Description:TECHNICAL FIELD
The present disclosure relates generally to deterrent devices. More particularly, the present disclosure relates to an IOT-based deterrent system and a method thereof.
BACKGROUND
For decades, agriculture has stood as both the backbone and vulnerability of nations worldwide. In many regions, particularly in countries like India where agriculture serves as a primary source of livelihood for a significant portion of the population, farmers have grappled with persistent challenges that threaten their very sustenance. Among these challenges, the perennial menace posed by avian species, animals, and reptiles has been a longstanding issue. These creatures, while emblematic of the rich biodiversity surrounding farmlands, often wreak havoc on crops during critical stages of growth, from sowing to ripening. The depredation inflicted by birds and other animals translates into tangible economic losses, exacerbating the precarious financial situation of farmers who rely solely on their land for sustenance.
The conventional methods of crop protection have proven inadequate against the relentless onslaught of avian species and other crop-damaging creatures. Farmers have resorted to various means, from scarecrows to chemical deterrents, but these measures often fall short of providing comprehensive and sustainable solutions. As a result, the agricultural sector continues to grapple with significant losses, jeopardizing the livelihoods of millions and impeding efforts to achieve food security and economic prosperity. The persistent struggle against wildlife incursions has underscored the urgent need for innovative, technology-driven interventions capable of safeguarding crops effectively while promoting sustainable agricultural practices.
Thus, there is a need for a system, an apparatus, and a method capable of providing protection against such intruders that harm the crops or seeds, which demands a need for improvised technical solution that overcomes the aforementioned problems.
SUMMARY
In an aspect of the present disclosure, an IOT-based deterrent system is disclosed. The system includes an input unit, a plurality of sensors, processing circuitry and an alert unit. The input unit includes a plurality of sensors configured to sense signals representing presence of a plurality of intruders, such that the plurality of intruders including at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region. The processing circuitry is coupled to the input unit and configured to an identify at least one intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques. The processing circuitry may be further configured to determine, upon identification, a limiting frequency associated with the at least one intruder of the plurality of intruders and generate an alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders. The alert unit is coupled to the processing circuitry, and configured to generate, upon generation of the alert signal, a plurality of sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders.
In some aspects of the present disclosure, the input unit further includes a plurality of imaging devices that are configured to capture a plurality of images of the region such that the plurality of sensors sense signals representing the presence of the plurality of intruders based on the plurality of images.
In some aspects of the present disclosure, the system further includes a frame, a body, and an upper portion. The upper portion is coupled to the body such that the plurality of imaging devices are disposed on the upper portion, such that the upper portion is rotatably coupled to the body such that rotation of the upper portion with respect to the body facilitates rotation of the plurality of imaging devices that facilitates the plurality of imaging devices to capture a 360 degrees (3600) view of the region.
In some aspects of the present disclosure, the system further includes an output unit that is coupled to the processing circuitry, and configured to display one of, (i) one or more details of the at least one intruder of the plurality of intruders, (ii) a first numerical value associated to the limiting frequency of the at least one intruder of the plurality of intruders, (iii) a second numerical value associated to a sound frequency of the plurality of sound frequencies for the at least one intruder of the plurality of intruders.
In some aspects of the present disclosure, further includes a database that is coupled to the processing circuitry and configured to store a first set of images associated with the region and a second set of images associated with the plurality of intruders.
In some aspects of the present disclosure, the processing circuitry implements a classifier model to identify the at least one intruder of the plurality of intruders, such that to train the classifier model the processing circuitry is configured to (i) receive the first and second sets of images, (ii) pre-process the first and second sets of images to generate a set of pre-processed images, and (iii) train the classifier model by way of the set of pre-processed images, such that the classifier model is optimized by (a) scheduling a learning rate of the classifier model by employing a decay function and (b) applying model fitting to the classifier model by way of early stops and checkpoints callbacks.
In some aspects of the present disclosure, the processing circuitry is configured to generate the alert signal by way of a frequency division multiplexing (FDM) technique.
In some aspects of the present disclosure, the alert unit is configured to generate the plurality of sound frequencies by way of a demultiplexing technique.
