Part III DETAILED ACTION
1. The present application is being examined under the pre-AIA first to invent provisions. This application has been examined. Claims 1-20 are pending in this application.
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
2. Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated
by Karounos (WO-2021/207782-A1).
With regard claim 1, Karounos teaches a system for animalia identification and species-specific interaction (reads on the abstract, concern with detection of pest species , the pest represent the animal species) comprising: presence detector configured to detect a presence of animalia (reads on page 2, lines 30-34 and page 9, lines 28-30); a biometric sensor configured to collect biometric data for identification of the animalia (reads on page 3, line 30 thru page 4, line 23, biometric such as wing noise or noise call) ; an acoustic output device configured to emit an acoustic sound; a processor communicatively coupled to the presence detector, the biometric sensor, and the acoustic output device (reads on page 8, lines 7-9, the responses of the pest species to the influencing factor are recorded by the sensing means and communicated to an artificial intelligence or machine learning processor); wherein the biometric sensor is further configured communicate the biometric data to the processor (see P. 4, Iines 15-18- the identifying means is combined with the sensor which detects a sound associated with the pest, such as the noise call of the pest, the pest identified then compares the noise call with those in the first reference library of noise calls, in order to identify the pest, p. 4, Iines 19-21, the first reference library is preferably a database of pest features, preferably held in a remote cloud, with which the identifying means communicates using a suitable processor and communication link which enables data exchange); wherein the processor is configured to: activate the biometric sensor based on the detection of the presence of the animalia (see page 4, Iines 10-12, e.g. the identifying means may be a video camera which is activated by the sensor to record the pest feature, being in this example images of the pest in flight); receive the biometric data collected by the biometric sensor (reads on claim 1, an image is received or captured by the sensor for sensing presence of a pest in a selected location); analyze the biometric data to identify species of the animalia (reads on claim 1, a sensor for sensing presence of a pest in a selected location; identifying means for capturing a pest feature, analyzing by comparing the pest feature with features in a first reference library and therefore identifying the pest species); and instruct the acoustic output device to emit the acoustic sound, wherein the acoustic sound is selected from a set of acoustic sounds associated with the identified species of the animalia (reads on p 5, lines 34-36, sound(s) are emitted by speaker 22 by a sequence of sounds is a gunshot sound or a predator sound for the species to identify the pest or animal related to the associated pest or animal sound). ;
With regard claim 2, Karounos further teaches wherein the presence detector is a motion sensor, thermal detector, camera, or a combination thereof (reads on page 3, line 30 thru page 4, line 4 and page 8, line 29-32, wherein each unit may contain a camera activated by a motion detector).
With regard claim 3, Karounos further teaches biometric sensor is a camera configured to capture an image or a video of the animalia (reads on page 4, lines 10-14 and page 8, line 29-32, wherein each unit may contain a camera activated by a motion detector).
With regard claim 4, Karounos further teaches wherein biometric sensor is a bioacoustic sensor configured to record sounds of the animalia (reads on page 3, line 30 thru page 4, line 14 , the system includes a plurality of sensors wherein each sensor may work with the identifying means to capture an image of the pest, a vocal signature of the pest and kinematics in relation to the pest, in order to identify the pest).
. With regard claim 5, Karounos further teaches wherein the sounds of the animalia comprise infrasonic sounds, human audible sounds, or ultrasonic sounds (see page 4, lines 15-18, the identified information is combined with the sensor which detects a sound associated with the pest, such as the noise call of the pest. Al, the identifying then comparing the noise call with those in the first reference library of noise calls, in order to identify the pest or animal).
With regard claim 6, Kundu further teaches wherein the processor is configured to use machine learning to perform analysis on the biometric data in order to identify the species of the animalia (see page 8, lines 7-10, it is particularly preferred that responses of the pest species to the influencing factor are recorded by the sensing means and communicated to an artificial intelligence or machine learning processor which accordingly changes the action of the means to reduce complacency).
With regard claim 7, Kundu further teaches wherein the acoustic sound emitted by the acoustic output device comprises infrasonic sound, human audible sound, or ultrasonic sound (see page 5, lines 5-7- e.g. if the pest bird is a rosella, the predator sound may be that of a peregrine falcon, a wedge tail short or a whistling kite (or any raptor)).
With regard claim 8, Kundu further teaches wherein the biometric sensor is further configured to record a reaction of the animalia to the acoustic sound (see page 5, lines 5-7, e.g., if the pest bird is a rosella, the predator sound may be that of a peregrine falcon, a wedge tail short or a whistling kite (or any raptor)).
With regard claim 9, Kundu further teaches, wherein the processor is further configured to update the set of acoustic sounds associated with the identified species of the animalia (inherently reads on abstract and page 2, lines 8-12, clearly different sounds are used based on the need of the region, different regions have different native pests or animals).
With regard claim 10, Kundu further teaches a visual output device coupled with the processor and configured to generate a visual signal, wherein the processor is further configured to instruct the visual output device to generate the visual signal, and wherein the visual signal is selected from a set of visual signals associated with the identified species of animalia (inherently reads on page 6, lines 21-36 and page 4, the camera or drone can captured an image and generate a visual signal from the captured images).
With regard claim 11, Kundu further teaches a wireless communication device configured to communicate the biometric data to an external device (reads on page 8, line 37 thru page 9, lines 1-2, the system may have the ability to use 4G/5G or Wi Fi to a gateway for connection to the cloud. Any artificial intelligence processor may be installed locally instead of or as well as on cloud infrastructure).
With regard claim 12, Kundu further teaches wherein the processor is further configured to instruct the acoustic output device to emit a preconfigured acoustic sound if the species of the animalia cannot be identified (see page 5, lines 28-30, Non-limiting examples of negative influencing factors which may be used in addition to those selected for the identified species are predator sounds (where the predator is not species-specific).
With regard to claims 13-20, the limitations of claims 13-30 are covered by the
limitations of claims 1-12 above.
Conclusion
3. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Purohit (2025/0076497) teaches a monitoring system for detecting emitted sounds to identify motion of an object.
Fichman et al. (2024/0090473) teaches an animal marking control system and method.
Azima-Sadjadi et al. (2021/0315186) teaches an intelligent dual sensory species specific recognition trigger system.
Sarzen (2021/0289755) teaches a method and system for using sound data to analyze health condition and welfare states in collections of farm animals.
4. Any inquiry concerning this communication or earlier communications from the
examiner should be directed to Gabriel I. Garcia whose telephone number is (571)
272-7434. The examiner can normally be reached Monday-Thursday from 8:000 AM-6:00 PM.. The
fax phone number for this group is (571) 273-8600.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's
supervisor, Benny Tieu can be reached on (571) 272-7490. The fax phone
number for the organization where this application or proceeding is assigned is 571-
273-8300.
Information regarding the status of an application may be obtained from the Patent
Application Information Retrieval (PAIR) system. Status information for published
applications may be obtained from either Private PAIR or Public PAIR. Status
information for unpublished applications is available through Private PAIR only. For
more information about the PAIR system, see http://pair-direct.uspto.gov. Should you
have questions on access to the Private PAIR system, contact the Electronic Business
Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO
Customer Service Representative or access to the automated information system, call
800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Any inquiry of a general nature or relating to the status of this application should be
directed to the Group receptionist whose telephone number is (571) 272-2600.
/Gabriel I Garcia/
Primary Examiner, Art Unit 2682
February 01, 2026