Description:FIELD OF THE INVENTION

[0001] The present invention relates to a control system for controlling surveillance drones that is developed to optimize real-time flight dynamics, environmental responsiveness, data processing, and user interaction, thereby providing an autonomous solution for surveillance tasks. More specifically, the system also facilitates automated flight adjustments, GPS-independent navigation, real-time data transmission, and autonomous recovery from flight irregularities, thereby ensuring suitability for various applications including, but not limited to, security, reconnaissance, and surveillance in both indoor and outdoor environments.

BACKGROUND OF THE INVENTION

[0002] Operating surveillance drones manually presents several challenges. When controlling the drone, the operator must constantly adjust rotor speed and blade pitch to compensate for changing environmental conditions, like wind or temperature. This ongoing manual adjustment often proves difficult, especially in unpredictable weather. Furthermore, maintaining a stable video feed while controlling the drone requires the operator's full attention, which might be draining and lead to mistakes. Even small distractions or errors cause the drone to lose its course or miss vital footage. Navigating through complex areas with obstacles adds another layer of difficulty, as the operator must continuously steer the drone to avoid collisions, requiring quick reflexes and constant decision-making. In addition, when the drone experiences communication loss or encounters a flight anomaly, manual intervention is necessary to regain control. This reliance on the operator to fix issues lead to delays or loss of critical surveillance. These manual processes create inefficiencies, increase the risk of human error, and make long-term drone operations more challenging, particularly in dynamic environments.

[0003] Early systems were simple and required manual operation, often involving basic camera systems or rudimentary surveillance tools mounted on drones. These equipment’s provided limited control and had high operational costs. So, people also use high-definition cameras, and a variety of sensors, such as barometers, and proximity sensors for the operation. Despite the advancements the battery life of drones remains a significant limitation. The power demands of high-definition cameras, sensors, and data transmission systems drain the battery quickly, restricting the duration of flights. This is especially problematic for extended surveillance missions or in remote areas where recharging or replacing batteries is not feasible.

[0004] RU2709562C1 relates to attractions and can be used for entertainment or for training control of radio-controlled aircrafts. Method of controlling a drone is characterized by forming, using a user panel, commands for controlling a drone in a polygon space, wherein obstacles, including side and lower boundaries of the polygon, are determined as a set of points of space, to which the approach of the drone is prohibited for a distance closer to the pre-set value of the buffer zone, during flight of the drone, data on the position of the drone in space are obtained using on-board sensors, the obtained data are transmitted through wireless communication channels to the central computing device, through which the velocity vector of the drone and the approach to the obstacle are calculated, correcting the drone control command, reducing the speed of its approach to the obstacle, so that as the boundary of the buffer zone of the obstacle reaches the speed of approach of the drone with the obstacle tends to zero. Although RU’562 relates to a system and method of controlling the drones. But the cited invention unable to recover from communication breakdowns or flight-related interruptions, thereby requiring manual intervention under difficult conditions.

[0005] JPWO2020004366A1 discloses about an invention that includes a drone capable of maintaining high safety even during autonomous flight, that is, an unmanned aerial vehicle. A drone system is a drone system in which a pilot and a drone are connected to each other through a network NW and operate in cooperation with each other. The drone system has a plurality of different states, and each state By satisfying the specified conditions, it transitions to another state corresponding to the conditions, and multiple states can transition to multiple states based on the operation command from the user (including S7, the drone is a standby state. The drone system includes a battery for driving the drone and a low battery detection unit for detecting that the amount of electricity stored in the battery is below a predetermined value, and the drone system is based on the detection by the low battery detection unit. Transition to standby state. Though JP’366 relates to a method for controlling the drone system. But the cited inventions often lack in monitoring and assessing surveillance data in real time, which negatively impacts both operational effectiveness and the precision of critical decision-making.

[0006] Conventionally, many systems have been developed that are capable of controlling a surveillance drone. However, these existing systems fail to recover from disruptions in communication or flight which causes need for manual intervention in challenging environments. Additionally, these existing systems also fail in monitoring and analysing surveillance footage in real-time which affects operational efficiency and decision-making accuracy.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a system that requires to autonomously recover from disruptions in communication or flight, thereby allowing for continuous operation without manual intervention, even in challenging environments. In addition, the developed system also needs to enable real-time data collection and transmission while ensuring that surveillance footage is monitored and analyzed in real-time, irrespective of the operational environment, thus enhancing operational efficiency and decision-making accuracy.

