stamp information is recorded in association with beacon information. Data is stored in various databases, i.e., tables.; fig. 11, ¶ 96 – “Location server 214 can include location data interface module 1108. Location data interface module 1108 is a component of location server 214 programmed to receive location data 1109 from various information sources. The location data can include geographic coordinates of stations of a transit system and geometry of routes of the transit system. Location data interface module 1108 can provide location data 1109 to connectivity determination module 1106 for performing “snap to route” operations, including mapping the measurements in the signal profile from a time dimension to a space dimension and adding geometry, including way points defined by latitude and longitude coordinates, to the belief state. Output of connectivity determination module 1106 can be stored in connectivity database 1110.”);
a passenger status generator configured to determine a passenger current status based on the moving object beacon signal strength, the stationary object beacon signal strength and/or a previous passenger status (abstract – A location of a user is determined.; ¶¶ 113-122 – Location of a user and if the user is at a stop or in motion are determined.; ¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 51 – “The signal measurements can be associated with one or more identifiers of one or more signal sources. An identifier of a signal source can be a MAC address of the signal source, or any other identifier that can uniquely identify the signal source. In some implementations, the sampling device can associate other sensor readings with the signal measurements. The sampling device can collect the signal measurements repeatedly for a pre-specified period of time, e.g., five minutes. The sampling device may be moving, so each time the sampling device takes measurements from multiple signal sources that are in fixed locations, the values of the measurements may be different from measurements of an earlier time.”).
Millman does not explicitly disclose a beacon signal recognizer configured to determine a moving object beacon signal strength of beacon signals received from beacons installed on a moving object and a stationary object beacon signal strength of beacon signals received from beacons installed on a stationary object, wherein the beacon signal strength is a sum of a number of beacon IDs stored in the beacon signal management table, wherein the beacon signal recognition module is configured to determine the moving object beacon signal strength by counting the number of beacon IDs of beacon signals received from moving objects stored in the beacon signal management table and the stationary object beacon signal strength by counting the number of beacon IDs of beacon signals received from stationary objects stored in the beacon signal management table.
Millman evaluates a signal strength of a corresponding signal source, including a beacon (Millman: ¶¶ 111, 130; claim 13). Like Millman, Flores assesses signal strength. Regarding the determination of a sum of the number of beacon IDs, Flores determines the relative signal quality at a location based on a total number of beacons with signal strength over a defined threshold, such as a predefined minimum RSSI (Flores: ¶¶ 31, 39, 46, 48, 49, 51, 54). Additionally, Han discloses that a signal strength sequence may be detected, using signal sources disposed at a stop (i.e., at a stationary object) or on a vehicle in the travel route (i.e., on a moving object) (Han: abstract, ¶¶ 42-45), thereby providing additional suggestion that Flores’ correlation of a number of detected beacons indicating a sufficiently strong signal strength can be applied to any type of beacon, including stationary and moving beacons. Flores simply provides Millman with an approach to assessing signal strength. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman to include a beacon signal recognizer configured to determine a moving object beacon signal strength of beacon signals received from beacons installed on a moving object and a stationary object beacon signal strength of beacon signals received from beacons installed on a stationary object, wherein the beacon signal strength is a sum of a number of beacon IDs stored in the beacon signal management table, wherein the beacon signal recognition module is configured to determine the moving object beacon signal strength by counting the number of beacon IDs of beacon signals received from moving objects stored in the beacon signal management table and the stationary object beacon signal strength by counting the number of beacon IDs of beacon signals received from stationary objects stored in the beacon signal management table in order to facilitate more accurate correlations among the various fingerprints, signal profiles, and user location through a more cost effective and time efficient application of training data to the models (as suggested in ¶ 4-9 of Flores) and because “a vehicle scheduling strategy corresponding to a travel route can be determined based on a signal strength sequence of a detection signal detected by scanning the travel route by a user terminal, thereby accurately determining a vehicle scheduling strategy in the travel route.” (Han: ¶ 25) This would have enhanced Millman’s ability to track users on their travel routes.
[Claim 2] Millman discloses wherein the passenger status generator is configured to determine the passenger's current status based on the moving object beacon signal strength, the stationary object beacon signal strength, a change over time of the moving object beacon signal strength, the stationary object beacon strength and/or the previous passenger status (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; abstract – A location of a user is determined.; ¶¶ 113-122 – Location of a user and if the user is at a stop or in motion are determined.; ¶¶ 125, 126, 131 – Motion states over time may be tracked.; fig. 6 – Shows changes in detected signals over time.).
