DESC:TECHNICAL FIELD
[0001] The present disclosure relates to the field of aerial delivery systems and image processing. More particularly, the present disclosure relates to a system and method for enhanced Unmanned Aerial Vehicles (UAVs) delivery.

BACKGROUND
[0002] The following description of the related art is intended to provide background information pertaining to the field of the present disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section is used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of the prior art.
[0003] Unmanned Aerial Vehicles (UAVs) belong to the family of aircraft that are operated remotely without an on-board pilot. Unmanned Aerial Vehicles or UAVs were invented in the mid-1800s and are used for military applications such as dropping bombs in remote locations and used for delivering the war essentials such as food, medicines, and ammunition to the battlefield. The modern-day UAVs are well advanced in terms of technology, and precession and are designed in such a way that the UAV can be customised and modified based on the applications. The applications of UAVs include surveillance, surveying, mapping aerial photography, critical response, and agricultural and delivery applications. Considering the rapid growth of the aviation sector, the shift towards sustainability embarks on a new era of modern logistics where UAVs also known as Unmanned Aerial Vehicle plays a major role. The Logistical application includes the delivery of goods from one place to another. The utilisation of UAVs for Logistical applications not only reduces the time of commute but also reduces the carbon footprint.
[0004] The UAVs have revolutionized the logistics industries which are used to deliver goods such as food, medicines, and necessary essentials and provide response at critical times. The UAVs are also used for military purposes as well; it is used to supply Ammunition and information to the outposts that are at remote and classified locations. The UAVs are also used to collect real-time data on the terrain and the geographic conditions of a specific location.
[0005] One of the conventional UAV delivery system focuses on integrating station resources and energy-efficient static distribution schemes. Further, the conventional UAVs use a handover station model for package transfer rather than direct delivery to recipients. As a result, the conventional UAV delivery system lacks recipient verification methods, relying primarily on delivery task allocation without recipient identification.
[0006] Another conventional UAV delivery system employs human body gesture recognition for interaction with the UAV. Further, the conventional UAVs focuses on planning UAV usage based on operational loss and maintenance needs. As a result, the conventional UAV delivery system relies on human-computer interaction, which may introduce potential delays and complexity in the delivery process.
[0007] Existing UAV delivery system faces significant challenges regarding the safety and security of packages during transport. Unauthorized access or theft of packages presents a major concern, as ensuring secure delivery is critical. Additionally, maintaining an optimal flight time is crucial, influenced by both the distance of delivery and the payload carried by the UAV. As payload weight increases, it affects flight duration and stability, leading to potential risks during transport.
[0008] There is, therefore, a need in the art to provide Unmanned Aerial Vehicles (UAVs) delivery system using image-based authentication, and method thereof that can overcome the shortcomings of the existing prior arts. Thus, it is important for a robust solution which ensures secure, reliable deliveries while optimizing the UAVs flight parameters to account for payload and distance without compromising efficiency.

OBJECTS OF THE PRESENT DISCLOSURE
[0009] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0010] It is another object of the present disclosure to provide a system and a method that provides image-based authentication to ensure packages are delivered only to verified recipients, significantly reducing theft and mis-delivery risks.
[0011] It is another object of the present disclosure to provide a system and a method that provides a contactless solution that enhances safety and efficiency, operates autonomously, allowing for optimized path planning without delays from human couriers.
[0012] It is another object of the present disclosure to provide a system and a method which incorporates machine learning techniques and autonomous navigation for providing optimized delivery routes and improves the overall efficiency of the system.
[0013] It is another object of the present disclosure to provide a system and a method that provides direct package recipient verification through facial recognition.
[0014] It is another object of the present disclosure to provide a system and a method that enhances user experience by offering a seamless and intuitive delivery process with advanced security measures.

SUMMARY
[0015] In an aspect, the present disclosure relates an integrated system. The integrated system includes a processor communicatively coupled to an Unmanned Aerial Vehicle (UAV). A memory operatively coupled with the processor, where said memory stores instructions which, when executed by the processor, cause the processor receive information associated with delivery of one or more objects to one or more users through one or more computing devices. The processor determines via a machine learning engine an optimized path for the delivery of the one or more objects based on the received information. The processor analyzes, one or more features associated with the one or more users to authenticate the one or more users for the delivery of the one or more objects. The processor in response to a determination that the one or more users are authenticated delivers the one or more objects to the one or more users based on the analyzed one or more features.
[0016] In an embodiment, to analyze the one or more features, the processor may be configured to receive, one or more images associated with the one or more users through an image acquisition unit configured with the UAV. The processor may be configured to compare the received one or more images with one or more predefined inputs. The processor may be configured to, in response to a determination that the received one or more images match the one or more predefined inputs, subsequently authenticate the one or more users for the delivery of the one or more objects.
[0017] In an embodiment, the one or more images may include any or a combination of one or more facial patterns and a similarity index associated with the one or more users.
[0018] In an embodiment, to deliver the one or more objects to the one or more users, the processor may be configured to determine one or more GPS co-ordinates associated with the delivery of the one or more objects. The processor may be configured to subsequently activate, the image-acquisition unit to record the one or more images associated with the one or more users. The processor may be configured to in response to a determination that the received one or more images match the one or more predefined inputs, enable delivery of the one or more objects to the one or more users based on the matched one or more images and the one or more predefined inputs.
[0019] In an embodiment, the processor may be configured to receive an alert and enable the UAV to relocate to a specified location based on the received alert.
[0020] In an aspect, the present disclosure relates a method for delivery of objects. The method includes receiving, by a processor, information associated with an integrated system, for delivery of one or more objects to one or more users. The method includes determining, by the processor, via a machine learning engine, an optimized path for the delivery of the one or more objects based on the received information. The method includes analyzing, by the processor, one or more features associated with the one or more users to authenticate the one or more users for the delivery of the one or more objects. The method includes in response to a determination that the one or more users are authenticated, delivering, by the processor, the one or more objects to the one or more users based on the analyzed one or more features.