In an aspect of the present disclosure, the method begins sensing, by way of a plurality of sensors of an input unit, signals representing presence of a plurality of intruders, such that the plurality of intruders including at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region. The method proceeds to capturing, by way of a plurality of imaging devices of the input unit, a plurality of images of the region such that the plurality of sensors sense signals representing presence of the plurality of intruders based on the plurality of images. The method proceeds by identifying, by way of processing circuitry coupled to the input unit, at least one intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques. The method proceed by determining, by way of the processing circuitry, a limiting frequency associated with the at least one intruder of the plurality of intruders. The method proceed by generating, by way of the processing circuitry, an alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders and the method further generating, by way of an alert unit coupled to the processing circuitry, a plurality of sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders.
BRIEF DESCRIPTION OF DRAWINGS
The above and still further features and advantages of aspects of the present disclosure becomes apparent upon consideration of the following detailed description of aspects thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
FIG. 1A illustrates a block diagram of an IoT based deterrent system, in accordance with an aspect of the present disclosure;
FIG. 1B illustrates a schematic view of a device of the IoT based deterrent system of the FIG. 1A, in accordance with an aspect of the present disclosure; and
FIG. 2 illustrates a flow chart of a method for deterring a plurality of intruders by way of the IoT based deterrent system of the FIG. 1A, in accordance with an exemplary aspect of the present disclosure.
To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures.
DETAILED DESCRIPTION
Various aspect of the present disclosure provides a system, an apparatus, and a method for hardware-based cryptography. The following description provides specific details of certain aspects of the disclosure illustrated in the drawings to provide a thorough understanding of those aspects. It should be recognized, however, that the present disclosure can be reflected in additional aspects and the disclosure may be practiced without some of the details in the following description.
The various aspects including the example aspects are now described more fully with reference to the accompanying drawings, in which the various aspects of the disclosure are shown. The disclosure may, however, be embodied in different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects are provided so that this disclosure is thorough and complete, and fully conveys the scope of the disclosure to those skilled in the art. In the drawings, the sizes of components may be exaggerated for clarity.
It is understood that when an element is referred to as being “on,” “connected to,” or “coupled to” another element, it can be directly on, connected to, or coupled to the other element or intervening elements that may be present. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
The subject matter of example aspects, as disclosed herein, is described with specificity to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventor/inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different features or combinations of features similar to the ones described in this document, in conjunction with other technologies. Generally, the various aspects including the example aspects relate to an IoT-enabled deterrent system.
As mentioned, there is a need for a system that is capable of protecting crops and increase the productivity of the food grains. The present aspects, therefore: provides a system for protection of the crops from the intruders (animals, reptiles, pests, and birds) to overcome the aforementioned problems.
The aspects herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting aspects that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the aspects herein. The examples used herein are intended merely to facilitate an understanding of ways in which the aspects herein may be practiced and to further enable those of skill in the art to practice the aspects herein. Accordingly, the examples should not be construed as limiting the scope of the aspects herein.
FIG. 1A illustrates a block diagram of an internet of things (IoT) based deterrent system 100 (hereinafter referred to and denoted as “the system 100”), in accordance with an aspect of the present disclosure. The system 100 may prevent the entry of intruders into the farms or fields which may increase the yield and productivity of the crops and seeds. In other words, the system 100 could safeguard crops and seeds by deterring animals, birds, pests, and reptiles from entering the farm to consume them. The system 100 may be based on the Internet of things (IoT) and an artificial intelligence (AI). The system 100 may be powered by solar energy which makes the system 100 energy efficient and sustainable. Furthermore, the system 100 could dissuade intruders by emitting a sound of a specific frequency that discourages them from entering the farm to consume crops or seeds. The system 100 may generate the sound with such a frequency that the intruders may be deterred without their ears being harmed. The system 100 may be configured to generate the sound of the suitable frequency by recognizing the intruder. Specifically, the system 100 may be configured to generate the sound of the suitable frequency by recognizing the intruder by way of one or more machine learning techniques and the one or more artificial
The system 100 may include a device 102, an information processing apparatus 104, and an output unit 106. The device 102 may include an input unit 108, a microcontroller 110, and an alert unit 112. The input unit 108 may include a plurality of sensors and a plurality of imaging devices 116. The information processing apparatus 104 may include a database 118 and processing circuitry 120. The device 102 may be fixed anywhere in an agricultural field or a farm area. The device 102 may be durable and adjustable. The device 102 may be adjusted to the height of the crop. The device 102, the information processing apparatus, and the output unit 106 may be communicatively coupled to each other by way of a communication network 124. The device 102 may utilize renewable sources of energy to provide the electrical energy to the components.