[Claim 3] Millman discloses wherein the passenger status generator is configured to determine the current passenger status by selecting a passenger status from a plurality of predefined passenger status stored in the passenger status definition table (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 118 – “For example, the location server, or sampling device, can determine that the mobile device entered an underground station upon determining an increase in air pressure, a decrease in light, and a loss of GPS signals. The last known location, according to the GPS signals, can match a location of the first station as stored in a location database. The location server can then determine that a radio receiver of the sampling device detected a signal pattern of RSSIs of one or more access points that matches a location fingerprint associated with the first platform by matching the signal patterns with location fingerprints of various parts of the first station.”; abstract – A location of a user is determined.; ¶¶ 113-122 – Location of a user and if the user is at a stop or in motion are determined.; ¶¶ 125, 126, 131 – Motion states over time may be tracked.; fig. 6 – Shows changes in detected signals over time.).
[Claim 4] Millman discloses wherein the plurality of predefined passenger status are defined in the passenger status definition table each based on a combination of at least one of an absolute value of the moving object beacon signal strength, an absolute value of the stationary object beacon strength, a change over time of the moving object beacon signal strength, the stationary object beacon strength and/or the previous passenger status (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 118 – “For example, the location server, or sampling device, can determine that the mobile device entered an underground station upon determining an increase in air pressure, a decrease in light, and a loss of GPS signals. The last known location, according to the GPS signals, can match a location of the first station as stored in a location database. The location server can then determine that a radio receiver of the sampling device detected a signal pattern of RSSIs of one or more access points that matches a location fingerprint associated with the first platform by matching the signal patterns with location fingerprints of various parts of the first station.”; abstract – A location of a user is determined.; ¶¶ 113-122 – Location of a user and if the user is at a stop or in motion are determined.; ¶¶ 125, 126, 131 – Motion states over time may be tracked.; fig. 6 – Shows changes in detected signals over time.).
[Claim 5] Millman does not explicitly disclose wherein the plurality of predefined passenger status stored in the passenger status definition table includes "outside", "waiting", "ready to board" and "onboard". Han discloses that the duration of various stages of travel are identified, including “a waiting time duration the user spends until the vehicle arrives at the travel departure stop (Han: ¶ 20), which is akin to the passenger being “outside” or “waiting” or “ready to board”. It may also be detected when a user is at a boarding stop (Han: ¶ 62), which is another example of “outside” or “ready to board” or even “onboard”. A “travel time” is also determined (Han: ¶¶ 17, 20, 23, 24), which is another example of an “onboard” passenger status. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the plurality of predefined passenger status stored in the passenger status definition table (1103) includes "outside", "waiting", "ready to board" and "onboard" in order to facilitate more accurate monitoring and planning of a travel route, particularly in regard to detected signals (as suggested in ¶ 25 of Han).
[Claim 7] Millman discloses wherein the beacon signal management table stores each beacon ID (Millman: ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”). Millman does not explicitly disclose wherein the beacon signal management table (1102) stores each beacon ID such as to differentiate between beacon IDs from a stationary object and a moving object, respectively.
However, Han discloses that a signal strength sequence may be detected, using signal sources disposed at a stop or a vehicle in the travel route (Han: abstract, ¶¶ 42-45). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the beacon signal management table (1102) stores each beacon ID such as to differentiate between beacon IDs from a stationary object and a moving object, respectively, because “a vehicle scheduling strategy corresponding to a travel route can be determined based on a signal strength sequence of a detection signal detected by scanning the travel route by a user terminal, thereby accurately determining a vehicle scheduling strategy in the travel route.” (Han: ¶ 25) This would have enhanced Millman’s ability to track users on their travel routes.