[0021] In an embodiment, for analyzing the one or more features, the method may include receiving, by the processor, one or more images associated with the one or more users through an image acquisition unit configured with the UAV. The method may include comparing, by the processor, the received one or more images with one or more predefined inputs. The method may include, in response to a determination that the received one or more images match the one or more predefined inputs, subsequently authenticating, by the processor, the one or more users for the delivery of the one or more objects.
[0022] In an embodiment, for delivering the one or more objects to the one or more users, the method may include determining, by the processor, one or more GPS co-ordinates associated with the delivery of the one or more objects. The method may include subsequently activating, by the processor, the image-acquisition unit to record the one or more images associated with the one or more users. The method may include, in response to a determination that the received one or more images match the one or more predefined inputs, enabling, by the processor, delivery of the one or more objects to the one or more users based on the matched one or more images and the one or more predefined inputs.
[0023] In an embodiment, the method may include receiving, by the processor, an alert and enabling the UAV to relocate to a specified location based on the received alert.

BRIEF DESCRIPTION OF THE DRAWINGS
[0024] The accompanying drawings, which are incorporated herein, and constitute a part of this invention, illustrate exemplary embodiments of the disclosed methods and systems which like reference numerals refer to the same parts throughout the different drawings. Components in the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the present invention. Some drawings may indicate the components using block diagrams and may not represent the internal circuitry of each component. It will be appreciated by those skilled in the art that the invention of such drawings includes the invention of electrical components, electronic components or circuitry commonly used to implement such components.
[0025] FIG. 1A illustrates an exemplary network architecture of the proposed Unmanned Aerial Vehicles (UAVs) delivery system using image-based authentication, in accordance with an embodiment of the present disclosure.
[0026] FIG. 1B illustrates an exemplary framework of the proposed UAVs delivery system, in accordance with an embodiment of the present disclosure.
[0027] FIG. 2 illustrates an exemplary block diagram architecture of the UAVs delivery system, in accordance with an embodiment of the present disclosure.
[0028] FIG. 3A illustrates an exemplary block diagram representing the components of the UAVs delivery system, in accordance with an embodiment of the present disclosure.
[0029] FIG. 3B illustrates an exemplary representation of the Ardupilot mission planner interface, in accordance with an embodiment of the present disclosure.
[0030] FIG. 3C illustrates an exemplary representation output of the facial recognition analysis, in accordance with an embodiment of the present disclosure.
[0031] FIG. 4 illustrates a flow diagram for implementing a method for UAVs delivery system using image-based authentication, in accordance with an embodiment of the present disclosure.
[0032] FIG. 5 illustrates an exemplary computer system in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION
[0033] In the following description, for the purposes of explanation, various specific details are set forth in order to provide a thorough understanding of embodiments of the present disclosure. It will be apparent, however, that embodiments of the present disclosure may be practiced without these specific details. Several features described hereafter can each be used independently of one another or with any combination of other features. An individual feature may not address all of the problems discussed above or might address only some of the problems discussed above. Some of the problems discussed above might not be fully addressed by any of the features described herein.
[0034] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0035] The present disclosure relates to the field of aerial delivery systems and image processing. More particularly the present disclosure relates to an Unmanned Aerial Vehicles (UAVs) delivery system using image-based authentication, and method thereof. The UAVs are most commonly used for surveillance, mapping, surveying, rescue operations, entertainment as well as logistical purposes. The Logistical application includes the delivery of goods from one place to another. The UAV can be made autonomous where the path planning can be generated by setting one or more waypoints which the UAV can follow to reach the destination, ensuring an optimised travel path. The Autonomous UAV helps in reducing manpower and ensures ultimate-mile delivery. The UAV can manuever through rough terrain and harsh environments making it suitable for logistical application. The UAV can be tacked with the help of an onboard GPS module that is connected to the flight controller. The proposed UAVs delivery system ensures that the package reaches a recipient. The UAVs delivery system incorporates an onboard microcomputer processes which receives an input data from an image capturing unit associated with the UAV. Further, using an image-based authentication technique, the recipient's face can be identified by comparing to a predefined input. The significant match of the recipient's face, triggers the package delivery/drop mechanism which can be connected to the processer of the UAV. Thus, by implementing the UAVs delivery system the efficiency of the autonomous delivery of goods can be improved significantly.
[0036] Various embodiments of the present disclosure will be explained in detail with respect to FIGs. 1A-5.
[0037] FIG. 1A illustrates an exemplary network architecture 100 of the proposed Unmanned Aerial Vehicles (UAVs) delivery system 102 or integrated system 102 or system 102 using image-based authentication, in accordance with an embodiment of the present disclosure.
[0038] FIG. 1B illustrates an exemplary framework of the proposed UAVs delivery system 102, in accordance with an embodiment of the present disclosure.
[0039] In an embodiment, referring to FIG. 1A and 1B, the Unmanned Aerial Vehicles (UAVs) delivery system 102 (also known as system 102, herein) may be connected to a network 104, which is further connected to at least one computing device 108-1, 108-2, … 108-N (collectively referred as computing device 108, herein) associated with one or more users 106-1, 106-2, … 106-N (collectively referred as user 106, herein).
[0040] In an embodiment, the system 102 comprises at least one user equipment or UAV 108 associated with the user 106 capable of directing the system 102 and ensuring the safe delivery of the package to a recipient 106 via a network 104. The system 102 can include, but not limited to a drone, a multirotor, a zip-line, and the like, which are capable of enabling aerial autonomous delivery of goods.