OBJECTS OF THE INVENTION

[0008] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0009] An object of the present invention is to develop a system that autonomously adjusts flight parameters, including speed, blade pitch, and trajectory, based on real-time atmospheric conditions and environmental data.

[0010] Another object of the present invention is to develop a system that facilitates in altitude control and head-free navigation, for enhancing manoeuvrability and stability during flight operations without relying on external orientation cues.

[0011] Another object of the present invention is to develop a system that enables independent navigation in environments where GPS signals are unavailable, ensuring functionality in confined spaces such as indoors or urban areas, thereby providing reliable performance even in challenging locations.

[0012] Another object of the present invention is to develop a system that manages battery life by selectively deactivating non-essential functions, thereby maximizing the duration of flight and maintaining core operational capabilities.

[0013] Another object of the present invention is to develop a system that minimizes processing load while navigating complex environments, thereby enhancing performance and efficiency during autonomous operations.

[0014] Yet another object of the present invention is to develop a system that dynamically adjust data transmission rates and control parameters based on real-time network conditions, ensuring optimal performance in varying connectivity situations.

[0015] The foregoing and other objects, features, and advantages of the present invention will become readily apparent upon further review of the following detailed description of the preferred embodiment as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION

[0016] The present invention relates to a control system for controlling surveillance drones that is capable of providing a means for dynamically adjusting flight parameters in response to environmental conditions, thereby enabling efficient and stable operation during surveillance tasks.

[0017] According to an embodiment of the present invention, a control system for controlling surveillance drones, comprises of a body, a rotor blade mounted with the body to impart flight to the body, an adaptive propulsion module configured with a microcontroller controlling the rotor blade, dynamically adjusts rotor speed and blade pitch based on real-time atmospheric conditions, detected by environmental sensors embedded in the body, the adaptive propulsion module detects obstacles to calculate optimal trajectories with minimal computational overhead, for navigation through complex environments in an automated manner, a barometric pressure sensor in combination with a magnetometer, provided in the body for altitude control and head-free operation, an array of cameras installed on the body include a downwards facing first camera and four second cameras, with each of the second cameras aligned with a cardinal direction for capturing surveillance footage, an internet-based communication unit configured to transmit real-time video streams captured by the array of cameras and receive flight control commands for flight operation executed by the microcontroller, the communication unit is configured with a communication module based on pagekite tunneling protocol and port forwarding for distance-independent reception of flight control commands, a user interface adapted to be installed with a computing unit, to facilitate communication between the computing unit and the communication unit for reception of video stream and transmission of flight control commands, the user interface displays video stream from the facing first camera and four second cameras, simultaneously, and a self-revival unit configured with the microcontroller to autonomously recover from communication losses and flight anomalies.

[0018] According to another embodiment of the present invention, the system further includes a position hold module configured with the microcontroller, receives data from an optical flow sensor and a time-of-flight sensor disposed with the body to enable GPS-independent indoor navigation, an emergency power conservation module configured with the microcontroller monitors battery voltage curves and automatically deactivates non-essential cameras and sensors while maintaining core flight functions, activates regenerative braking during descent phases, and calculates the optimal return path based on current wind conditions and terrain to maximize remaining flight time, a computational load is dynamically balanced between the microcontroller and the computing unit, based on real-time assessment of network stability and battery status, a synchronisation module configured with the user interface, maintains operational continuity during switching between computing units, by transferring control state, camera calibrations, and navigation parameters between authorized computing units without interrupting flight operations enabling collaborative control, backup computing unit deployment during extended missions, and an artificial-intelligence based predictive connection management module integrated with the microcontroller to anticipate connectivity fluctuations by analysing historical connection quality patterns and environmental factors, to proactively adjust data transmission rates, compression protocols, and control protocol parameters prior to actual connection fluctuations.

[0019] While the invention has been described and shown with particular reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0020] These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
Figure 1 illustrates a front view of a control system for controlling surveillance drones;
Figure 2 illustrates a bottom view of the system; and
Figure 3 illustrates a perspective view of the system.

DETAILED DESCRIPTION OF THE INVENTION

[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

[0022] In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

[0023] As used herein, the singular forms “a,” “an,” and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.