[Claim 8] Millman discloses wherein the beacon ID translator is configured to periodically sample received beacon signals and to write the beacon ID and the time stamp of receipt into the beacon signal management table (1102) at first predetermined time intervals (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 121 – “The location server can determine (1408), using the motion states, a time-based probability distribution of location of a user device traveling from the first platform of the first station to the third platform of the second station along the route and a probability distribution of time mobile devices staying on the first platform or the third platform. Determining the time-based probability distribution of the location of the user device can include converting a sequence of measurements from a time dimension to a space dimension by associating the timestamps with the inertial sensor readings. The location server can then determine the time-based probability distribution of the location of the user device over time since the user device leaves the first platform based on the converted sequence of measurements. The location server, or the user device, can overlay a representative of the location of the user device and a representation of the transit system on a map.”; fig. 6, ¶¶ 63-66 – Shows beacon information at various time intervals corresponding to time in minutes, which would correlate to timestamp information.; ¶ 63 – “A sampling device, e.g., sampling device 202 of FIG. 2, can be programmed to record signal measurements of a portion of a transit system between two stations while the sampling device travels on a train that runs from a first station to a second station. A location server, e.g., location server 214, can determine a time-based location fingerprint for the portion of the transit system.”; Reiterating the discussion of time stamps from claim 1 above: ¶¶ 114, 116 – The sensor readings are obtained by the location server and associated with timestamps and tags.; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 63 – “A sampling device, e.g., sampling device 202 of FIG. 2, can be programmed to record signal measurements of a portion of a transit system between two stations while the sampling device travels on a train that runs from a first station to a second station. A location server, e.g., location server 214, can determine a time-based location fingerprint for the portion of the transit system.”; ¶¶ 51-52 – Relevant data is gathered, including sensor readings (which may include a time stamp, as seen in ¶¶ 114, 116), and forwarded to the location server.; figs. 11-13, ¶¶ 73, 77, 94-97, 116 – It is understood that the location server must have access to time-related information in order to determine the dwell time and activities related to motion, thereby implying that the time stamp information is recorded in association with beacon information. Data is stored in various databases, i.e., tables.; fig. 11, ¶ 96 – “Location server 214 can include location data interface module 1108. Location data interface module 1108 is a component of location server 214 programmed to receive location data 1109 from various information sources. The location data can include geographic coordinates of stations of a transit system and geometry of routes of the transit system. Location data interface module 1108 can provide location data 1109 to connectivity determination module 1106 for performing “snap to route” operations, including mapping the measurements in the signal profile from a time dimension to a space dimension and adding geometry, including way points defined by latitude and longitude coordinates, to the belief state. Output of connectivity determination module 1106 can be stored in connectivity database 1110.”).
[Claim 13] Millman discloses wherein the beacon signal recognizer is configured to store the beacon ID of each beacon signal received from the mobile device in a predetermined storage location of the signal management table according to the attribute corresponding to the beacon ID (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”).
[Claim 14] Millman discloses wherein the passenger status generator is further configured to store a start time as a first time when the passenger status generator determines a passenger’s current status for the first time and an end time as a time when the passenger status generator determines a passenger’s current status for a last time during a passenger journey in a passenger status history table comprised in the data storage unit (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; fig. 6, ¶¶ 33, 63-73 – Shows beacon information at various time intervals corresponding to time in minutes. Details of each point, including a start and a destination point, in the user’s journey are recorded in the location server via the sampling device of the user.; ¶¶ 37, 121 – The user’s journey can be overlaid on a transit map.; ¶ 79 – “The location server can provide connectivity data as described in both FIG. 7B and FIG. 7C to a user device. The user device can use the connectivity data to estimate a location of the user device and a time to destination. For example, if the user device determines that a travel time between station 702 and 704 is ten minutes, and, based on location fingerprint of station 704, that the user device has stayed at station 704 for one minute, the mobile device can determine that, 15 minutes later, the location of the mobile device will be less than halfway between station 704 and station 706, and that an estimated time to destination station 710 will be one minute remaining dwelling time at station 704 plus 30 minutes from station 704 to station 706, plus two minutes at station 706, plus 45 minutes to station 710, which is 78 minutes.”; ¶¶ 55, 111 – Histogram and fingerprint information may be used to project transit activity.; fig. 6 – A historical account of user movement is tracked.).
[Claim 15] Millman discloses a journey validator configured to store a travel start station as a location where a passenger starts a journey and a travel end station as a location where a passenger ends a journey in a journey history table comprised in the data storage (¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; fig. 6, ¶¶ 33, 63-73 – Shows beacon information at various time intervals corresponding to time in minutes. Details of each point, including a start and a destination point, in the user’s journey are recorded in the location server via the sampling device of the user.; ¶¶ 37, 121 – The user’s journey can be overlaid on a transit map.).
