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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4/27/26 has been entered.
Response to Amendment
Receipt is acknowledged of applicant’s amendment filed on 4/27/26. Claim12 amended. Claims 1-22 are pending and an action on the merits is as follows.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 2, 8-14, and 19-22 are rejected under 35 U.S.C. 102a1 as being anticipated by Zelman US Publication No. 2021/0257074.
Re Claim 1, Zelman et al. discloses a method for determining locations of internet of things (loT) tags, comprising:
receiving, during a predefined time window, packets from a plurality of gateways, wherein a received packet includes at least sensing signals transmitted from the loT tags (P29 -30, P33, P34, P37, P38 P44, P50, P32, see claim 1, (5) gateways 120-1 through 120-5 , each of which is deployed at a different station , the various stations are in different physical locations each gateway 120 is configured to receive signals from the IoT tags 110-1 through 110-n in the respective station, encapsulate those signals together with additional data in data packets, and transmit the data packets to the cloud computing platform 130 to be processed by the server 140);
determining an affinity among the loT tags based on the sensing signals received from the plurality of gateways (P39, based on an RF values from multiple co-located IOT tags , similar sense RF values) ;
determining locations of loT tags based on the determined affinity and the sensing signals received from the plurality of gateway s (P39 co-lation sensing),
wherein a location of an loT tag is a probability that an loT tag is located in proximity to a gateway of the plurality of gateways (P13. P69-70 with respect to a location of the gateway tracing of a location of the vial );
and reporting the determined locations to a user terminal (P36, P40, P74, P75).
Re Claim 2, Zelman discloses the method of claim 1, further comprising clustering loT tags based on their determined locations (Fig. 1) .
Re Claim 8, Zelman disclose the method of claim 1, wherein an loT tag is a wireless battery-less loT tag communicating with a gateway using a low-power communication protocol (P76).
Re Claim 9, Zelman disclose the method of claim 1, wherein the method is performed by a server, wherein each of the gateways communicate with the server over the Internet (P36).
Re Claim 10, Zelman disclose the method of claim 1, wherein a packet includes sensing signals transmitted by an loT tag, an identifier of the loT tag transmitting the sensing signals, and an identifier of the gateway (P69, P36).
Re Claim 11, Zelman disclose the method of claim 1, wherein a sensing signal includes any one of: a frequency word, a received signal strength indicator (RSSI), a digitally controlled oscillator (DCO) signal (P69, P38).
Re Claim 12, Zelman disclose a non-transitory computer readable medium having stored thereon instructions for causing a processing circuitry to execute a process for determining locations of internet of things (loT) tags, the process comprising:
receiving, during a predefined time window, packets from a plurality of gateways, wherein a received packet includes at least sensing signals transmitted from the loT tags (P29 -30, P33, P34, P37, P38 P44, P50, P32, see claim 1, (5) gateways 120-1 through 120-5 , each of which is deployed at a different station , the various stations are in different physical locations each gateway 120 is configured to receive signals from the IoT tags 110-1 through 110-n in the respective station, encapsulate those signals together with additional data in data packets, and transmit the data packets to the cloud computing platform 130 to be processed by the server 140);
determining an affinity among the loT tags based on the sensing signals received from the plurality of gateways (P39, based on an RF values from multiple co-located IOT tags , similar sense RF values);
determining locations of loT tags based on the determined affinity and the sensing signals received from the plurality of gateways,
wherein a location of an loT tag is a probability that an loT tag is located in proximity to a gateway of the plurality of gateways(P13, P39 P69-70);
and reporting the determined locations to a user terminal (P36, P40, P74, P75).
Re Claim 13, Zelman discloses a system for determining locations of internet of things (loT) tags, comprising: a processing circuitry; a memory connected to the processing circuitry and configured to contain a plurality of instructions that when executed by the processing circuitry configure the system to:
receive, during a predefined time window, packets from a plurality of gateways, wherein a received packets include at least sensing signals transmitted from the loT tags (P29 -30, P33, P34, P37, P38 P44, P50, P32, see claim 1, (5) gateways 120-1 through 120-5 , each of which is deployed at a different station , the various stations are in different physical locations each gateway 120 is configured to receive signals from the IoT tags 110-1 through 110-n in the respective station, encapsulate those signals together with additional data in data packets, and transmit the data packets to the cloud computing platform 130 to be processed by the server 140);
determine an affinity among the loT tags based on the sensing signals received from the plurality of gateways (P39, based on an RF values from multiple co-located IOT tags , similar sense RF values);
determine locations of loT tags based on the determined affinity and the sensing signals received from the plurality of gateways(P39 co-lation sensing), wherein a location of an loT tag is a probability that an loT tag is located in proximity to a gateway of the plurality of gateways (P13, P69-70 with respect to a location of the gateway tracing of a location of the vial;
and report the determined locations to a user terminal (P36, P40, P74, P75).