[0041] In an exemplary embodiment, the computing device 108 may include, but not be limited to, a computer enabled device, a mobile phone, a smartphone, a tablet, a laptop, a display device, a surveillance camera, an automatic teller machine, and a point of sale, a kiosk, and a smart doorbell, a smart home device, a Augmented Reality/Virtual Reality/Mixed Reality (AR/VR/MR), an imaging device, a display projector, a Remote Detection Service (Detection Device) enabled devices such as iBeacon technologies, or some combination thereof. A person of ordinary skill in the art will understand that the at least one computing device 108 may be individually referred to as a computing device and collectively referred to as computing devices 108.
[0042] In an exemplary embodiment, the network 104 may include, but not be limited to, at least a portion of one or more networks having one or more nodes that transmit, receive, forward, generate, buffer, store, route, switch, process, or a combination thereof, etc. one or more messages, packets, signals, waves, voltage or current levels, some combination thereof, or so forth. In an exemplary embodiment, the network 104 may include, but not be limited to, a wireless network, a wired network, an internet, an intranet, a public network, a private network, a packet-switched network, a circuit-switched network, an ad hoc network, an infrastructure network, a Public-Switched Telephone Network (PSTN), a cable network, a cellular network, a satellite network, a fiber optic network, or some combination thereof.
[0043] In an embodiment, the system 102 may be used in various surveillance, surveying, mapping aerial photography, critical response, and agricultural, delivery applications and the like. The system 102 may play a pivotal role in authentication, recipient identification, and delivery of goods/packages. The users may include, but not limited to, trainee, operators, individuals, customers, retailers, and the like. The input data may include user actions which include, but not limited to, capturing image of the recipient, receiving recipient data, and the like.
[0044] In an embodiment, the system 102 includes one or more processors (refer FIG. 2), and a memory (refer FIG. 2) coupled to the one or more processors, where said memory stores instructions which when executed by the one or more processors cause the system 102 to receive the input data from the computing device 108 associated with the users 106.
[0045] FIG. 2 illustrates an exemplary block diagram architecture of the UAVs delivery system, in accordance with an embodiment of the present disclosure.
[0046] In an aspect, referring to FIG. 2, the system 102 may include one or more processor(s) 202. The one or more processor(s) 202 may be implemented as one or more microprocessors, microcomputers, microcontrollers, edge or fog microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the one or more processor(s) 202 may be configured to fetch and execute computer-readable instructions stored in a memory 204 of the system 102. The memory 204 may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory 204 may include any non-transitory storage device including, for example, volatile memory such as Random Access Memory (RAM), or non-volatile memory such as Erasable Programmable Read-Only Memory (EPROM), flash memory, and the like.
[0047] Referring to FIG. 2, the system 102 may include an interface(s) 206. The interface(s) 206 may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 206 may facilitate communication to/from the system 102. The interface(s) 206 may also provide a communication pathway for one or more components of the system 102. Examples of such components include, but are not limited to, processing unit/engine(s) 208 and a local database 210.
[0048] In an embodiment, the processing unit/engine(s) 208 may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 208. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 208 may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 208 may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 208. In such examples, the system 102 may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system 102 and the processing resource. In other examples, the processing engine(s) 208 may be implemented by electronic circuitry.
[0049] In an embodiment, the local database 210 may include data that may be either stored or generated as a result of functionalities implemented by any of the components of the processor 202 or the processing engines 208. In an embodiment, the local database 210 may be separate from the system 102.
[0050] In an exemplary embodiment, the processing engine 208 may include one or more engines selected from any of a data acquisition module 212, a face recognition module 214, a coordinate generation module 216, a speed regulation module 218, a machine learning engine 222, and other modules 224 having functions that may include but are not limited to testing, storage, and peripheral functions, such as a wireless communication unit for remote operation, an audio unit for alerts, and the like.
[0051] In an embodiment, the system 102 may include the data acquisition module 212 which may be configured to integrate sensors, processing components, to capture, process, and deliver packages which are based on user requests.
[0052] In an embodiment, the system 102 may include the face recognition module 214 can be configured to verify the recipient's identity at the point of delivery. The UAV captures an image of the person receiving the package and compares it with stored biometric data using on-board image processing. Thus, the face recognition module 214 ensures that only authorized individuals can collect the delivery. The system 102 also integrates real-time monitoring to authenticate the recipient before releasing the package, providing a secure and efficient delivery process.
[0053] In an embodiment, the system 102 may include the coordinate generation module 216 which may be configured to determine precise GPS coordinates for the delivery location (or specific location). The coordinate generation module 216 can process input data such as customer addresses or predefined waypoints, converting the input data into navigable geographic coordinates. The coordinate generation module 216 accounts for geofencing and restricted areas to ensure safe flight paths. The coordinates are then fed into the system 102 to guide it through the delivery route. Additionally, the real-time adjustments can be made to adapt to changing conditions or obstacles during flight.
[0054] In an embodiment, the system 102 may include the speed regulation module 218 which may be configured to dynamically adjust the speed of the system 102 based on various factors such as payload weight, weather conditions, and battery status. The speed regulation module 218 can ensure optimal speed to maintain stability, conserve energy, and enhance safety.
[0055] In an embodiment, the system 102 may include a machine learning engine 222 for processing the received data.
[0056] In an embodiment, the processor 202 may receive information associated with delivery of one or more objects to one or more users (106-1, 106-2 … 106-N) through one or more computing devices (108).
[0057] In an embodiment, the processor 202 may determine via the machine learning engine 222 an optimized path for the delivery of the one or more objects based on the received information. To analyze the one or more features, the processor 202 may be configured to receive, one or more images associated with the one or more users (106-1, 106-2 … 106-N) through an image acquisition unit configured with the UAV. The one or more images may include any or a combination of one or more facial patterns and a similarity index associated with the one or more users (106-1, 106-2 … 106-N).