[Claim 16] Millman discloses a system which includes the apparatus according to claim 1 (please see the rejection of claim 1 above, which is hereby incorporated by reference), a passenger mobile device comprising a beacon signal detector, a beacon installed on a stationary object configured to send a beacon signal comprising a beacon ID and a beacon installed on a another object configured to send a beacon signal comprising a beacon ID (¶ 34 – “For example, mobile device 102 can pass station 1 at a given time. While passing station 1, a wireless receiver of mobile device 102 may detect RF signals of one or more wireless access points (APs). Mobile device 102 can determine a received signal strength indication (RSSI) for each detected signal and an identifier of each AP. Mobile device 102 can match the identifiers of the APs, the RSSIs, or both to the location fingerprint data and identify a station that has a location fingerprint data that matches the identifiers of APs or RSSIs. For example, the location fingerprint data can include a station “Station 1” associated with a media access control (MAC) address X identifying an AP that is detectable at “Station 1.” Mobile device 102 can detect an RF signal including MAC address X. By matching the MAC address in the location fingerprint data and the detected RF signal, mobile device 102 can determine that mobile device 102 passed station “Station 1.””; ¶ 36 – “Mobile device 102 can display user interface 104 to a user. User interface 104 can include prompt 106. Prompt 106 can include recommendation 108 indicating a next train for a user carrying mobile device 102 to take.”).
Millman does not explicitly disclose wherein another beacon is installed on a moving object. However, Han discloses that a signal strength sequence may be detected, using signal sources disposed at a stop or a vehicle in the travel route (Han: abstract, ¶¶ 42-45). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein another beacon is installed on a moving object because “a vehicle scheduling strategy corresponding to a travel route can be determined based on a signal strength sequence of a detection signal detected by scanning the travel route by a user terminal, thereby accurately determining a vehicle scheduling strategy in the travel route.” (Han: ¶ 25) This would have enhanced Millman’s ability to track users on their travel routes.
[Claim 17] Millman discloses a method for determining a passenger status (abstract) comprising:
receiving, from a mobile device, a beacon signal including a beacon ID which the mobile device received from a beacon (¶ 34 – “For example, mobile device 102 can pass station 1 at a given time. While passing station 1, a wireless receiver of mobile device 102 may detect RF signals of one or more wireless access points (APs). Mobile device 102 can determine a received signal strength indication (RSSI) for each detected signal and an identifier of each AP. Mobile device 102 can match the identifiers of the APs, the RSSIs, or both to the location fingerprint data and identify a station that has a location fingerprint data that matches the identifiers of APs or RSSIs. For example, the location fingerprint data can include a station “Station 1” associated with a media access control (MAC) address X identifying an AP that is detectable at “Station 1.” Mobile device 102 can detect an RF signal including MAC address X. By matching the MAC address in the location fingerprint data and the detected RF signal, mobile device 102 can determine that mobile device 102 passed station “Station 1.””; ¶ 36 – “Mobile device 102 can display user interface 104 to a user. User interface 104 can include prompt 106. Prompt 106 can include recommendation 108 indicating a next train for a user carrying mobile device 102 to take.”);
reading a position ID and an attribute corresponding to the beacon ID indicating whether a beacon is installed on a moving object or a stationary object from a storage (¶ 107 -- The signal source can be a beacon.; ¶¶ 34, 67 – The various access points (APs) are also examples of beacons.; ¶ 57 – “The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 38 – “Mobile device 102 can move location marker 112 along a route of the transmit system, even when GPS signals are unavailable, upon determining that (1) mobile device 102 left Station 1, (2) a motion sensor indicates that mobile device 102 is moving, and (3) a barometer reading indicates that mobile device 102 is underground.”; ¶ 34 – “For example, mobile device 102 can pass station 1 at a given time. While passing station 1, a wireless receiver of mobile device 102 may detect RF signals of one or more wireless access points (APs). Mobile device 102 can determine a received signal strength indication (RSSI) for each detected signal and an identifier of each AP. Mobile device 102 can match the identifiers of the APs, the RSSIs, or both to the location fingerprint data and identify a station that has a location fingerprint data that matches the identifiers of APs or RSSIs. For example, the location fingerprint data can include a station “Station 1” associated with a media access control (MAC) address X identifying an AP that is detectable at “Station 1.” Mobile device 102 can detect an RF signal including MAC address X. By matching the MAC address in the location fingerprint data and the detected RF signal, mobile device 102 can determine that mobile device 102 passed station “Station 1.””; ¶ 36 – “Mobile device 102 can display user interface 104 to a user. User interface 104 can include prompt 106. Prompt 106 can include recommendation 108 indicating a next train for a user carrying mobile device 102 to take.” Station, business, platform, etc. identifications are examples of indicators of access points/beacons that are stationary objects.; ¶ 107 -- “The sensor readings can include readings from at least one of an accelerometer, a magnetometer, a barometer, a gyroscope, a light sensor, a sound pressure sensor, or a radio receiver coupled to the sampling device. In some implementations, the sensor readings are measurements of strength of radio RF signals of a signal source that are detectable at the portion of the transit system. The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source. The identifiers can be MAC addresses of the signal sources.”; ¶ 114 – “The location server can obtain (1402) sensor readings that are taken by a sampling device in a transit system that includes a route, stations