In some aspects of the present disclosure, the communication network 124 may include, any one of, but not limited to a local area network (LAN), Zigbee, Bluetooth, Wi-Fi, a Wide area network (WAN), a cellular network, a mesh network. Aspects of the present disclosure are intended to include and/or otherwise include all the type of communication networks that may be employed to establish the communication, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the one or more sensors may include, one or more motion sensors, one or more Infrared (IR) sensors, one or more acoustic sensors, one or more vibration sensors, one or more environmental sensors, and one or more proximity sensors. Aspects of the present disclosure are intended to include and/or otherwise include all the sensors that may be employed for the detection of the intruders, without deviating from the scope of the present disclosure.
In operation, the plurality of sensors 114 may sense the signals that may represent the presence of the plurality of intruders, for example, a movement of the intruder that may be approaching an area where the device 102 is installed. The parameters that may represent the presence of the plurality of intruders may include, motion, acoustic signals, infrared radiation, light intensity, proximity, electromagnetic fields and environmental factors such as temperature, humidity, air quality, etc. After sensing, the plurality of imaging devices 116 may capture the plurality of images of the region. The data from the plurality of sensors 114 and the plurality of imaging devices 116 may be transmitted to the microcontroller 110. The microcontroller 110 transmit the collective data of the pluraliuty of sensors 114 and the plurality of imaging devices 116 to the processing circuitry 120 for the determination of the intruder and the potential threat that may be caused by the detected intruder. Based on the severity of threat the intruder may cause to the crop, the processing circuitry 120 may generate an alert signal which inturn may activate the deterrent mechanism, that may include emitting the sound frequencies to deter the intruder. The output unit 122 may be configured to display relevant information about the detected intruder and the details associated with the device 102 in response to deter the intruder.
FIG. 1B illustrates a schematic view the device 102 of the system 100 of FIG. 1A, in accordance with an aspect of the present disclosure. The device 102 may utilize a solar panel 134 to power the components. In other words, the device 102 may include the solar panel 134 to supply the power to the components for functioning.
The frame 126 may include an upper portion 128, a body 130, and a base 132. The upper portion 128 of the frame 126 may be coupled to the body 130 of the frame 126. The upper portion may be rotatable. The frame 126 may be adjustable. Specifically, the height of the frame 126 may be adjusted. The base 132 may be adapted to provide structural support to the frame 126.
In some aspects of the present disclosure, the frame 126 may be made up of, steel, aluminium, fiberglass reinforced plastic (FRP), carbon fibre, High-Density Polyethylene (HDPE), and wood. Aspects of the present dislosure are intended to include and/or otherwise include all the materials that may be used in making the frame durable, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the body 130 of the frame 126 may include one or more adjusting means that may include, any one of, an adjustable leg, threaded rods or bolts, a lever mechanism, and latches to adjust the height of the frame 126. Aspects of the present disclosure are intended to include and/or otherwise include all the adjusting means that may adjust the height of the frame 126, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the upper portion 128 may be coupled to the body 130 of the frame 126 by way of, but not limited to a gear mechanism, chain or belt drive, rack and pinion mechanism, electric motor, and a plurality of electrically controlled rollers. Aspects of the present disclosure are intended to include and/or otherwise include all the ways or mechanisms of coupling of the upper portion to the body of the frame, without deviating from the scope of the present disclosure.