[0058] In an embodiment, the processor 202 may be configured to compare the received one or more images with one or more predefined inputs. The processor 202 may be configured to, in response to a determination that the received one or more images match the one or more predefined inputs. The processor 202 may be configured to subsequently authenticate the one or more users (106-1, 106-2 … 106-N) for the delivery of the one or more objects. To deliver the one or more objects to the one or more users (106-1, 106-2 … 106-N), the processor 202 may be configured to determine one or more GPS co-ordinates associated with the delivery of the one or more objects. The processor 202 may be configured to subsequently activate, the image-acquisition unit to record the one or more images associated with the one or more users (106-1, 106-2 … 106-N). The processor 202 may be configured to in response to a determination that the received one or more images match the one or more predefined inputs enable delivery of the one or more objects to the one or more users (106-1, 106-2 … 106-N) based on the matched one or more images and the one or more predefined inputs.
[0059] In an embodiment, the processor 202 may analyze, one or more features associated with the one or more users (106-1, 106-2 … 106-N) to authenticate the one or more users (106-1, 106-2 … 106-N) for the delivery of the one or more objects.
[0060] In an embodiment, the processor 202 may in response to a determination that the one or more users (106-1, 106-2 … 106-N) are authenticated, deliver the one or more objects to the one or more users (106-1, 106-2 … 106-N) based on the analyzed one or more features. The processor (202) may be configured to receive an alert and enable the UAV to relocate to a specified location based on the received alert.
[0061] FIG. 3 illustrates an exemplary block diagram 300 representing the components of the UAVs delivery system 102, in accordance with an embodiment of the present disclosure.
[0062] In an embodiment, the system 102 may include one or more motors (302-1, 302-2,…, 302-4), one or more Electronic Speed Controller (ESC) (304-1, 304-2,…, 304-4), a flight controller 306, a frame 308, at least one image capturing unit 310, a gimbal system 312, a radio transmitter 314, a radio receiver 316, a battery 318, and a delivery mechanism 320.
[0063] In an embodiment, the one or more motors (302-1, 302-2,…, 302-4) (also known as servo motor 302 (MG996R), or a motor 302) may be a high-torque servo motor and due to immediate reaction speed which is mainly used in hexapods, grippers, robots, mini manipulators, and the like that require accurate control and movement. The reaction speed of the motor 302 in no load condition is 0.19s/60 degrees at 4.8V and 0.15s/60 degrees at 6.6V which allows the motor 302 to maintain quick and responsive movements. The motor 302 may be capable of generating a huge torque of 11kg/cm at 6V and 9.4kg/cm at 4.8V. The motor 302 may consists of a 3-pin power, control horns, a mounting hardware and also a control cable. The motor 302 has a standard 3-pin connector which is easy to control. The motor 302 uses only digital pins and can be directly used with an Arduino. The servo motor 302 has a wide range of operating voltages between 4.8V- 6.6V DC, which may be all-metal gear servo motor with an advantage of high durability and resistance to wear and tear when compared to motors with plastic gears. Additionally, to increase the lifespan and reduce friction, the motor 302 has a ball bearing that is used to support the outer shaft. A PWM signal to control the speed, direction, and position of the motor precisely. The maximum torque output of the motor is achieved at lower speeds i.e., the motor’s torque output is inversely proportional to the speed of the motor.
[0064] Further, the main thumb rule is aiming for a minimum 2:1 thrust/weight ratio. The motors 302 with high speed have lower torque. Higher the voltage faster the motors spin hence drawing more current. A brushless DC motor rated at 1000KV when given a voltage of 1V can rotate at a speed of 1000 rpm and generates a high torque which has a current rating of 10A. Usually, brushless DC motors (BLDC) are utilized because of their high reliability, efficiency, and power-to-weight ratio. An electronic speed controller (ESC) is connected to each motor to regulate its speed and direction. The propellers are attached to the motors 302 to convert the rotational energy of the motor into thrust. The materials used to make these propellers are light in weight such as carbon fiber. These propellers are designed with a particular angle and pitch to maximize efficiency. The propellers used in this prototype quadcopter are 4.5 x 10-inch propellers. The copter can control the amount of thrust produced by each propeller by changing the speed of the motor attached to it
[0065] In an embodiment, the Electronic Speed Controller (ESCs) (304-1, 304-2, 304-3, 304-4) or ESC 304 may be configured to regulate the speed and power of the motors (302-1, 302-2, 302-3) or motor (302), enabling precise control over flight dynamics. The ESC 304 translates signals from the flight controller 306 into motor movement, adjusting the propeller speeds to maintain stability, acceleration, and directional changes. The ESC 304 may be an electronic circuit that is used to control and adjust the speed of an electronic motor 302. ESC 304 may be used for dynamic braking and reversing the motor 302. The terminals of the ESC 304 are connected to the terminals of the BLDC motor. The APM 2.8 flight controller 306 sends a signal (Pulse Width Modulation (PWM) signal) to the ESC 304 to increase or decrease the voltage of the motor thereby, changing the speed of the propeller as per the requirements. The speed controller 306 consists of power MOSFETs which act as switches to control the flow of current to the motor. The power switches are the responsible for the motor switching during on and off at high frequencies for the regulation of speed. The speed controllers are also used for regenerative breaking where the mechanical energy of the motor is converted into electrical energy that is in turn used to recharge the battery of the drone. The above process mainly occurs in cases where the UVA is in deceleration condition. There are two types of ESCs brushless speed controllers and brushed speed controllers. Mostly brushless ESCs are used mainly due to their high performance and durability in comparison to brushed ESCs 304.