on the route, and one or more platforms at each station. Each sensor reading can be associated with a timestamp and a tag indicating on which portion of the transit system the reading was taken. The sensor readings can be readings of inertial sensor indicating motion states of the sampling device. The inertial sensor can include an accelerometer or a gyroscope.”; ¶ 51 – “The signal measurements can be associated with one or more identifiers of one or more signal sources. An identifier of a signal source can be a MAC address of the signal source, or any other identifier that can uniquely identify the signal source. In some implementations, the sampling device can associate other sensor readings with the signal measurements. The sampling device can collect the signal measurements repeatedly for a pre-specified period of time, e.g., five minutes. The sampling device may be moving, so each time the sampling device takes measurements from multiple signal sources that are in fixed locations, the values of the measurements may be different from measurements of an earlier time.”);
storing the beacon signal strength for each beacon signal received from a beacon installed on a moving object or a stationary object during the predefined time interval in the storage (¶ 118 – “For example, the location server, or sampling device, can determine that the mobile device entered an underground station upon determining an increase in air pressure, a decrease in light, and a loss of GPS signals. The last known location, according to the GPS signals, can match a location of the first station as stored in a location database. The location server can then determine that a radio receiver of the sampling device detected a signal pattern of RSSIs of one or more access points that matches a location fingerprint associated with the first platform by matching the signal patterns with location fingerprints of various parts of the first station.”; fig. 5A; ¶ 56 – “FIG. 5A illustrates exemplary techniques of determining location fingerprint data from signal profiles. A location server, e.g., location server 214, can receive measurements from one or more sampling devices, e.g., sampling device 202. The location server can determine signal profiles 502, 504, and 506 from the received measurements. Signal profile 502 can be associated with a first station, Station 1. Signal profiles 504 and 506 can be associated with a first platform and a second platform of a second station, Station 2, respectively. Signal profiles 504 and 506 can correspond to a same set of signal sources. Signal profile 502 can correspond to a different set of signal sources.”; ¶ 57 – “The location server can determine location fingerprint data 508 from signal profiles 502, 504, and 506. Location fingerprint data 508 can include location fingerprints 510, 512, and 514, corresponding to signal profiles 502, 504, and 506, respectively. The location server can designate location fingerprints 510, 512, and 514 as location fingerprints of the first station, the first platform of the second station, and the second platform of the second station, respectively. The location server can store the location fingerprints 510, 512, and 514, in association with their respective transit system identifiers, station identifiers, platform identifiers, and signal source identifiers in location fingerprint database 516.”; ¶ 48 – “Being carried by the surveyor, sampling device 202 can move on platform 302 in a random pattern or following a pre-specified pattern, e.g., following path 306. While moving, sampling device 202 can record measurements of signals detected by sampling device 202, e.g., RF signals from signal source 206. In addition, in some implementations, sampling device 202 can record readings from sensors other than RF receivers. For example, sampling device 202 can record sound level, air pressure level, or magnetic field. Sampling device 202 can associate the measurements with an identifier. A gradual increase in sound level, air pressure level, and magnetic field disturbance may indicate that a train is approaching the station where platform 302 is located. Likewise, a gradual decrease in those readings may indicate that a train is departing the station. Sampling device 202 can associate the readings with the signal measurements. Sampling device 202 can submit the measurements and associated readings to a location server.”; ¶¶ 94-100 – The various pieces of information of interest are stored in databases, i.e., tables.; ¶ 107 – “The signal source can be a cell site of a cellular communications network, a wireless access point, or a Bluetooth™ low energy (BLE) beacon. Each measurement can be associated with an identifier of a corresponding signal source.” The signal source can be a beacon.; ¶ 34 – The various access points (APs) are also examples of beacons.; ¶ 51 – “The signal measurements can be associated with one or more identifiers of one or more signal sources. An identifier of a signal source can be a MAC address of the signal source, or any other identifier that can uniquely identify the signal source. In some implementations, the sampling device can associate other sensor readings with the signal measurements. The sampling device can collect the signal measurements repeatedly for a pre-specified period of time, e.g., five minutes.”);
determining a passenger's current status based on the beacon signal strength and/or a previous passenger status (abstract – A location of a user is determined.; ¶¶ 113-122 – Location of a user and if the user is at a stop or in motion are determined.; ¶ 159 – “Each of the above identified instructions and applications can correspond to a set of instructions for performing one or more functions described above.”; ¶ 51 – “The signal measurements can be associated with one or more identifiers of one or more signal sources. An identifier of a signal source can be a MAC address of the signal source, or any other identifier that can uniquely identify the signal source. In some implementations, the sampling device can associate other sensor readings with the signal measurements. The sampling device can collect the signal measurements repeatedly for a pre-specified period of time, e.g., five minutes. The sampling device may be moving, so each time the sampling device takes measurements from multiple signal sources that are in fixed locations, the values of the measurements may be different from measurements of an earlier time.”).