Re Claim 14, Zelman disclose the system of claim 13, wherein the system is further configured to: cluster loT tags based on their determined locations (fig. 1).
Re Claim 19, Zelman disclose The system of claim 18, wherein the probabilistic graphical model is a dynamic Bayesian network (DBN) (P51).
Re Claim 20, Zelman disclose the system of claim 13, wherein an loT tag is a wireless battery- less loT tag communicating with a gateway using a low-power communication protocol(P76).
Re Claim 21, Zelman disclose the system of claim 13, wherein a packet includes sensing signals transmitted by an loT tag, an identifier of the loT tag transmitting the sensing signals, and an identifier of the gateway (P69, P36).
Re Claim 22, Zelman disclose the system of claim 13, wherein a sensing signal includes any one of: a frequency word, a received signal strength indicator (RSSI), a digitally controlled oscillator (DCO) signal (P69, P38, P93).
Claim(s) 3-5, 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Zelman US Publication No. 2021/0257074 in view of Freeman et al. US Publication No. 2022/0207473 cited in previous action.
Re Claims 3-5, Zelman discloses the method of claim 1, wherein receiving, during a predefined time window, packets from a plurality of gateways.
Zelman fails discloses for each of the loT tags, creating a vector of an average value of sensing signals transmitted by each of the loT tags as received by each of the gateways; and forming a sensing signal matrix based on the created vectors.
However Freeman discloses for each of the loT tags, creating a vector of an average value of sensing signals transmitted by each of the loT tags as received by each of the gateways; and forming a sensing signal matrix based on the created vectors (P97, P72, P31; Fig. 7c).
Freeman further discloses computing the distance metric using any one of: a Euclidean distance function, and a cosine similarity (P97, P101).
Given the teachings of Freeman 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 teachings of Zelman with for each of the loT tags, creating a vector of an average value of sensing signals transmitted by each of the loT tags as received by each of the gateways; and forming a sensing signal matrix based on the created vectors.
Doing so would improve location sensing technologies because they include new functionality and components that improve the accuracy of location sensing systems, among other things (P20).
Re-claims 15-17, Zelman discloses the system of claim 13.
Zelman fails to disclose wherein the system is further configured to: for each of the IoT tags, create a vector of an average value of sensing signals transmitted by each of the IoT tags as received by each of the gateways; and form a sensing signal matrix based on the created vectors.
Freeman discloses wherein the system is further configured to: for each of the IoT tags, create a vector of an average value of sensing signals transmitted by each of the IoT tags as received by each of the gateways; and form a sensing signal matrix based on the created vectors (P97, P72, P31; Fog. 7c).
Freeman discloses wherein the system is further configured to: for each pair of IoT tags, compute a distance metric between the pair of IoT tags, wherein the distance metric is computed using the respective average values of sensing signals included in the sensing signal matrix; and form an affinity matrix based on the distance metric (P97; Fig. 7c).
Freeman also discloses computing the distance metric using any one of: a Euclidean distance function, and a cosine similarity (P97, P101).
Given the teachings of Freeman 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 teachings of Zelman with wherein the system is further configured to: for each of the IoT tags, create a vector of an average value of sensing signals transmitted by each of the IoT tags as received by each of the gateways; and form a sensing signal matrix based on the created vectors.
Doing so would improve location sensing technologies because they include
new functionality and components that improve the accuracy of location sensing
systems, among other things (P20).
Allowable Subject Matter
Claims 6, 7, 18 and 19 are allowed.
The following is a statement of reasons for the indication of allowable subject matter in Re Claim 6: none of the cited prior art of record, discloses, teach or fairly suggest at least wherein determining locations of loT tags further comprises: applying a probabilistic graphical model to estimate a location matrix of a current time window, wherein the probabilistic graphical model is applied on the affinity matrix determined for a pervious time window, the sensing signal matrix of the current time window, and a location matrix of a pervious time window, wherein the location matrix includes probabilities of each loT tag located in a proximity to each of the gateways.
The following is a statement of reasons for the indication of allowable subject matter in Re Claim 18: none of the cited prior art of record, discloses, teach or fairly suggest at least , wherein the system is further configured to: apply a probabilistic graphical model to estimate a location matrix of a current time window, wherein the probabilistic graphical model is applied on the affinity matrix determined for a pervious time window, the sensing signal matrix of the current time window, and a location matrix of a pervious time window, wherein the location matrix includes probabilities of each loT tag located in a proximity to each of the gateways.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 12, and 13 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The following reference is cited but not relied upon:
ZUBERI discloses a set of ID sensors can be employed in an inventory control environment and subsets of the ID sensors can collectively sense tagged items in shared space
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SONJI N. JOHNSON
Examiner
Art Unit 2876
/SONJI N JOHNSON/Primary Examiner, Art Unit 2876
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