[0024] The present invention relates to a control system for controlling surveillance drones that is capable of facilitating autonomous adjustment of flight settings, such as speed, blade angle, and flight path, in response to real-time atmospheric factors and environmental information, thereby ensuring optimal performance, stability, and energy efficiency during complex and dynamic flight scenarios.

[0025] Referring to Figure 1 and 2, a front view of a control system for controlling surveillance drones and a bottom view of the system are illustrated, respectively, comprising a body 101, a rotor blade 102 mounted with the body 101, an array of cameras 201, 103 installed on the body 101 include a downwards facing first camera 201 and four second cameras 103, a user interface adapted to be installed with a computing unit 104.

[0026] The system disclosed herein comprising a structural body 101, wherein at least one rotor blade 102 is operatively mounted with the body 101. The rotor blade 102 being configured to impart controlled aerodynamic lift and thrust to the body 101, thereby facilitating vertical take-off, sustained flight, maneuverability, and landing operations. The rotor blade 102 enabling the body 101 to perform stable flight patterns required for surveillance and monitoring applications across varied environmental and operational conditions.

[0027] The rotor blade 102 operates by rotating at high speed when powered by the drone’s motor, generating lift through aerodynamic force. As the motor turns the rotor shaft, each blade 102 cuts through the air at a specific angle, known as pitch. The pitch angle is dynamically controlled by the microcontroller to increase or decrease lift, depending on flight requirements. When lift exceeds the drone’s weight, it ascends; when reduced, it descends. Yaw, tilt, and pitch movements of the drone are achieved by varying the speed and pitch of individual blade 102. This coordination enables stable flight and precise directional control.

[0028] An adaptive propulsion module, integrated with the microcontroller, is configured to regulate the speed and pitch of the rotor blade 102 based on real-time atmospheric conditions, as detected by environmental sensors embedded within the drone’s body 101. The environmental sensors continuously monitor key atmospheric parameters, including air density, temperature, and humidity.

[0029] These sensors provide real-time data to the microcontroller, which, in turn, adjusts the rotor blade 102 speed and pitch accordingly to optimize flight performance. The system ensures that the drone adapts to changes in environmental conditions, maintaining stability and efficiency across a variety of operational environments, thereby enhancing overall flight control and endurance.

[0030] In an embodiment of the present invention the environmental sensors disclosed above are an air pressure sensor, a temperature sensor and a humidity sensor. The air pressure sensor operates by detecting the surrounding atmospheric pressure. When air enters the sensor, it presses against a diaphragm or membrane inside the sensor. This diaphragm deforms based on the pressure exerted by the air. The deformation is then measured electronically and converted into an electrical signal, which correlates to the atmospheric pressure. The sensor outputs a signal proportional to the pressure, allowing the microcontroller to assess altitude, air density, or environmental conditions, which is crucial for adjusting flight parameters such as rotor speed and blade 102 pitch in real-time.

[0031] The temperature sensor detects environmental temperature changes by measuring the variation in electrical resistance or thermoelectric voltage due to temperature fluctuations. The sensor converts these changes into an electrical signal, providing a precise temperature reading. This information is used by the microcontroller to adjust operational parameters such as rotor speed or blade 102 pitch based on environmental conditions, ensuring stable flight performance.

[0032] The humidity sensor detects the moisture level in the surrounding environment through changes in the electrical resistance or capacitance of a hygroscopic material. The material absorbs moisture from the air, leading to a measurable change in resistance or capacitance, which is then converted into an electrical signal. The microcontroller analyzes this data to adjust operational parameters, optimizing flight control and stability based on real-time humidity levels.

[0033] The adaptive propulsion module, in conjunction with the microcontroller, detects obstacles within the drone’s path by utilizing cameras, lidar, or ultrasonic sensors. These sensors provide real-time environmental data, which is processed by the microcontroller to assess the proximity and location of potential obstacles. Based on this data, the module calculates optimal flight trajectories that minimize computational load while ensuring safe navigation through complex environments.

[0034] The module dynamically adjusts the drone's flight parameters, including speed and rotor blade 102 pitch, to navigate around obstacles and maintain the desired flight path, enabling efficient autonomous navigation. The system operates with minimal computational overhead by streamlining data processing and utilizing pre-programmed flight protocols to facilitate smooth, real-time decision-making during operation.