[0066] In an embodiment, the flight controller 306, may also be an APM 2.8 Multicopter flight controller 306 which is an open-source autopilot system. The flight controller 306 determines the ideal speed for each of the motors 302 by analyzing the sensor data. The flight controller 306 may transmit the desired speed to the ESC 304, which in turn convert the desired speed into a signal in which the motors 302 can comprehend. This APM 2.8 controller is integrated with a 32-bit ARM Cortex-M4 processor which gives swift and reliable processing of the sensor data. The flight controller 306 includes a 3-axis gyroscope, an accelerometer, and, a barometer. The flight controller 306 also includes a built-in GPS system for precise positioning and navigation purposes. Since the flight controller 306 may be an open-source autopilot system, the users can easily change and customize the program to meet their specific requirements. The flight controller 306 also has an additional feature of telemetry, here the users can monitor the drone in real-time flight operations. The flight controller 306 has an on-board 4MB data flash chip for the automatic logging of sensor data. The minimum voltage required for the functioning of the APM 2.8 controller is 5V and the maximum is 16V. The flight controller 306 also supports the radio receiver 312 which can be used to receive commands from the radio transmitter 314.
[0067] In an embodiment, the air frame 308 (also known as frame 308) frame used in the quadcopter is an F450 frame which may be made from advanced materials to obtain the least weight and maximum strength. The frame 308 weighs nearly around 280g only making easier to fly. The main frame of the quadcopter is made using glass fibre as it gives high strength, corrosion resistance, and lightweight properties making it an ideal and durable material for its construction. Next, the construction of the arms is made from ultra-durable nylon known for its protection against abrasion and lifespan. The frame 308 has an advantage because of its coloured arms. The colored arms help in keeping track of the orientation and direction of the quadcopter during its flight. The features such as the large center plate aid in the mounting of gimbals and cameras for aerial photography. The frame 308 may be designed in such a way that it can easily accommodate 10-11-inch propellers, ensuring an adequate balance of thrust and stability. The combined PCB and frame structure facilitates the stacking of electronic components such as FPV equipment, ESC, and flight controllers 306. Additionally, the battery mount 318 can be integrated in the frame 308 to hold the battery 318 in its position during flight operations. The frames 308 may be designed in such a way that allows users to easily switch damaged parts and personalize the configuration of the UAV.
[0068] In an embodiment, the at least one image capturing unit 310 and the gimbal system 312 which may require real-time images to access the situations and act on the received information such as surveillance, videography, aerial photography, etc. The quality of the images captured by the at least one image capturing unit 310 depends on resolution, sensor size, and most importantly its field of view. The at least one image capturing unit 310 are mostly connected to the flight controller 306 which can be the source of power and commands. The image capturing unit 310 may be connected to this quadcopter as shown is the one that has a 4K resolution. The gimbal system 312 may allow the rotation of the image capturing unit 310 along the desired direction. The gimbal system 312 may be used in the UVA prototype is a 3-axis gimbal that stabilizes the camera in the three roll, pitch, and yaw movements of the drone. The flight controller 306 may also control the movements of the gimbal system 312 ensuring the smooth control of the image capturing unit 310. One of the main functions of the gimbal system 312 may be to isolate the image capturing unit 310 from the drone's main frame movements ensuring proper orientation of the image capturing unit 310 for its stable footage. Another function of the flight controller 306 which may align the data from the image capturing unit 310 with the telemetry data of the UVA to allow features such as the at least one image capturing unit 310 tracking and GPS tracking.
[0069] In an embodiment, the radio transmitter 314 is a device used to transmit radio signals wirelessly by using a set of radio frequencies to the radio receiver 316 which is connected to the copter or being controlled remotely. The radio receiver 316 may receive commands via signals from the radio transmitter 314 and interpret the received signals through the flight controller 306. The flight controller 306 interprets the signals into commands that are used to perform specific actions that are used to control the UVA. For instance, the drones which use APM 2.8 as controller operate on frequency band such as 2.4GHz or 5.8GHz. The communication protocol that is used in the flight controller 306 is serial protocol such as SBUS or PPM. The communication protocols are used in unidirectional communication where the controller receives data from the peripherals or sends commands to them. Telemetry protocols are used for wireless communication between the ground station and drone. These telemetry protocols are used in the drone for the transmission of data such as sensor data, flight parameters, and the status of the system to the station present on the ground.
[0070] In an embodiment, the battery 318 powers the UAVs propulsion, navigation, and control systems. Lithium-polymer (LiPo) batteries 318 are commonly used due to their high energy density and lightweight nature, enabling longer flight times. However, the payload weight and flight distance directly impact battery life, often limiting the range and duration of delivery missions.
[0071] In an embodiment, the processor(s) 202 which can include, but not limited to: Raspberry Pi 4 Model B, may be a high-performance 64-bit quad-core cortex-A72 processor and has various peripherals such as ethernet, USB, etc. The processor(s) 202 include a dual display feature to aid resolutions up to 4K by using a pair of micro HDMI ports which enable the board to support hardware video decoding at 4Kp60. Raspberry Pi’s processing is closer to an entry-level x86 PC system processing which enables handle challenging tasks such as software development, multimedia editing, and even tasks such as web browsing. The processor(s) 202 16GB RAM may allow to perform more complex programs and do multiple tasks efficiently. The Pi 4 Model B board includes a dual-band wireless LAN (Local area network) and also Bluetooth which may be used for swift and reliable wireless communication. Additionally, the incorporation of a gigabit ethernet enables high-speed wired networking which is crucial for functions that demand consistent and quick data transfer rates. The inclusion of USB 3.0 ports rather than standard USB 2.0 ports makes it considerably faster at data transfer. The said model still remains energy efficient when compared to the previous models while fully delivering a significant boost in its performance, processor speed, memory capacity and lastly connectivity options. The addition of dual-band wireless LAN and Bluetooth support modular compliance certification, making it simple for the designers to integrate the Raspberry Pi into end products.