Millman does not explicitly disclose determining a beacon signal strength based on a moving object beacon signal strength and a stationary object beacon signal strength by building a sum of a number of received beacon IDs from the beacons which are installed on a moving object or a stationary object during a predefined time interval, wherein the moving object beacon signal strength is determined by counting a number of beacon IDs of beacon signals received from moving objects during the predefined time interval and the stationary object beacon signal strength is determined by counting a number of beacon IDs of beacon signals received from stationary objects during the predefined time interval.
Millman evaluates a signal strength of a corresponding signal source, including a beacon (Millman: ¶¶ 111, 130; claim 13). Like Millman, Flores assesses signal strength. Regarding the determination of a sum of the number of beacon IDs, Flores determines the relative signal quality at a location based on a total number of beacons with signal strength over a defined threshold, such as a predefined minimum RSSI (Flores: ¶¶ 31, 39, 46, 48, 49, 51, 54). Additionally, Han discloses that a signal strength sequence may be detected, using signal sources disposed at a stop (i.e., at a stationary object) or on a vehicle in the travel route (i.e., on a moving object) (Han: abstract, ¶¶ 42-45), thereby providing additional suggestion that Flores’ correlation of a number of detected beacons indicating a sufficiently strong signal strength can be applied to any type of beacon, including stationary and moving beacons. Flores simply provides Millman with an approach to assessing signal strength. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman to determine a beacon signal strength based on a moving object beacon signal strength and a stationary object beacon signal strength by building a sum of a number of received beacon IDs from the beacons which are installed on a moving object or a stationary object during a predefined time interval, wherein the moving object beacon signal strength is determined by counting a number of beacon IDs of beacon signals received from moving objects during the predefined time interval and the stationary object beacon signal strength is determined by counting a number of beacon IDs of beacon signals received from stationary objects during the predefined time interval in order to facilitate more accurate correlations among the various fingerprints, signal profiles, and user location through a more cost effective and time efficient application of training data to the models (as suggested in ¶ 4-9 of Flores) and because “a vehicle scheduling strategy corresponding to a travel route can be determined based on a signal strength sequence of a detection signal detected by scanning the travel route by a user terminal, thereby accurately determining a vehicle scheduling strategy in the travel route.” (Han: ¶ 25) This would have enhanced Millman’s ability to track users on their travel routes.
[Claim 18] Millman, Han, and Flores each disclose a computer program product stored in a memory comprising instructions which, when carried out by a computer, causes the computer (Millman: ¶¶ 134-140; Han: ¶¶ 190-199; Flores: ¶ 65) to perform the (respectively disclosed aspects of the) method according to claim 17 (please see the rejection of claim 17 above, which is hereby incorporated by reference).
Claims 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Millman et al. (US 2016/0094950) in view of Han et al. (US 2020/0279203 in view of Flores et al. (US 2021/0216906), as applied to claim 1 above, in view of Nishimura (US 2019/0120927).
[Claim 9] Millman does not explicitly disclose wherein the beacon signal recognizer is configured to determine the beacon signal strength after the expiry of a second predetermined time interval which is equal to or longer than a first predetermined time interval. Nishimura explains the behavior of signals in multiple transmissions in the following excerpts:
[0074] In Modification 1, when the receiving unit 22 in each of the receivers 20a to 20g receives the beacon, the control unit 24 sends the first reception information after the lapse of a waiting time that is set to be longer as the received beacon has lower signal strength. However, the control unit 24 stops sending of the first reception information when the second reception information is received from the other receiver during the lapse of the waiting time after receiving the beacon.