[0035] A barometric pressure sensor and a magnetometer are integrally disposed within the body 101 and operatively coupled with the microcontroller. The barometric pressure sensor enables altitude determination by detecting atmospheric pressure changes, while the magnetometer facilitates head-free operation by determining directional orientation with respect to the Earth’s magnetic field. This integrated configuration allows the drone to maintain stable elevation and directional control, irrespective of its yaw axis orientation. The microcontroller receives and interprets signals from both sensors to execute precise altitude management and navigation functions during autonomous or remote operation.

[0036] The barometric pressure sensor measures atmospheric pressure by detecting the force exerted by air on a membrane within the sensor. As altitude increases, atmospheric pressure decreases. The sensor captures this variation and transmits analog or digital signals to the microcontroller, which then calculates the corresponding altitude. The pressure readings are continuously updated during flight to monitor changes in elevation. The microcontroller uses this real-time data to adjust rotor speed and blade 102 pitch, maintaining desired altitude. Sudden pressure changes are interpreted as ascent or descent, prompting automated stabilization.

[0037] In an embodiment of the present invention, the barometric pressure sensor provided within the body 101 is implemented using an MS5611 barometric pressure sensor. The sensor is operatively coupled with the microcontroller to provide high-resolution atmospheric pressure data, facilitating accurate altitude control.

[0038] The MS5611 barometric pressure sensor performs continuous pressure measurement by utilizing a high-resolution piezoresistive sensing element. The internal 24-bit ADC converts analog pressure inputs into precise digital values. Upon activation, the sensor initiates a digital command sequence from the microcontroller, triggering pressure and temperature readings. These raw outputs are compensated using predefined onboard adjustment values stored in the sensor's PROM. The compensated data is transmitted via I2C or SPI interface to the microcontroller. The microcontroller processes this data to determine altitude changes during flight. This process is repeated at defined intervals, supporting accurate real-time altitude adjustments and stabilization in varying atmospheric conditions.

[0039] The magnetometer detects the direction and strength of the Earth's magnetic field by measuring magnetic flux density across its X, Y, and Z axes. This data is relayed to the microcontroller, which interprets it to determine heading or directional orientation. Unlike GPS, the magnetometer provides absolute direction regardless of drone rotation. This enables head-free operation, allowing flight control inputs to remain consistent even when the drone changes its facing direction. The microcontroller continuously receives and processes magnetic readings to maintain orientation stability. The information ensures accurate directional control and supports autonomous navigation, especially in GPS-limited or indoor environments.

[0040] In an embodiment of the present invention, the magnetometer provided in the body 101 for altitude control and head-free operation is implemented as an HMC5883 magnetometer, which is operatively linked with the microcontroller to detect geomagnetic field vectors for determining the orientation of the drone with respect to magnetic north.

[0041] The HMC5883 magnetometer operates by continuously sampling magnetic field strength along three orthogonal axes (X, Y, and Z) using anisotropic magneto resistive sensors. These measurements are digitized via an internal ADC and transmitted to the microcontroller through the I2C interface. The microcontroller retrieves the magnetic vector data and applies soft-iron and hard-iron compensation protocols to correct for distortions. Using these corrected values, the system computes the drone’s heading relative to magnetic north. The magnetometer updates its readings in real time, allowing the microcontroller to maintain directional orientation and support head-free operation by correlating heading data with flight commands.

[0042] An array of cameras 201, 103 is structurally integrated with the body 101 and operatively connected to the system. The array includes a first camera 201 oriented downward to monitor ground-level activity directly beneath the drone. In addition, four second cameras 103 are spatially positioned to correspond with the four cardinal directions—north, south, east, and west, to collectively provide a comprehensive 360-degree horizontal field of view (as shown in figure 3).

[0043] This spatial arrangement facilitates continuous multi-directional visual surveillance, enabling simultaneous capture of environmental conditions, movement patterns, and activities occurring around the operational perimeter. The visual data acquired by the array is transmitted in real-time to the control interface for monitoring, archival, or subsequent analytical processing by authorized personnel, thereby supporting uninterrupted situational awareness and effective surveillance coverage across diverse operational contexts.