The input unit 108 may include the plurality of sensors 114, the plurality of imaging devices 116, and the microcontroller 110. The plurality of sensors 114 may be configured to sense signals representing the presence of a plurality of intruders. The plurality of intruders may include at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region. The input unit 108 may further include a plurality of imaging devices 116. The plurality of imaging devices 116 may be configured to capture a plurality of images of the region such that the plurality of sensors 114 sense signals representing the presence of the plurality of intruders based on the plurality of images.
The plurality of imaging devices 116 may be fixed to the upper portion 128 of the device 102, such that when the plurality of imaging devices 116 may be adapted to rotate w.r.t the frame 126 of the device 102 to capture the 360 degrees view of the surroundings of the device 102. Specifically, the plurality of imaging devices 116 may be adapted to rotate w.r.t the frame 126 of the device 102 to capture the 360 degrees view of the surroundings of the device 102 when the plurality of sensors 114 may sense the signals that may represent the presence of the plurality of intruders.
In some aspects of the present disclosure, the one or more sensors may include, the one or more motion sensors, the one or more infrared (IR) sensors, the one or more acoustic sensors, the one or more vibration sensors, the one or more environmental sensors, and one or more proximity sensors. Aspects of the present disclosure are intended to include and/or otherwise include all the sensors that may be employed for the detection of the intruders, without deviating from the scope of the present disclosure.
The microcontroller 110 may be coupled to the input unit 108. The microcontroller 110 may be configured to collect the data associated with the plurality of sensors 114 and the plurality of imaging devices 116. Specifically, the microcontroller 110 may be configured to collect the raw data associated with the plurality of sensors 114 and the plurality of imaging devices 116. The microcontroller 110 may be further configured to preprocess the raw data. The microcontroller 110 may preprocess the raw data by way of the one or more techniques, which may include, one or more filtering techniques, one or more noise reduction techniques, one or more normalization techniques, and one or more feature extraction techniques. Aspects of the present disclosure are intended to include and/or otherwise include all the techniques that may be employed by the microcontroller 110 to preprocess the raw data, without deviating from the scope of the present disclosure.
In some aspects of the present disclosure, the microcontroller 110 may be, any one of, Raspberry Pi, Arduino NANO, 33 BLE sense, ESP32, STM32, PIC, Teensy, BeagleBone, MSP430, Particle, Nordic nRF52. Aspects of the present disclosure are intended to include and/or otherwise include all the type of microcontroller that can be programmed, without deviating from the scope of the present disclosure.
The device 102 may be coupled to the information processing apparatus 104. The information processing apparatus 104 may include the database 118 and the processing circuitry 120. The database 118 may be configured to store a first set of images and a second set of images. Specifically, the database 118 may be configured to store to store the first set of images associated with the region and the second set of images associated with the plurality of intruders.
The processing circuitry 120 may be configured to identify at least one intruder of the plurality of intruder from the preprocessed data that may be received by the microcontroller 110. The processing circuitry 120 may be configured to identify at least one the intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques.
The processing circuitry 120 may be configured to determine a limiting frequency associated with the at least one intruder of the plurality of intruders. Specifically, the processing circuitry 120 may be configured to determine the limiting frequency associated with the at least one intruder of the plurality of intruders based upon the identification of the intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques. The processing circuitry 120 may be configured to generate an alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders.
In some aspects of the present disclosure, the processing circuitry 120 may implement a classifier model to identify at least one intruder of the plurality of intruders, such that to train the classifier model, the processing circuitry 120 may be configured to (i) receive the first and second sets of images, (ii) pre-process the first and second sets of images to generate a set of pre-processed images, and (iii) train the classifier model by way of the set of pre-processed images, such that the classifier model is optimized by (a) scheduling a learning rate of the classifier model by employing a decay function and (b) applying model fitting to the classifier model by way of early stops and checkpoints callbacks.
The alert unit 112 may be coupled to the processing circuitry 120. The processing circuitry 120 may be configured to generate the alert signal by way of a frequency division multiplexing (FDM) technique. The alert unit 112 may be configured to generate an alert signal, such that upon generation of the alert signal, a plurality of sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders. The alert unit 112 may be configured to generate the plurality of sound frequencies by way of a demultiplexing technique.
