Description:FIELD OF THE INVENTION
This invention relates to Drone Surveillance System using Machine Learning and Internet of Things.
BACKGROUND OF THE INVENTION
Drone technology is in trend in whole world which has its pros and cons. Drones can be used for many anti-social activities including- delivery of weapons for mass destruction, surveillance of sensitive areas like - airport, army area, dams, stadiums, fairs, etc.
AU2020203351B2 ABSTRACT ALA Drone-assisted emergency response methods, systems, and equipment, including computer programs stored on storage media. A monitoring system, according to one aspect, consists of a number of monitoring control units and a monitoring application server, the latter of which has a network interface, one or more processors, and one or more storage devices on which are stored instructions for carrying out operations. Receiving an emergency event notice from a first monitoring control unit among the numerous monitoring control units, identifying the emergency event's kind and the location 10 it is linked with, among other things, identifying one or more drones that can be sent to the emergency event site and sending a command to a monitoring station server connected to a drone base station to send the one or more identified drones to the emergency event location.
Research Gap: Our system detects the drone and triggers the alarm only after checking if the detected drone is authorized or not and sends the signal to the nearby police station and as well as the main control room.
JP2019040321A A drone monitoring system and a drone monitoring technique are both capable of more securely detecting drones than previous works. SOLUTION: To find a suspicious drone 95 in the area R1 to be found, a drone monitoring system 10 sends several allowed drones 90 whose flights are authorized to fly in that area. The suspicious drone 95 is found by suspicious object detecting devices 21 placed on the approved drones 90. The drone monitoring system 10 therefore consists of several radio base stations 11 that may communicate via radio with the drone radio terminals 20 installed on the approved drones 90, while dispersing and positioning them in a drone communication region R2 that includes the monitored area R1.
Research Gap: Our system detects the drone and triggers the alarm only after checking if the detected drone is authorized or not and sends the signal to the nearby police station and as well as the main control room.
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 Drone Surveillance System using Machine Learning and Internet of Things.
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.
A Drone Surveillance System using Machine Learning and Internet of Things comprises Wi-Fi/GSM/RAF (101), Cloud Server(102), Main Control Room (103), Nearest Police Station (104), Surveillance Node 1 (105), Surveillance Node 2 (106), Surveillance Node 3 (107), Controlling Unit (201), Radar (202), Co-Processor (203), AI/ML (204), Camera (205A, 205B, 205C), Alarm (206), and Wi-Fi Module (206).
Multiple cameras (205 A, 205 B, 205 C) installed in such a way that it covers the whole 360 degrees and these cameras will be positioned or angled in such a way that they can see the upper atmosphere where the drones will be operated. As soon as anything is seen by the cameras, firstly it will be identified if it’s even a drone or not with the help of machine learning. Once it’s confirmed that the detected object is a drone, then it will be checked if the detected drone is authorized or not with the help of radar, artificial intelligence and machine learning and also using the data from the database of DGCA (Directorate General of Civil Aviation). If the detected drone will be an unauthorized drone, it will display the footage of the drone in the nearest police station and the main control room and those drone footages will be stored in the database of the main control room. It will also display the location of the drone in the google maps with a small circle indicating a range where the drone is detected. It will also trigger an alarm in the nearest police station and the main control room and also at the place of where the device will be installed to alert the public that a drone is being detected nearby. Multiple surveillance nodes will be installed in the whole state and every single surveillance node will have their own Unique ID and the main control room can access any surveillance node at any time with the help of their Unique ID.
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 Drone Surveillance System
Fig. 2 Surveillance Node
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.
Multiple cameras (205 A, 205 B, 205 C) installed in such a way that it covers the whole 360 degrees and these cameras will be positioned or angled in such a way that they can see the upper atmosphere where the drones will be operated. As soon as anything is seen by the cameras, firstly it will be identified if it’s even a drone or not with the help of machine learning. Once it’s confirmed that the detected object is a drone, then it will be checked if the detected drone is authorized or not with the help of radar, artificial intelligence and machine learning and also using the data from the database of DGCA (Directorate General of Civil Aviation). If the detected drone will be an unauthorized drone, it will display the footage of the drone in the nearest police station and the main control room and those drone footages will be stored in the database of the main control room. It will also display the location of the drone in the google maps with a small circle indicating a range where the drone is detected. It will also trigger an alarm in the nearest police station and the main control room and also at the place of where the device will be installed to alert the public that a drone is being detected nearby. Multiple surveillance nodes will be installed in the whole state and every single surveillance node will have their own Unique ID and the main control room can access any surveillance node at any time with the help of their Unique ID.
ADVANTAGES OF THE INVENTION:
1. It will help police and defence mechanism in monitoring drones in public and sensitive areas.
2. It can be installed everywhere, where it is needed.
3. It will trigger alarm in nearby police station and as well as main control room whenever any unauthorized drone is detected by the system. , Claims:We Claim:
1. A Drone Surveillance System using Machine Learning and Internet of Things comprises Wi-Fi/GSM/RAF (101), Cloud Server(102), Main Control Room (103), Nearest Police Station (104), Surveillance Node 1 (105), Surveillance Node 2 (106), Surveillance Node 3 (107), Controlling Unit (201), Radar (202), Co-Processor (203), AI/ML (204), Camera (205A, 205B, 205C), Alarm (206), and Wi-Fi Module (206).
2. The system as claimed in claim 1, wherein multiple cameras (205 A, 205 B, 205 C) installed in such a way that it covers the whole 360 degrees and these cameras are positioned or angled in such a way that they can see the upper atmosphere where the drones are operated; wherein as soon as anything is seen by the cameras, firstly it is identified if it’s even a drone or not with the help of machine learning; when once it’s confirmed that the detected object is a drone, then it is checked if the detected drone is authorized or not with the help of radar, artificial intelligence and machine learning and also using the data from the database of DGCA (Directorate General of Civil Aviation).
3. The system as claimed in claim 1, wherein if the detected drone is an unauthorized drone, it will display the footage of the drone in the nearest police station and the main control room and those drone footages will be stored in the database of the main control room.
4. The system as claimed in claim 1, wherein it is displaying the location of the drone in the google maps with a small circle indicating a range where the drone is detected; and also trigger an alarm in the nearest police station and the main control room and also at the place of where the device will be installed to alert the public that a drone is being detected nearby.
5. The system as claimed in claim 1, wherein Multiple surveillance nodes are installed in the whole state and every single surveillance node will have their own Unique ID and the main control room can access any surveillance node at any time with the help of their Unique ID.
6. The system as claimed in claim 1, wherein Vision inspired drone surveillance system for real-time alert generation through Wi-Fi connectivity, artificial intelligence and machine learning.