[0044] The downward-facing first camera 201 continuously capturing vertical imagery of the area directly below the drone. The camera's lens is calibrated for high-resolution imaging and functions under various lighting conditions. Captured visual data is instantly processed through the microcontroller and compressed for transmission. The stream is relayed to the user interface for live monitoring or storage. Autofocus and exposure settings are dynamically adjusted mid-flight to maintain clarity. During hovering or low-altitude flight, the camera supports detailed ground surveillance. If motion is detected in the frame, frame rates may be automatically increased for better visual tracking precision.

[0045] Each of the four cameras 103 aligned to the cardinal directions (north, south, east, west) operates in parallel, capturing horizontal imagery surrounding the drone. These cameras 103 continuously feed visual data into the microcontroller, which synchronizes the streams and adjusts resolution based on bandwidth availability. Edge detection and motion sensitivity protocols are applied during real-time processing. The cameras 103 operate with stabilized lenses to reduce motion blur during flight. Rotational shifts in the drone’s orientation trigger automatic calibration to maintain directional accuracy. The combined feed creates a panoramic situational view, enabling uninterrupted 360-degree surveillance, especially useful when tracking moving objects or monitoring wide areas.

[0046] An internet-based communication unit is operatively configured to establish a bi-directional data transmission link between the surveillance drone and an external computing interface. The communication unit is integrated within the body 101 and is adapted to transmit real-time video streams obtained from the array of onboard cameras 201, 103 to a remote user interface, thereby facilitating live monitoring of surveillance footage.

[0047] Additionally, the communication unit is configured to receive flight control commands issued from a remote computing unit 104 and transmit the same to the microcontroller for execution. This ensures uninterrupted data flow over secure network channels, allowing for responsive command execution and continuous surveillance functionality throughout the drone’s operational cycle.

[0048] The communication unit is operatively integrated with a communication module specifically configured on the basis of the PageKite tunneling protocol, in combination with port forwarding, to ensure uninterrupted and distance-independent reception of flight control commands. The application of the PageKite tunneling protocol enables the communication unit to securely expose the drone's local services to the internet without requiring a static IP address, thereby maintaining seamless communication even behind firewalls or NAT (Network Address Translation) systems.

[0049] Simultaneously, the port forwarding arrangement is employed to direct external control signals to designated internal network ports, ensuring accurate delivery of command data to the microcontroller responsible for flight operations. This dual-layer communication configuration support stable, scalable, and secure remote operation of the drone, independent of physical proximity to the operator or network architecture, thereby facilitating compliance with operational and regulatory standards applicable to remote-controlled surveillance drones.

[0050] A user interface is operatively adapted for installation within the computing unit 104 to enable bidirectional communication between the computing unit 104 and the communication unit integrated with the surveillance drone. This interface serves as a control and monitoring gateway, wherein the reception of real-time video streams captured by the drone is facilitated through an established data transmission link. Concurrently, flight control commands originating from the computing unit 104 are transmitted through the same interface, ensuring the drone responds promptly to operator inputs.

[0051] Also, the user interface is configured to simultaneously display the video stream received from the downwards facing first camera 201 and the four second cameras 103, each oriented in alignment with a respective cardinal direction. This concurrent display functionality allows the operator to obtain a comprehensive, real-time visual overview of the surveillance environment without requiring manual toggling between individual camera feeds. The system ensures seamless streaming and synchronization of all five video sources through the computing unit 104, thereby enhancing situational awareness and enabling effective monitoring, tracking, and decision-making during flight operations. The simultaneous multi-angle visualization provided by the user interface supports uninterrupted oversight of both the drone’s immediate surroundings and broader navigational context.

[0052] A self-revival unit is operatively configured with the microcontroller and adapted to autonomously initiate recovery protocols in the event of communication losses or flight anomalies, without requiring manual intervention. Upon detection of a disruption in signal transmission or deviation from expected flight behaviour, the self-revival unit executes pre-programmed corrective measures, such as stabilizing flight posture, entering a hover mode, or initiating a return-to-base sequence, based on the nature and severity of the anomaly. The unit continuously monitors operational parameters in view of allowing for real-time assessment and immediate corrective action. This ensures that flight continuity is maintained, mission data is preserved, and potential safety hazards are mitigated, particularly in complex or remote environments where external control may be temporarily unavailable.