[0072] In an embodiment, the Global Positioning System provides precision technology, which can be is used for various tasks such as aerial photography, mapping, and surveying of unknown areas, where exact positioning is very important. The use of precision technology is to find out the exact geographical location of the UAV by connecting itself to a network of satellites. The GPS system is extremely important in cases where the drone loses its connection with the ground station or when the battery levels of the drone are at dangerously low levels. The GPS ensures that the UVA is safely navigating it back to an initial take-off point thereby ensuring the safe return of the drone and also safeguarding the stored data. Another feature of using GPS in drones is their capability to fly autonomously along a loaded programmed path. The programmed path can be extremely useful in search and rescue operations and inspections. Additionally, the positioning system helps the drone maintain its altitude and position even in extremely turbulent and windy conditions. The GPS module is connected to the flight controller APM 2.8, and the flight controllers 306 enable the users to configure the GPS settings such as GPS mode, baud rate, and update rate. To set the communication speed between the flight controller and the GPS module and also it is essential to configure the right and precise frequency at which location updates can be provided by the GPS module. The GPS module has common interface protocols such as UART, I2C, SPI, and USB. It can also have some more features such as Bluetooth, or cellular connectivity for remote control and monitoring.
[0073] In an embodiment, referring to FIG. 3A, the UAV 102 may be operated remotely with the help of a specifically designed radio transmission and reception protocol. The protocol runs on PWM (Pulse Width Modulation). The Unmanned Aerial Vehicle is controlled by a 2.4 GHz Radio Transmitter and has the capability of operating 6-10 channels based on the applications. These individual channels can be programmed based on the requirements and the application. Each channel is independent of each other. The channels can be assigned to various switches on the transmitter (remote) based on the required PWM values and the sensitivity. The channels in the transmitter 314 are directly connected to the corresponding channels of the receiver 316. The channels of the transmitter 314 can be reversed such that the high signal in the transmitter can be portrayed in the receiver as a low signal. The receiver 316 is connected to the input terminals of the flight controller 308 respectively, hence ensuring the connection of the respective channel of the transmitter 314 to the respective input terminal of the flight controller 308.
[0074] In an embodiment, the Flight Controller 308 are the signals that are provided by the respective channels of the Transmitter 314. The four main channels of the Unmanned Aerial Vehicles are Pitch, Roll, Yaw and Throttle. The Pitch function of the quadcopter provides forward and backward thrusts that are necessary for the forward and backward movement. The Roll function provides the left and right roll of the aircraft. The Yaw function provides a 360-degree Yaw movement with a horizontal base. The Throttle function is used to provide the Vertical take-off and land of the quadcopter. The ranges of these functions vary from -1500 to +1500 based on the PWM values provided by the transmitter. The Flight Controller 308 is programmed such that the flight controller is able to process the input commands from the receiver and provide output commands in terms of digital signals that are connected to the Electronic Speed Controllers 304. The Flight Controllers 306 take several factors into account while providing an output such as the GPS module that is connected to the flight controller providing the GPS coordinates in real-time. The Flight Controller has an in-built compass and an additional compass in the GPS Module. The Gyroscope present in the flight controller ensures the stability of the flight. The APM 2.8 flight controller is capable of inputting 8 channels from the radio receiver and can provide a maximum output that can be connected to 8 different motors. The flight controller has an inbuilt memory that can store the firmware that can be modified based on the application and requirements of the aircraft.
[0075] In an embodiment, the Unmanned Aerial Vehicle that is being employed is a quadcopter, that belongs to the family of rotorcrafts. The Quadcopter consists of four motors that are attached to the frame of the Quadcopter. The frame of the Quadcopter is designed in such a way that each motor is attached to the frame is 90 degrees apart from each other. The frame also consists of a power distribution board that has one input terminal and four output terminals. The input terminal of the power distribution board is connected to the battery and the output terminals of the power distribution board are connected to the individual motors via Electronic Speed Controllers 304, respectively. The power distribution board has a power rating of 750 Watts, where the power distribution board can handle an input voltage of 25 Volts and 30 Amps at peak load conditions. The battery 318 that is connected to the power distribution board is a 12.4 V battery that is connected to the input terminals of the power distribution board. The battery 318 can provide a maximum current of 30 Amps. The Output terminals are connected to the Input Power terminals of the Electronic Speed Controller (ESC) 304.
[0076] In an embodiment, the ESC 304 has two input power terminals and a combined digital input terminal, 5V, and GND as power output terminal that is connected output terminal of the flight controller. The power output of the Electronic Speed Controller is connected to the input terminals of the motor. The output of the ESC is a three-terminal output where the ESC takes two input power terminals, these two input power terminals are then converted into three output power terminals by 6 Mosfets that are connected in series along with the three output power terminals of the electronic speed controller. The two input power terminals are subjected to switching where the gate pulses of the Mosfets are provided by the digital input terminal of the Electronic Speed Controller that is connected to the Output terminals of the Flight Controller. The Mosfets are switches such that two output terminals of the ESC conduct, act as a positive terminal and provide the flow of input current into the motor whereas the third output terminal of the ESC acts as the receiving part which acts as a GND or negative terminal. The switching of the Mosfets in the ESC happens extensively at a faster rate based on the commands received from the flight controller 306.