In some aspects of the present disclosure, the plurality of sound frequencies may be generated by way of, any one of, a speaker, a transducer, a megaphone, a horn, and siren. Aspects of the present disclosure are intended to include and/or otherwise include all the mechanisms by which the sound frequencies may be emitted, without deviating from the scope of the present disclosure.
The output unit 106 may be coupled to the processing circuitry 120. The output unit 106 may be configured to to display one of, (i) one or more details of the at least one intruder of the plurality of intruders, (ii) a first numerical value associated to the limiting frequency of the at least one intruder of the plurality of intruders, (iii) a second numerical value associated to a sound frequency of the plurality of sound frequencies for the at least one intruder of the plurality of intruders.
The output unit 106 may be further confifured to display readings of the plurality of sensors 114, the image of the atleast one intruder of the plurality of the intruders, date and time, species of the atleast one intruder of the plurality of the intruders, internet connectivity and battery details.
In some aspects of the present disclosure, the output unit 106 may be incorporated within the device 102 or may include a device, that may include any one of, but not limited to, a mobile, a desktop computer, a television, a tablet and a smartwatch. Aspects of the present disclosure are intended to include and/or otherwise include all the display devices, without deviating from the scope of the present disclosure.
In some aspects of this disclosure, user may access the data displayed by the user device through an application. A user who wants to access the data may login to the application by entering credentials that may include, a mail id, phone number, password or any other credential that may be used for log in purpose.
FIG. 2 illustrates a flow chart of a method for deterring the plurality of intruders by way of the IoT based deterrent system of FIG. 1, in accordance with an exemplary aspect of the present disclosure.
At step 202, the system 100 may be configured to sense the signals that may represent the presence of the plurality of intruders, such that the plurality of intruders including at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region. Specifically, the the system 100 may be configured to sense the signals that may represent the presence of the plurality of intruders, such that the plurality of intruders including at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in the region by way of the plurality of sensors of the input unit 108.
At step 204, the system 100 may be configured to capture the plurality of images of the region such that the plurality of sensors 114 sense signals representing presence of the plurality of intruders based on the plurality of images. Specifically, the system 100 may be configured to capture the plurality of images of the region such that the plurality of sensors 114 sense signals representing presence of the plurality of intruders based on the plurality of images, by way of the plurality of the imaging devices 116.
At step 206, the system 100 may be configured to identify at least one intruder of the plurality of intruders by way of one of, the one or more Artificial Intelligence (AI) techniques and the one or more Machine Learning (ML) techniques. Specifically, the system 100 may be configured to identify at least one intruder of the plurality of intruders by way of one of, the one or more Artificial Intelligence (AI) techniques and the one or more Machine Learning (ML) techniques by way of the processing circuitry 120.
At step 208, the system 100 may be configured to determine the limiting frequency associated with the at least one intruder of the plurality of intruders. Specifically, the the system 100 may be configured to determine the limiting frequency associated with the at least one intruder of the plurality of intruders by way of the processing circuitry 120.
At step 210, the system 100 may be configured to generate the alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders. Specifically, the system 100 may be configured to generate the alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders by way of the processing circuitry 120.
At step 212, the system 100 may be configured to generate the plurality of the sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders. Specifically, the system 100 may be configured to generate the plurality of the sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders by way of the processing circuitry 120.
The foregoing discussion of the present disclosure has been presented for purposes of illustration and description. It is not intended to limit the present disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the present disclosure are grouped together in one or more aspects, configurations, or aspects for the purpose of streamlining the disclosure. The features of the aspects, configurations, or aspects may be combined in alternate aspects, configurations, or aspects other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention the present disclosure requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, configuration, or aspect. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate aspect of the present disclosure.
Moreover, though the description of the present disclosure has included description of one or more aspects, configurations, or aspects and certain variations and modifications, other variations, combinations, and modifications are within the scope of the present disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, configurations, or aspects to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.