[0053] In an embodiment of the present invention, upon detection of a communication loss between the drone and the computing unit 104, the self-revival unit, in cooperation with the microcontroller and a GPS module, initiates a Return-to-Home (RTH) mode. In this mode, the drone is configured to first ascend to a predefined altitude sufficient to avoid surrounding obstacles. Upon reaching the safe altitude, the drone navigates to a previously recorded Home point, which is stored in its onboard memory at the time of initial take-off. Thereafter, the system autonomously initiates a controlled descent and executes landing procedures at the Home point. This sequence is performed without manual intervention and is designed to safeguard both the drone and any associated surveillance data during unexpected loss of control signal.

[0054] In another embodiment of the present invention, when a communication loss is temporarily detected in an environment where GPS signals are reliably available, the self-revival unit, configured with the microcontroller, triggers a Loiter or Hold mode. In this mode, the drone maintains a hover position at the current GPS coordinates and altitude for a predetermined period, as stored in the internal memory of the control unit. This mode is specifically designed to accommodate temporary signal interferences or minor disruptions in connectivity. If reconnection is established within the timeframe, the system resumes normal flight operations. If not, the self-revival unit may transition into a secondary safety mode, such as Return-to-Home or Auto-Land, depending on pre-configured parameters.

[0055] In another embodiment of the present invention, in the absence of GPS signal availability or when hovering timeout is exceeded, the self-revival unit is configured to activate an Auto-Land mode. In such case, the drone is instructed by the microcontroller to initiate a gradual and stable descent at its current location, ensuring a safe landing with minimal lateral displacement. This protocol is particularly applied in indoor navigation scenarios or during conditions of low battery voltage, where extended hovering or navigation could pose operational risks. The descent and landing sequence is executed through onboard sensors including barometric pressure and proximity sensors, ensuring terrain-aware vertical maneuvering.

[0056] Yet another embodiment of the present invention, for surveillance drones operating under autonomous mission parameters, the self-revival unit is adapted to activate a Mission Resume mode upon detection of transient communication loss during mid-mission. In this configuration, the microcontroller continues executing the pre-uploaded mission protocol stored locally in non-volatile memory. The drone follows its designated flight path, captures surveillance data using the array of cameras 201, 103, and maintains altitude and heading through onboard navigation modules. Once communication is reestablished, the computing unit 104 may either take over real-time control or allow the drone to complete its autonomous mission. This embodiment ensures minimal interruption in surveillance tasks and maintains operational consistency.

[0057] A position hold module operatively linked with the microcontroller is configured to receive and process data from an optical flow sensor and a time-of-flight sensor, both structurally integrated within the body 101. The module enables stable, GPS-independent navigation in indoor or obstructed environments by utilizing relative motion data and precise distance measurements.

[0058] The microcontroller, based on the inputs from the sensors, calculates and continuously updates the drone’s relative position and velocity, thereby facilitating autonomous flight stabilization and controlled navigation within confined or signal-denied areas, without reliance on satellite-based positioning systems.

[0059] The optical flow sensor captures successive low-resolution images of the ground or surface beneath the drone via first camera 201. By comparing pixel displacement between consecutive frames, the sensor determines the direction and speed of motion relative to the ground. This displacement data is then converted into velocity vectors, which are transmitted to the microcontroller. The microcontroller uses this information to estimate position shifts over time, allowing it to make adjustments to rotor speed for stabilizing the drone's position. This ongoing process allows for steady hovering and lateral motion control, especially in GPS-denied environments like indoors or narrow passages.

[0060] The time-of-flight (ToF) sensor emits a beam of light, typically infrared, toward a target surface and measures the time taken for the reflected light to return. The measured time is used to calculate the exact distance between the drone and the surface or obstacle. These measurements are sent to the microcontroller in real-time. The microcontroller integrates this distance data with other positional inputs to maintain accurate altitude and prevent collisions. When the drone approaches surfaces, such as walls or ceilings, the microcontroller commands altitude or direction adjustments accordingly, ensuring precise vertical control and obstacle avoidance during indoor navigation.

[0061] An emergency power conservation module integrated with the microcontroller is configured to monitor real-time battery voltage curves to assess available energy reserves with precision. Upon identification of diminishing power thresholds or abnormal battery drain, the module autonomously initiates a predefined sequence of energy optimization protocols. These protocols include automatic deactivation of non-essential components, such as cameras 201, 103 and sensors, while ensuring continuous operation of core flight functionalities required for safe aerial maneuverability.

