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 .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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) 1-4, 9-11, 16-17 and 21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Uleru et al. (Uleru et al., “Electro‐optical spiking neural networks using an enhanced optical axon with pulse amplitude modulation and automatic gain controller”, IET Optoelectron, 2023, Wiley, August 2023).
Regarding claim 1, Uleru et al. teaches in FIG. 1 a method of transmitting data by light communication, the method comprising: encoding a set of data values using one or more light emitters (the blue LED), wherein the set of data values is encoded through a temporal variation of light emitted by the one or more light emitters (Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate); recording, using an event-based sensor (the optical receiver of FIG. 1), a sequence of events including a pattern of events reflecting the temporal variation of the light emitted by the one or more light emitters; and processing the recorded sequence of events using a spiking neural network (Uleru et al. teaches in the title spiking neural networks) to obtain information indicative of the temporal variation of the light that was emitted by the one or more light emitters such that the set of data values that was encoded can be decoded from the temporal variation of the light emitted by the one or more light emitters (Uleru et al. teaches in FIG. 1 amplitude demodulator and synapses).
Regarding claim 2, Uleru et al. teaches in FIG. 1 a method of decoding a set of data values encoded into a temporal variation of light emitted by one or more light emitters (the blue LED), the method comprising: recording, using an event-based sensor (the optical receiver of FIG. 1), a sequence of events including a pattern of events reflecting the temporal variation of light emitted by the one or more light emitters (Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate); processing the recorded sequence of events using a spiking neural network (Uleru et al. teaches in the title spiking neural networks) to obtain information indicative of the temporal variation of the light emitted by the one or more light emitters; and decoding the set of data values encoded into the temporal variation of light emitted by the one or more light emitters from the obtained information indicative of the temporal variation of the light emitted by the one or more light emitters (Uleru et al. teaches in FIG. 1 amplitude demodulator and synapses).
Regarding claim 3, Uleru et al. teaches in FIG. 1 optical filter for removing at least some background noise.
Regarding claim 4, Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate equivalent to event frequency of instant claim.
Regarding claim 9, Uleru et al. teaches in FIG. 1 a system for transmitting data comprising: one or more light emitters configured to emit light (the blue LED), wherein the emitted light is configured to cause a set of data values to be transmitted is encoded into a temporal variation of light emitted by the one or more light emitters (Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate); and a decoder apparatus comprising: an event-based sensor (the optical receiver of FIG. 1) configured to record a sequence of events such that the recorded sequence of events includes a pattern of events reflecting the temporal variation of the light that was emitted by the one or more light emitters; and a processing unit configured to execute a spiking neural network (Uleru et al. teaches in the title spiking neural networks), wherein the spiking neural network is configured to obtain information indicative of the temporal variation of the light that was emitted by the one or more light emitters such that the set of data values encoded can be decoded from the obtained information indicative of the temporal variation of the light emitted by the one or more light emitters (Uleru et al. teaches in FIG. 1 amplitude demodulator and synapses).
Regarding claim 10, Uleru et al. teaches in FIG. 1 a system for decoding a set of data values encoded into a temporal variation of light emitted by one or more light emitters (the blue LED) comprising: an event-based sensor (the optical receiver of FIG. 1) configured to record a sequence of events such that the recorded sequence of events includes a pattern of events reflecting the temporal variation of the light emitted by the one or more light emitters (Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate); and a processing unit configured to execute a spiking neural network (Uleru et al. teaches in the title spiking neural networks), wherein the spiking neural network is configured to obtain information indicative of the temporal variation of the light emitted by the one or more light emitters, and wherein the processing unit is further configured to obtain the set of data values encoded from the obtained information indicative of the temporal variation of the light emitted by the one or more light emitters (Uleru et al. teaches in FIG. 1 amplitude demodulator and synapses).
Regarding claims 11, 16 and 21, Uleru et al. teaches in FIG. 1 optical filter for removing at least some background noise.
Regarding claim 17, Uleru et al. teaches on page 177, left col., 5th paragraph that the voltage generated by the sensors is converted into a spiking rate equivalent to event frequency of instant claim.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 8 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Uleru et al. (Uleru et al., “Electro‐optical spiking neural networks using an enhanced optical axon with pulse amplitude modulation and automatic gain controller”, IET Optoelectron, 2023, Wiley, August 2023) in view of Liu et al. (U.S. Patent Application Pub. 2017/0261975 A1).
Uleru et al. has been discussed above in regard to claims 1-4, 9-11, 16-17 and 21. The difference between Uleru et al. and the claimed invention is that Uleru et al. does not teach that the light communication is used to facilitate control of a vehicle when performing an automated manoeuvre, wherein the automated manoeuvre includes facilitating an autonomous landing manoeuvre for an aircraft. Liu et al. teaches in FIG. 1 a landing guidance system for an aerial drone by using light communication where a light source generates light signals to be received by the light sensors 104 and 106 installed at the bottom of the aerial drone 106. One of ordinary skill in the art would have been motivated to combine the teaching of Uleru et al. with the system of Uleru et al. because it is a practical application of the light communication system of Uleru et al. Thus it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system of Uleru et al. for a landing guidance system for an aerial drone, as taught by Liu et al.
Allowable Subject Matter
Claims 5-7, 12-13, 18-19 and 22 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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skl3 August 2026
/SHI K LI/Primary Examiner, Art Unit 2635
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