Certain terms are used throughout the following description and claims to refer to particular features or components. As one skilled in the art will appreciate, different persons may refer to the same feature or component by different names. This document does not intend to distinguish between components or features that differ in name but not structure or function. While various aspects of the present disclosure have been illustrated and described, it will be clear that the present disclosure is not limited to these aspects only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the present disclosure, as described in the
claims. , Claims:1. A deterrent system (100) comprising:
an input unit (108) comprising:
a plurality of sensors (114) configured to sense signals representing presence of a plurality of intruders, wherein the plurality of intruders comprising at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region;
processing circuitry (120) coupled to the input unit (108), and configured to:
identify at least one intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques;
determine, upon identification, a limiting frequency associated with the at least one intruder of the plurality of intruders; and
generate an alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders, such that upon generation of the alert signal, a plurality of sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders.
2. The deterrent system (100) as claimed in claim 1, wherein the input unit (108) further comprising a plurality of imaging devices 116 configured to capture a plurality of images of the region such that the plurality of sensors (114) sense signals representing presence of the plurality of intruders based on the plurality of images.

3. The deterrent system (100) as claimed in claim 2, further comprising:
a frame (126) comprising:
a body (130); and
an upper portion (128) coupled to the body (130) such that the plurality of imaging devices (116) are disposed on the upper portion (128), wherein the upper portion (128) is rotatably coupled to the body (130) such that rotation of the upper portion (128) with respect to the body (130) facilitates rotation of the plurality of imaging devices (116) that facilitates the plurality of imaging devices (116) to capture a 360 degrees (3600) view of the region.

4. The deterrent system 100 as claimed in claim 3, further comprising an output unit 106 that is coupled to the processing circuitry (120), and configured to display one of, (i) one or more details of the at least one intruder of the plurality of intruders, (ii) a first numerical value associated to the limiting frequency of the at least one intruder of the plurality of intruders, (iii) a second numerical value associated to a sound frequency of the plurality of sound frequencies for the at least one intruder of the plurality of intruders.

5. The deterrent system (100) as claimed in claim 1, further comprising a database (118) that is coupled to the processing circuitry (120) and configured to store a first set of images associated with the region and a second set of images associated with the plurality of intruders.

6. The deterrent system 100 as clamed in claim 5, wherein the processing circuitry (120) implements a classifier model to identify the at least one intruder of the plurality of intruders, wherein to train the classifier model the processing circuitry (120) is configured to (i) receive the first and second sets of images, (ii) pre-process the first and second sets of images to generate a set of pre-processed images, and (iii) train the classifier model by way of the set of pre-processed images, wherein the classifier model is optimized by (a) scheduling a learning rate of the classifier model by employing a decay function and (b) applying model fitting to the classifier model by way of early stops and checkpoints callbacks.
7. The deterrent system (100) as claimed in claim 1, wherein the processing circuitry (120) is configured to generate the alert signal by way of a frequency division multiplexing (FDM) technique.

8. The deterrent system 100 as claimed in claim 7, wherein the alert unit (112) is configured to generate the plurality of sound frequencies by way of a demultiplexing technique.

9. A method (300) for deterring a plurality of intruders comprising:
sensing (302), by way of a plurality of sensors (114) of an input unit (108), signals representing presence of a plurality of intruders, wherein the plurality of intruders comprising at least one of, (i) a plurality of insects, (ii) a plurality of reptiles, (iii) a plurality of birds, and (iv) a plurality of animals in a region;
capturing (304), by way of a plurality of imaging devices (116) of the input unit (108), a plurality of images of the region such that the plurality of sensors (114) sense signals representing presence of the plurality of intruders based on the plurality of images.
identifying (306), by way of processing circuitry (120) coupled to the input unit (108), at least one intruder of the plurality of intruders by way of one of, one or more Artificial Intelligence (AI) techniques and one or more Machine Learning (ML) techniques;
determining (308), by way of the processing circuitry (120), a limiting frequency associated with the at least one intruder of the plurality of intruders;
generating (310), by way of the processing circuitry (120), an alert signal based on the limiting frequency of the at least one intruder of the plurality of intruders; and
generating (312), by way of an alert unit (112) coupled to the processing circuitry (120), a plurality of sound frequencies such that each sound frequency of the plurality of sound frequencies is generated based on the limiting frequency of the at least one intruder of the plurality of intruders.