[0062] Additionally, during descent phases, the module activates regenerative braking arrangement designed to convert kinetic energy into usable electrical energy, thereby supplementing remaining battery life. Concurrently, the module processes environmental data, including wind direction, speed, and topographical layout, to compute and initiate an optimal return flight path. This configuration is strategically implemented to extend flight duration under emergency conditions and to secure the safe retrieval of the drone with minimal energy consumption, even in adverse operational scenarios.

[0063] A computational load balancing functionality is operatively established between the microcontroller and the computing unit 104, wherein the functionality is configured to dynamically allocate processing tasks in accordance with real-time evaluations of network stability and battery health parameters. In operation, the system continuously monitors fluctuations in network connectivity and the current battery charge level, utilizing this data to determine the most efficient division of computational responsibilities.

[0064] Upon detecting reduced network stability or declining battery status, the system responsively redistributes processing functions to the component—either the microcontroller or the computing unit 104—that is optimally positioned to execute the tasks without compromising operational continuity or data integrity. This dynamic allocation ensures uninterrupted processing of mission-critical operations while preventing system overloads, thereby maintaining consistent performance, reducing latency in data handling, and prolonging the overall operational lifespan of the surveillance drone under variable mission conditions.

[0065] Further a synchronisation module operatively configured with the user interface is structured to uphold uninterrupted operational continuity during transitions between multiple computing unit 104. The module is functionally adapted to facilitate seamless transfer of critical control state data, including but not limited to camera calibration settings and navigation parameters, from one authorized computing unit 104 to another. Such transfer is executed in a manner that does not disrupt or suspend ongoing flight operations, thereby ensuring persistent control and real-time surveillance continuity. This configuration enables collaborative management of the drone by multiple authorized operators and supports the deployment of backup computing unit 104, particularly during extended or mission-critical operations, where continuous command and data reception are imperative.

[0066] Furthermore, an artificial intelligence-based predictive connection management module, integrated within the microcontroller, is designed to estimate potential fluctuations in connectivity by analyzing historical data related to connection quality and environmental influences. This module employs machine learning protocols to study past connection performance and environmental conditions, allowing it to predict when connectivity might degrade.

[0067] Based on these predictions, the module proactively adjusts data transmission rates, compression protocols, and control protocol parameters in advance of any fluctuations, thereby optimizing the system's performance and ensuring stable communication during potential disruptions. This proactive approach minimizes the risk of data loss or lag, ensuring seamless and reliable operation in dynamic and variable environments. The integration of such predictive capabilities allows the system to adapt to changing conditions without manual intervention, thus enhancing the overall efficiency and robustness of the communication network.

[0068] Moreover, a battery is associated with the system for powering up electrical and electronically operated components associated with the system and supplying a voltage to the components. The battery used herein is preferably a Lithium-ion battery which is a rechargeable unit that demands power supply after getting drained. The battery stores the electric current derived from an external source in the form of chemical energy, which when required by the electronic component of the system, derives the required power from the battery for proper functioning of the system.

[0069] The present invention works best in the following manner, where the system as disclosed comprises of the body 101, the rotor blade 102 which is mounted with the body 101 to impart flight to the body 101. The adaptive propulsion module configured with the microcontroller controlling the rotor blade 102, dynamically adjusts rotor speed and blade 102 pitch based on real-time atmospheric conditions, detected by environmental sensors. Also, the adaptive propulsion module detects obstacles to calculate optimal trajectories with minimal computational overhead, for navigation through complex environments in the automated manner. The barometric pressure sensor in combination with the magnetometer, provided in the body 101 for altitude control and head-free operation. The array of cameras 201, 103 includes the downwards facing first camera 201 and four second cameras 103, with each of the second cameras 103 aligned with the cardinal direction for capturing surveillance footage. Thereafter the internet-based communication unit configured to transmit real-time video streams captured by the array of cameras 201, 103 and receive flight control commands for flight operation executed by the microcontroller. The communication unit is configured with the communication module which is based on pagekite tunneling protocol and port forwarding for distance-independent reception of flight control commands. The user interface adapted to be installed with the computing unit 104, to facilitate communication between the computing unit 104 and the communication unit for reception of video stream and transmission of flight control commands.