[0085] In this case, however, because the reception information (second reception information) from the other receiver 20a is received during the lapse of the waiting time 2, which is longer than the waiting time 1, after receiving the beacon, the control unit 24 compares the signal strength (first signal strength) of the beacon received in step S25 with the signal strength (second signal strength) indicated by the information contained in the second reception information received from the other receiver 20a (S26). In this case, the control unit 24 determines, as a result of the comparison, that the second signal strength is higher than the first signal strength, and hence stops the sending of the first reception information (S27). The control unit 24 sends (transfers), from the sending unit 23, the reception information (second reception information) received from the other receiver 20a.
[0092] In this case, however, because the reception information (second reception information) from the other receiver 2a is received during the lapse of the waiting time 2, which is longer than the waiting time 1, after receiving the beacon, the control unit 24 confirms that the sequence number (here “Seq#5”) contained in the beacon received in step S35 matches with the sequence number (here “Seq#5”) contained in the second reception information received from the receiver 20a, and then executes the comparison between the first signal strength and the second signal strength as in Modification 2 for the beacons containing the same sequence number (S36). In this case, the control unit 24 determines, as a result of the comparison, that the second signal strength is higher than the first signal strength, and hence stops the sending of the first reception information (S37). The control unit 24 sends (transfers), from the sending unit 23, the reception information (second reception information) received from the other receiver 20a. (Emphasis added)
The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the beacon signal recognizer is configured to determine the beacon signal strength after the expiry of a second predetermined time interval which is equal to or longer than a first predetermined time interval in order to provide sufficient time for a second signal to be received so that more relevant and stronger signal information may be selected and relied upon, thereby minimizing congestion of data transmission in the network (as suggested in ¶ 12 of Nishimura).
[Claim 10] Millman does not explicitly disclose wherein the beacon signal recognizer is configured to reset the beacon signal management table after expiry of a second predetermined time interval. Nishimura explains the behavior of signals in multiple transmissions in the following excerpts:
[0074] In Modification 1, when the receiving unit 22 in each of the receivers 20a to 20g receives the beacon, the control unit 24 sends the first reception information after the lapse of a waiting time that is set to be longer as the received beacon has lower signal strength. However, the control unit 24 stops sending of the first reception information when the second reception information is received from the other receiver during the lapse of the waiting time after receiving the beacon.
[0085] In this case, however, because the reception information (second reception information) from the other receiver 20a is received during the lapse of the waiting time 2, which is longer than the waiting time 1, after receiving the beacon, the control unit 24 compares the signal strength (first signal strength) of the beacon received in step S25 with the signal strength (second signal strength) indicated by the information contained in the second reception information received from the other receiver 20a (S26). In this case, the control unit 24 determines, as a result of the comparison, that the second signal strength is higher than the first signal strength, and hence stops the sending of the first reception information (S27). The control unit 24 sends (transfers), from the sending unit 23, the reception information (second reception information) received from the other receiver 20a.
[0092] In this case, however, because the reception information (second reception information) from the other receiver 2a is received during the lapse of the waiting time 2, which is longer than the waiting time 1, after receiving the beacon, the control unit 24 confirms that the sequence number (here “Seq#5”) contained in the beacon received in step S35 matches with the sequence number (here “Seq#5”) contained in the second reception information received from the receiver 20a, and then executes the comparison between the first signal strength and the second signal strength as in Modification 2 for the beacons containing the same sequence number (S36). In this case, the control unit 24 determines, as a result of the comparison, that the second signal strength is higher than the first signal strength, and hence stops the sending of the first reception information (S37). The control unit 24 sends (transfers), from the sending unit 23, the reception information (second reception information) received from the other receiver 20a. (Emphasis added)
Additionally, Nishimura explains that a waiting time is determined based on the first established beacon period and a table is used to document and facilitate the analysis (Nishimura: ¶ 99 – “More specifically, a function or a table used for converting the signal strength of the beacon to the waiting time is prepared so as to provide the maximum value of the waiting time after the conversion, which is smaller than the beacon period. Alternatively, the control unit 24 multiplies the waiting time resulting from referring to a function or a table by a coefficient depending on the beacon period, thus correcting the waiting time such that a maximum value of the obtained waiting time is smaller than the beacon period.”). In other words, the table presents information dependent on the initial transmission time to determine the minimum waiting time for a subsequent transmission. Once the evaluation is performed for a first transmission and a corresponding waiting time, a decision as to which signal to use is made. Beacon positions are sent repeatedly (Nishimura: ¶¶ 48, 50), thereby implying that the process of identifying a time period for a first transmission and a corresponding waiting time would be repeated as well. The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the beacon signal recognizer is configured to reset the beacon signal management table after expiry of a second predetermined time interval so that the positions of multiple objects interacting with multiple beacons may be consistently evaluated, continually providing sufficient time for a second signal to be received so that more relevant and stronger signal information may be selected and relied upon, thereby minimizing congestion of data transmission in the network (as suggested in ¶ 12 of Nishimura).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Millman et al. (US 2016/0094950) in view of Han et al. (US 2020/0279203 in view of Flores et al. (US 2021/0216906), as applied to claim 1 above, in view of Batra et al. (US 2017/0374641).
