Description:Title of The Invention
LoRaWAN-IoT with machine learning approach for wild animal intrusion detection system
Field of the Invention
This invention relates to IoT-based Animal Surveillance and Repellent systems.
Background of the Invention
AU2021100064A4: The invention discloses a system that identifies animals near fences and alarms sound which is unpleasant to the particular species of animals to ensure it stays in its region and thereby being in a secured place. The invention uses Machine learning algorithms and plays the sounds which is unpleasant to the species respectively. This Invention ensures the safety of animals by continuous monitoring and alarms them from crossing the fence. In case animals cross the fence respective personnel are also alerted for further action. Camera, IR sensors, Iot sensors, set sensor algorithms identification alarming alerting safety al database.
Research Gap: This invention provides information based on the Sensor-based LoRa-WAN Gateway Network used to access the presence of an animal.
KR102140195B1: The present invention relates to a wild animal trespassing detection method using radar, capable of preventing road kill problems and inducing safe vehicle driving based on position information of an object collected from a radar apparatus installed on a road, and a system thereof. Also, the present invention is capable of generating different alarms depending on whether an object is located inside or outside a road or whether the object is moving or not, thereby enabling a vehicle driver driving on the road to easily check the possibility of a wild animal trespassing or whether road kill has occurred and prepare for a dangerous situation. Also, the present invention is capable of calculating the probability of a road kill occurrence from an artificial neural network model by inputting whether the object is located inside or outside the road, the speed and size of the object, and its movement patterns into the artificial neural network model, so as to generate an alarm set differently depending on the road kill probability score, thereby enabling the vehicle driver driving on the road to easily check the possibility of the trespassing of a wild animal or whether road kill has occurred and prepare for a dangerous situation.
Research Gap: This Invention is for monitoring wild animal intrusion detection Using Machine Learning along with LoRaWAN-IoT Technology.
KR20160080448A: The present invention relates to a system for protecting crops from wild animals. More specifically, the system for protecting crops from wild animals comprising an unmanned air vehicle eradicating wild animals trespassing on a farm; a sensor unit detecting that the wild animal trespasses on the farm; and a central server receiving a trespassing signal of the wild animal from the sensor unit and transmitting information to the unmanned air vehicle. The system for protecting crops from wild animals is a system of providing data to prepare for the wild animal by not only eradicating the wild animals but also blocking approach possibility and making statistics of the trespassing wild animals. The present invention is to provide the system for protecting crops from wild animals, which is free from restraint on space and is performed at low costs. The system for protecting crops from wild animals also takes direct measures in accordance with the position of the wild animals. Also, the system for protecting crops from wild animals has double steps for eradicating the wild animals and includes a step of making the statistics on each kind of trespassing wild animals.
Research Gap: This Invention is for crop protection as well as human life protection. This system will identify the wild animal type and accordingly appropriate action will be taken
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is protect the human settlement and livestock on the outskirts of the forest area by creating an automated system that detects wild animal entry and repels them back into the forest without harming them, thus minimizing the conflict negative effects.

SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention. This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The country's expanding population is causing a fatal battle with its animals. Injury, loss of life, property damage, crop damage, livestock hazard, and habitat devastation are just a few of the severe implications. As a result of increased human influence on wildlife habitats, man- wildlife conflicts are becoming a serious cause of concern in many parts of the world. Electric fencing, trenches, and traps are ineffective and are harmful tactics used all over the world that cause more harm than benefit. While there are several existing IoT-based Animal Surveillance and Repellent systems, a touch of machine learning can improve their efficiency and help them break beyond the barriers that IoT alone has erected.
The proposed solution aims to protect the human settlement and livestock on the outskirts of the forest area by creating an automated system that detects wild animal entry and repels them back into the forest without harming them, thus minimizing the conflict negative effects.

BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
Fig. 1, represent the solution aims to protect the human settlement and livestock on the outskirts of the forest area by creating an automated system that detects wild animal entry and repels them back into the forest without harming them, thus minimizing the conflict's negative effects. Fig. 2 shows LoRa (Long Range) Gateway (107) is a transceiver module and Wi-Fi modem employed for communicating the internet packets to the cloud server on the internet through BoltIotsoftware. Fig. 3 shows field zones (100), sensor nodes (102), Arduino Module(101)which consists APR Sound Player [USB Port] (102), Camera [Pink Port] (103),LCD Display and it is also connected with Real Time Clock [RTC] (106), LoRa RF module(107),Data storage Module(106) and LCD Display(109). Fig. 4 shows LoRa modem (107) of the current architecture for relaying transmission lines to the monitoring authority. The gateway converts RF transmissions into IP packets so that information can be communicated across the internet protocol.
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.

DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
These and other advantages of the present subject matter would be described in greater detail with reference to the following figures. It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
Electric fencing, trenches, and traps are ineffective and are harmful tactics used all over the world that cause more harm than benefit. While there are several existing IoT-based Animal Surveillance and Repellent systems, a touch of Machine Learning can improve their efficiency and help them break beyond the barriers that IoT alone has erected.
The proposed solution aims to protect the human settlement and livestock on the outskirts of the forest area by creating an automated system that detects wild animal entry and repels them back into the forest without harming them, thus minimizing the conflict's negative effects.
The purpose of an animal detection system is to identify the presence of animals and issue a warning. The IR sensor, motion sensor, and ultrasonic sensors were employed in this proposed work to detect the animal's movement and send a signal to the controller. It distracts the animal by emitting sound and signals, which are then communicated through the LoRaWAN network and promptly inform farmers and forest officials.
The proposed invention focused on:
• Design Wild Animal Intrusion Detection system with smart monitoring of it using LoRaWAN-IoT with machine learning algorithms.
• Measuring the number of different parameters required to detect the wild animal presence through various sensors network.
Man-Wildlife conflict is a huge concern in the forest zone and agricultural fields, where vast amounts of resources are lost and human life is endangered. Electrified fences, manual surveillance, and other habitat-protection techniques have shown to be short-term, non-economic, and risky solutions for both animals and humans. A mitigation strategy is essential to solve this problem which ensures the safety of both wild animals and humans. The LoRaWAN technology is utilized to convey messages and alerts to the appropriate authorities. Because of its greater range and lower power consumption, as well as the fact that it can be connected to the IoT cloud, from which information can be collected by the user, introducing LoRaWAN technology coupled with machine learning techniques in this field would enable improved surveillance. The sensors, which include a PIR sensor, motion sensor, and ultrasonic sensors, are connected to the LoRa modules and detect animal activity across the forest border, sending data to the gateway via the LoRa shield. The gateway, in turn, is linked to a cloud server, from which the user can extract data via a website and/or mobile application. This method will indicate the exact location of the intrusion, allowing authorities to take immediate action. As a result, this region must be regularly monitored to ensure that no wild animals enter. The present invention is in the field of wild animal intrusion detection systems, with a focus on an IoT-based control system. The proposed model is divided into several phases that aid in the investigation of the workings of the system. When the process will start, the phase of sensing the data, the data is continuously transferred to the cloud server connected with the LoRaWAN in regular intervals and with this the phase of monitoring starts. After monitoring, data analysis is carried on which helps to determine the appropriate actions.
The proposed innovation is a unified Smart Wild Animal Intrusion Detection System that monitors animal movement by merging a number of sensors with a LoRaWAN network and machine learning technology. When an animal enters the region, the PIR and ultrasonic sensors, as well as the motion sensor, identify the animal's presence and transmit an input signal to the controller. The APR board will turn on immediately, and a sound will be produced to distract the animal. The flashlight will be turned on at night, and a notice will be sent to the forest department. Solar panels or a controlled power supply will be used to provide power. The presence of animals and LDR readings are displayed on the LCD.

Claims:1. LoRaWAN-IoT with machine learning approach for wild animal intrusion detection system is comprises with field zones (100), sensor nodes (102), Arduino Module (101) which consists APR Sound Player [USB Port] (102), Camera [Pink Port] (103), LCD Display and it is also connected with Real Time Clock [RTC] (106), LLoRa (Long Range) Gateway (107) is a transceiver module and Wi-Fi modem employed for communicating the internet packets to the cloud server on the internet through Bolt IoT software field zones (100), sensor nodes (102), Arduino Module (101) which consists APR Sound Player [USB Port] (102), Camera [Pink Port] (103), LCD Display and connected with Real Time Clock [RTC] (106), LLoRa (Long Range) Gateway (107) is a transceiver module and Wi-Fi modem employed for communicating the internet packets to the cloud server on the internet through BoltIotsoftware.
2. The system as claimed in claim 1, wherein said system field zones (100), sensor nodes (102), Arduino Module (101) which consists APR Sound Player [USB Port] (102), Camera [Pink Port] (103), LCD Display and it is also connected with Real Time Clock [RTC] (106).
3. The system as claimed in claim 1, wherein said system LLoRa (Long Range) Gateway (107) is a transceiver module and Wi-Fi modem employed for communicating the internet packets to the cloud server on the internet through Bolt IoT software field zones (100), sensor nodes (102), Arduino Module (101).
4. The system as claimed in claim 1, wherein said system transmits data to the cloud server via the internet using LoRaWAN Gateway.
5. The system as claimed in claim 1, wherein said system user can access cloud server information using the web application/mobile application.
6. The system as claimed in claim 1, wherein said A LoRaWAN –IoT for Smart Wild Animal Intrusion Detection it consists of-
• Sensors
• LoRaWAN GateWay
• BoltIoT software