[0077] In an embodiment, the motors 302 that are used in the quadcopter are BLDC Motors, which are made up of permanent Magnet Motors. The Stator of BLDC Motors is made up of permanent magnets and the armature is made up of copper coils and is coated with enamel for higher performance and field production. These coils are three in number and are arranged consecutively one after the other. These Coils are energized in series one after the other so that the interaction between the armature and permanent magnet creates a force that causes the stator to rotate in the desired direction based on the sequence of energization of the coils. The flight controller is programmed such that the quadcopter can be controlled based on the inputs from the receiver that have been transmitted from the transmitter. The flight controller provides digital signals from the output terminals that are connected to the Electronic Speed Controller and hence the motors are controlled. The direction of the quadcopter can be controlled with the Pitch, Roll, Yaw and Throttle Functions. The Quadcopter has two clockwise and two anticlockwise motors connected one after the other. The Propellers are connected in such a way that the anticlockwise propeller is connected to the anticlockwise motors, and the clockwise propellers are connected to the clockwise propellers respectively. This configuration provides downward thrust and hence provides upward motion for the Quadcopter. To utilize the pitch action the speeds of the anterior and posterior motors are regulated. To Pitch Forward the speed of the posterior motors is reduced, and the speed of the anterior motors is increased and vice-versa for Pitch Backward. To utilize the roll action the speeds of the left and right motors are regulated. Such that the speed of the left motor is reduced to roll left and vice versa to roll right. To utilize the yaw action the motors are rotated in clockwise and anticlockwise directions respectively. The speed of the anticlockwise motors is increased, and the speed of the clockwise motors is reduced to provide yaw left and vice versa for yaw right.
[0078] In an embodiment, the Unmanned Aerial Vehicle 102 containing the package is programmed to autopilot by inputting the GPS Coordinates and the optimized travel path is determined by the flight controller in which the UAV along with the package can be commuted smoothly. Upon reaching the location of the receipt, the flight controller connected the Raspberry Pi microcomputer and provided an alert message to the command station as well as the receiver. Upon which the Image-based Authentication system is activated where the external camera connected to the Unmanned Aerial Vehicle controlled by the gimbal that is connected to the flight controller, captures the real-time photo as input. The system then analyses the live feed that is captured by the camera and then processed by the Microcomputer. The input image is then analyzed by the Image Processing Software and the facial patterns such as the face, eyes and lips of the receipt start by loading the input image and computing its face encoding, which is like a unique representation of that face. The code also converts the feed from the camera from BGR to RGB and detects faces in every frame that is being captured. In the said captured frames, it again computes the encoding for all the faces detected. The similarity index is then calculated upon which the servo is triggered to deliver the designed package to the recipient. The Raspberry Pi microcomputer is connected to the internet via a 4G Internet Dongle, that intern provides access to the servers for remote monitoring of the Unmanned Aerial Vehicles at times of emergency. After the successful package delivery that is captured by the camera. The Raspberry Pi alerts the Flight Controller to initiate the RTL (Return to Launch) Mode, enabling the Unmanned Aerial Vehicle to return to its Launch Position. The Launch Position Coordinates are stored beforehand with the help of the GPS Module, ensuring successful mission completion.
[0079] Referring to FIG. 3B, the Quadcopter is programmed using a software, for example, the Ardupilot Autopiloting Software. The coordinates of the recipient are programmed as the waypoints are set based on the optimized path. The altitude of the flight is determined by the user according to regional guidelines and regulations. The Home Location is set as the Quadcopter is forced to initiate the RTL based on the final delivery of the package. The Modes of the Unmanned Aerial Vehicle is programmed and calibrated on various factors of stability, geo position, speed and full throttle calibration of the transmitter using, for example, Ardupilot Mission Planner Software.
[0080] Referring to FIG. 3C, the specifically designed Facial Recognition Software analyses the live feed that is captured from the camera that is connected to the Raspberry Pi. The stored image that is shared via the cloud to the Raspberry Pi is analyzed as the facial pattern is constructed for further comparison with the real-time captured data. The Facial Recognition output from the Raspberry Pi is obtained via HDMI connection to provide clear insights into the operation as shown in Fig. 3. The similarity index of 94.07% of similarity index is obtained on testing the facial recognition software. Upon the Facial Recognition a servo motor connected to the Raspberry Pi is active and the package delivery is performed ensuring additional authentication. The Unmanned Aerial Vehicle is returned to the Home Location after the delivery operation is carried out.
[0081] FIG. 4 illustrates a flow diagram 400 for implementing a method for UAVs delivery system using image-based authentication, in accordance with an embodiment of the present disclosure.
[0082] In an embodiment, at step 402, the method may include receiving, information associated with an integrated system 102, associated with delivery of one or more objects to one or more users (106-1, 106-2, … 106-N).
[0083] In an embodiment, at step 404, the method may include determining, by the system 102, via a machine learning engine 222 an optimized path for the delivery of the one or more objects based on the received information.
[0084] In an embodiment, at step 406, the method may include analyzing, by the processor system 102, one or more features associated with the one or more users (106-1, 106-2 … 106-N) to authenticate the one or more users (106-1, 106-2 … 106-N) for the delivery of the one or more objects.
[0085] In an embodiment, at step 408, the method may include in response to a determination that the one or more users (106-1, 106-2 … 106-N) are authenticated, delivering, by the system 102, the one or more objects to the one or more users (106-1, 106-2 … 106-N) based on the analyzed one or more features.
[0086] FIG. 5 illustrates an exemplary computer system 500 in which or with which embodiments of the present invention can be utilized in accordance with embodiments of the present disclosure.
[0087] As shown in FIG. 5, the computer system 500 may include an external storage device 510, a bus 520, a main memory 530, a read only memory 540, a mass storage device 550, a communication port 560, and a processor 570. A person skilled in the art will appreciate that the computer system 500 may include more than one processor and communication ports. The processor 570 may include various modules associated with embodiments of the present invention. The communication port 560 may be any of an RS-232 port for use with a modem-based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. The communication port 560 may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects. The memory 530 may be a Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. The read-only memory 540 may be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for the processor 570. The mass storage 550 may be any current or future mass storage solution, which may be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays).