[Claim 11] Millman does not explicitly disclose wherein the beacon signal recognizer is configured to reset the beacon signal management table by overwriting the beacon IDs and time stamps previously stored in the beacon signal management table. Batra discloses:
[0054] If the determined beacon location duration is greater than the threshold duration, then it is determined whether the beacon 115 is in the same location at block 330. If the beacon 115 is not in the same location, then a new entry in a database (such as the long-term database) may be made at block 335 by the server 130 and/or the ticketing system 120. The new entry in the database may include the beacon 115 identification code, the identification code of the hub 110 or the user device 125 that received the beacon's signal, the location of the beacon 115, the temperature of the beacon 115, signal strength of the beacon 115, a battery power indication of the beacon 115, a time stamp, whether the beacon 115 is still fixed to the item, and/or additional and/or alternative information. If the beacon 115 is in the same location, then the existing entry in the database may be updated at block 340 by the server 130 and/or the ticketing system 120. For example, the entry may include the new temperature of the beacon 115, the new signal strength of the beacon 115, the new battery power indication of the beacon 115, the new time stamp, and/or additional and/or alternative information. In some embodiments, the old information may be overwritten with the new information. In some embodiments, the old information may be maintained. (Emphasis added)
The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the beacon signal recognizer is configured to reset the beacon signal management table by overwriting the beacon IDs and time stamps previously stored in the beacon signal management table in order to preserve storage resources by only maintaining needed information in storage.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Millman et al. (US 2016/0094950) in view of Han et al. (US 2020/0279203 in view of Flores et al. (US 2021/0216906), as applied to claim 1 above, in view of Otis et al. (US 2015/0379576)
[Claim 12] Millman does not explicitly discloses wherein the beacon signal strength is represented by discrete values ranging from a minimum of the value of zero to a maximum value which corresponds to a number of first predetermined time intervals within a second predetermined time interval. However, Millman does explain that “[s]ignal profile 400 can include one or more discrete or continuous probability distributions of number of measurements associated with the station or platform.” (Millman: ¶ 53) Millman further states, “Each of histogram 402 and histogram 404 can represent a distribution of number of measurement over RSSI of the corresponding signal source. Each histogram can include discrete intervals, referred to as bins, that are defined by signal strength. For example, a first bin can include measurements of the RSSIs between −100 decibel-milliwatts (dBm) and −90 dBm, a second bin can include measurements of the RSSIs between −90 dBm and −80 dBm, and so on. The frequency in each bin can be a number of measurements of RSSI values that fall into the bin.” (Millman: ¶ 54) In other words, the range of signal values correlates to a number of measured signal values that fall into each bin of a respectively defined range, which suggests a correlation between a number of signal data points in one profile vs. the number of signal data points in a different profile. Figure 4 of Millman shows a minimum and maximum range of RSSI for each of various signal sources (Millman: ¶¶ 53-55). While Millman does not explicitly disclose a minimum value of zero for its range of values, Otis explains that out-of-range signals may be assigned a signal strength of zero (Otis: ¶ 65). The Examiner submits that it would have been obvious to one of ordinary skill in the art before the effective filing date of Applicant’s invention to modify Millman wherein the beacon signal strength is represented by discrete values ranging from a minimum of the value of zero to a maximum value which corresponds to a number of first predetermined time intervals within a second predetermined time interval in order to facilitate the more accurate extrapolation and/or interpolation of relevant patterns (as suggested in ¶ 55 of Millman) while allowing for adaptation of the signal values to the most relevant scale of values for a given situation.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUSANNA M DIAZ whose telephone number is (571)272-6733. The examiner can normally be reached M-F, 8 am-4:30 pm.
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/SUSANNA M. DIAZ/
Primary Examiner
Art Unit 3625A