[0070] In continuation, the user interface also displays video stream from the facing first camera 201 and four second cameras 103, simultaneously. Afterwards the self-revival unit configured with the microcontroller to autonomously recover from communication losses and flight anomalies. The position hold module configured with the microcontroller, receives data from the optical flow sensor and the time-of-flight sensor disposed with the body 101 to enable GPS-independent indoor navigation. The emergency power conservation module configured with the microcontroller monitors battery voltage curves and automatically deactivates non-essential cameras 201, 103 and sensors while maintaining core flight functions. Also, the module activates regenerative braking during descent phases, and calculates the optimal return path based on current wind conditions and terrain to maximize remaining flight time. Further the computational load is dynamically balanced between the microcontroller and the computing unit 104, based on real-time assessment of network stability and battery status. Furthermore, the synchronisation module configured with the user interface, maintains operational continuity during switching between computing unit 104, by transferring control state, camera calibrations, and navigation parameters between authorized computing unit 104 without interrupting flight operations. Moreover, the artificial-intelligence based predictive connection management module integrated with the microcontroller to anticipate connectivity fluctuations by analysing historical connection quality patterns and environmental factors, to proactively adjust data transmission rates, compression protocols, and control protocol parameters prior to actual connection fluctuations.

[0071] Although the field of the invention has been described herein with limited reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternate embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention. , Claims:1) A control system for controlling surveillance drones, comprising a body 101, a rotor blade 102 mounted with said body 101 to impart flight to said body 101, said control system comprising:

i) an adaptive propulsion module configured with a microcontroller controlling said rotor blade 102, dynamically adjusts rotor speed and blade 102 pitch based on real-time atmospheric conditions, detected by environmental sensors embedded in said body 101;
ii) a barometric pressure sensor in combination with a magnetometer, provided in said body 101 for altitude control and head-free operation;
iii) an array of cameras 201, 103 installed on said body 101 for capturing surveillance footage;
iv) an internet-based communication unit configured to transmit real-time video streams captured by said array of cameras 201, 103 and receive flight control commands for flight operation executed by said microcontroller;
v) a user interface adapted to be installed with a computing unit 104, to facilitate communication between said computing unit 104 and said communication unit for reception of video stream and transmission of flight control commands;
vi) a self-revival unit configured with said microcontroller to autonomously recover from communication losses and flight anomalies; and
vii) a position hold module configured with said microcontroller, receives data from an optical flow sensor and a time-of-flight sensor disposed with said body 101 to enable GPS-independent indoor navigation.

2) The system as claimed in claim 1, wherein said adaptive propulsion module detects obstacles to calculate optimal trajectories with minimal computational overhead, for navigation through complex environments in an automated manner.

3) The system as claimed in claim 1, wherein said environmental sensors detect air density, temperature and humidity.

4) The system as claimed in claim 1, wherein said array of cameras 201, 103 include a downwards facing first camera 201 and four second cameras, with each of the second cameras 103 aligned with a cardinal direction.

5) The system as claimed in claim 1, wherein said communication unit is configured with a communication module based on pagekite tunneling protocol and port forwarding for distance-independent reception of flight control commands.

6) The system as claimed in claim 1, wherein an emergency power conservation module configured with said microcontroller monitors battery voltage curves and automatically deactivates non-essential cameras 201, 103 and sensors while maintaining core flight functions, activates regenerative braking during descent phases, and calculates the optimal return path based on current wind conditions and terrain to maximize remaining flight time.

7) The system as claimed in claim 1, wherein a synchronisation module configured with said user interface, maintains operational continuity during switching between computing unit 104, by transferring control state, camera calibrations, and navigation parameters between authorized computing unit 104 without interrupting flight operations enabling collaborative control, backup computing unit 104 deployment during extended missions.

8) The system as claimed in claim 1, wherein computational load is dynamically balanced between said microcontroller and said computing unit 104, based on real-time assessment of network stability and battery status.

9) The system as claimed in claim 1, wherein an artificial-intelligence based predictive connection management module integrated with said microcontroller to anticipate connectivity fluctuations by analysing historical connection quality patterns and environmental factors, to proactively adjust data transmission rates, compression protocols, and control protocol parameters prior to actual connection fluctuations.

10) The system as claimed in claim 1, wherein said user interface displays video stream from said facing first camera 201 and four second cameras 103, simultaneously.