[0088] The bus 520 may communicatively couple the processor(s) 570 with the other memory, storage and communication blocks. The bus 520 may be, e.g. a Peripheral Component Interconnect (PCI)/PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor 570 to a software system.
[0089] Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to the bus 520 to support direct operator interaction with the computer system 500. Other operator and administrative interfaces may be provided through network connections connected through the communication port 560. The external storage device 510 may be any kind of external hard-drives, floppy drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc-Re-Writable (CD-RW), Digital Video Disk-Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[0090] While considerable emphasis has been placed herein on the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the invention. These and other changes in the preferred embodiments of the invention will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter to be implemented merely as illustrative of the invention and not as limitation.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0091] The present disclosure provides an Unmanned Aerial Vehicles (UAVs) delivery system using image-based authentication, and method thereof.
[0092] The present disclosure provides image-based authentication to ensure packages are delivered only to verified recipients, significantly reducing theft and mis-delivery risks.
[0093] The present disclosure provides a contactless solution that enhances safety and efficiency, operates autonomously, allowing for optimized path planning without delays from human couriers.
[0094] The present disclosure incorporates machine learning techniques and autonomous navigation for providing optimized delivery routes and improves the overall efficiency of the system.
[0095] The present disclosure provides direct package recipient verification through facial recognition.
[0096] The present disclosure enhances user experience by offering a seamless and intuitive delivery process with advanced security measures.
,CLAIMS:1. An integrated system (102), comprising:
a processor (202) communicatively coupled to an Unmanned Aerial Vehicle (UAV); and
a memory (204) operatively coupled with the processor (202), wherein said memory (204) stores instructions which, when executed by the processor (202), cause the processor (202) to:
receive information associated with delivery of one or more objects to one or more users (106-1, 106-2, … 106-N) through one or more computing devices (108-1, 108-2, … 108-N);
determine via a machine learning engine (222) an optimized path for the delivery of the one or more objects based on the received information;
analyze, one or more features associated with the one or more users (106-1, 106-2, … 106-N) to authenticate the one or more users (106-1, 106-2, … 106-N) for the delivery of the one or more objects; and
in response to a determination that the one or more users (106-1, 106-2, … 106-N) are authenticated, deliver the one or more objects to the one or more users (106-1, 106-2, … 106-N) based on the analyzed one or more features.
2. The integrated system (102) as claimed in claim 1, wherein to analyze the one or more features, the processor (202) is configured to:
receive, one or more images associated with the one or more users (106-1, 106-2, … 106-N) through an image acquisition unit configured with the UAV;
compare the received one or more images with one or more predefined inputs;
in response to a determination that the received one or more images match the one or more predefined inputs; and
subsequently authenticate the one or more users (106-1, 106-2, … 106-N) for the delivery of the one or more objects.
3. The integrated system (102) as claimed in claim 1, wherein the one or more images may comprise any or a combination of one or more facial patterns and a similarity index associated with the one or more users (106-1, 106-2, … 106-N).
4. The integrated system (102) as claimed in claim 2, wherein to deliver the one or more objects to the one or more users (106-1, 106-2, … 106-N), the processor (202) is configured to:
determine one or more GPS co-ordinates associated with the delivery of the one or more objects;
subsequently activate, the image-acquisition unit to record the one or more images associated with the one or more users (106-1, 106-2, … 106-N);
in response to a determination that the received one or more images match the one or more predefined inputs; and
enable delivery of the one or more objects to the one or more users (106-1, 106-2, … 106-N) based on the matched one or more images and the one or more predefined inputs.
5. The integrated system (102) as claimed in claim 1, wherein the processor (202) is configured to receive an alert and enable the UAV to relocate to a specified location based on the received alert.
6. A method (400) for delivery of objects, the method (400) comprising:
receiving (402) , by a processor (202), information associated with an integrated system (102), associated with delivery of one or more objects to one or more users (106-1, 106-2, … 106-N);
determining (404), by the processor (202),via a machine learning engine (222) an optimized path for the delivery of the one or more objects based on the received information;
analyzing (406), by the processor (202), one or more features associated with the one or more users (106-1, 106-2, … 106-N) to authenticate the one or more users (106-1, 106-2, … 106-N) for the delivery of the one or more objects; and
in response to a determination that the one or more users (106-1, 106-2, … 106-N) are authenticated, delivering (408), by the processor (202), the one or more objects to the one or more users (106-1, 106-2, … 106-N) based on the analyzed one or more features.
7. The method (400) as claimed in claim 6, wherein for analyzing the one or more features, the method comprises:
receiving, by the processor (202), one or more images associated with the one or more users (106-1, 106-2, … 106-N) through an image acquisition unit configured with the UAV;
comparing, by the processor (202), the received one or more images with one or more predefined inputs;
in response to a determination that the received one or more images match the one or more predefined inputs;
subsequently authenticating, by the processor (202), the one or more users (106-1, 106-2, … 106-N) for the delivery of the one or more objects.
8. The method (400) as claimed in claim 7, wherein for delivering the one or more objects to the one or more users (106-1, 106-2, … 106-N), the method comprises:
determining, by the processor (202), one or more GPS co-ordinates associated with the delivery of the one or more objects;
subsequently activating, by the processor (202), the image-acquisition unit to record the one or more images associated with the one or more users (106-1, 106-2, … 106-N);
in response to a determination that the received one or more images match the one or more predefined inputs;
enabling, by the processor (202), delivery of the one or more objects to the one or more users (106-1, 106-2, … 106-N) based on the matched one or more images and the one or more predefined inputs.
9. The method (400) as claimed in claim 6, comprising receiving, by the processor (202), an alert and enabling the UAV to relocate to a specified location based on the received alert.