Anti-drowning identification and emergency rescue intelligent equipment and rescue method

Abstract

The invention provides anti-drowning identification and emergency rescue intelligent equipment and a rescue method, and relates to the field of water surface rescue, and the equipment comprises an identification module, a data fusion perception decision module, a control module and an execution module; the recognition module adopts a binocular camera on the water surface to capture images on the water surface at the same time from slightly different angles, and the distance and the position of a target are determined by calculating the difference between the images. Terahertz waves are emitted under the water surface through the terahertz wave emitter, the waves penetrate through a water body and interact with an underwater object, and the reflected waves are captured by the receiver. A three-dimensional image of an underwater object is constructed by analyzing the intensity and phase of a reflected wave, measured data is transmitted to a data fusion perception decision module, a binocular camera and a terahertz wave technology are combined for use, the accuracy and efficiency of water surface and underwater target recognition are improved, the rescue and salvage efficiency is improved, and the rescue and salvage efficiency is improved. And the safety risk of rescue workers is reduced, the public safety is enhanced, and great social and economic values are achieved.

Description

Technical Field

[0001] The present invention relates to the field of water rescue, and in particular to an anti-drowning identification and emergency rescue intelligent equipment and a rescue method. Background Art

[0002] With the increase in water activities and shipping, accidents such as drowning and ship failure occur from time to time, and effective rescue equipment is needed to ensure the safety of personnel. Traditional rescue and salvage methods often rely on divers or simple salvage tools. These methods are inefficient in complex or dangerous water environments, have low operating accuracy, are greatly affected by the environment, and pose a threat to the safety of divers. Different water environments (such as oceans, rivers, and lakes) pose different challenges to rescue and salvage equipment, requiring the equipment to be able to adapt to different water quality and meteorological conditions. With the development of automation technology, the ability to remotely operate and autonomously perform tasks has received increasing attention, which can reduce the direct involvement of personnel in dangerous environments. Summary of the invention

[0003] In order to solve the problems of target recognition, operating accuracy, environmental adaptability, safety and efficiency of the above-mentioned existing water rescue and salvage equipment, the present invention has researched and developed an anti-drowning identification and emergency rescue intelligent equipment and rescue method, which can simultaneously identify and locate targets on the water surface and underwater, improve the target detection capability in complex water environments, especially in low visibility or turbid underwater environments, and can accurately classify and identify targets and formulate optimal salvage strategies.

[0004] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: an anti-drowning identification and emergency rescue intelligent equipment, including an identification module, a data fusion perception decision module, a control module, and an execution module;

[0005] The recognition module is used to obtain the distance and position data of the surface and underwater targets, distinguish different targets, and transmit the data to the data fusion perception decision module;

[0006] The data fusion perception decision module is used to comprehensively analyze and fuse the data provided by the recognition module to obtain more accurate target information; according to the state and environmental conditions of the target, the decision module will formulate the optimal salvage strategy, including selecting appropriate grabbing tools and salvage paths, generating decision signals, and transmitting the decision signals to the control module;

[0007] The control module receives instructions from the decision module and converts these instructions into specific control signals;

[0008] The execution module is used to receive the corresponding execution signal to ensure that the mechanical gripper can rescue the person in distress.

[0009] Specifically, in some embodiments, the recognition module of the present invention uses a binocular camera on the water surface to simultaneously capture images on the water surface from slightly different angles, and determines the distance and position of the target by calculating the difference between the images. Under the water surface, terahertz waves are emitted by a terahertz wave transmitter, the waves penetrate the water body and interact with underwater objects, and the reflected waves are captured by a receiver. By analyzing the intensity and phase of the reflected waves, a three-dimensional image of the underwater object can be constructed, and the measured data can be transmitted to the data fusion perception decision module; preferably, the frequency range of terahertz corresponds to 0.1~10THz (THz=10 12 Hz).

[0010] Specifically, in some embodiments, the data fusion perception decision module of the present invention combines the data provided by the surface camera system and the underwater terahertz wave detection system, fuses the two different data sources through an algorithm, creates a comprehensive surface and underwater environment model, and uses machine learning and artificial intelligence technology to conduct in-depth analysis of the fused data, identify and classify target objects, and make the optimal salvage decision based on the characteristics of the target and environmental conditions, and transmit the decision to the control module.

[0011] Preferably, the control module is responsible for the motion planning of the robot arm and gripper, including path planning, speed control and torque regulation.

[0012] Preferably, the control module receives the decision signal from the data fusion perception decision module, generates precise control signals for the robot arm and gripper, converts the signal output by the control card into instructions that the motor can understand, and receives the feedback signal from the execution module through the sensor interface.

[0013] Specifically, in some embodiments, the execution module of the present invention receives precise control signals from the control module, grasps objects through the gripper, and provides status feedback of the robotic arm and the gripper.

[0014] Another object of the present invention is to provide a drowning prevention identification and emergency rescue method, comprising the following steps:

[0015] S1. Obtain the distance and position data of the surface and underwater targets, and distinguish different targets; use a binocular camera on the water surface to simultaneously capture images on the water surface from slightly different angles, and determine the distance and position of the target by calculating the difference between the images; emit terahertz waves under the water surface through a terahertz wave transmitter, the waves penetrate the water body and interact with the underwater objects, and the reflected waves are captured by the receiver; construct a three-dimensional image of the underwater object by analyzing the intensity and phase of the reflected waves;

[0016] S2. Comprehensively analyze and integrate the data obtained in step S1 to obtain more accurate target information; formulate the optimal salvage strategy according to the state and environmental conditions of the target;

[0017] S3. Control the mechanical gripper through control signals to rescue people in distress.

[0018] Compared with the prior art, the present invention has the following beneficial effects:

[0019] The present invention can quickly and accurately identify and locate targets in complex water environments by integrating binocular cameras and terahertz wave detection technology, thereby greatly improving the efficiency of rescue and salvage. The direct participation of divers in dangerous environments is reduced, and the safety of the rescue process is improved through remote operation and automation technology. The targets can be accurately classified and identified, and the optimal salvage strategy can be formulated. The present invention can work under different water quality and meteorological conditions, including at night or in low visibility environments, which enables it to play a role in a wider range of situations. At the same time, the present invention is not only suitable for personnel rescue, but also for a variety of tasks such as object salvage and environmental monitoring, which increases the practicality and application scope of the equipment. The modular design makes the equipment easier to maintain and upgrade, and can be flexibly adjusted and optimized according to actual needs and technological development. As an advanced rescue and salvage tool, this design can provide new tools and methods for scientific research, and at the same time bring innovative solutions to the field of water rescue and salvage.

[0020] Instruction Manual

[0021] Figure 1 An exemplary implementation diagram of an anti-drowning identification and emergency rescue intelligent equipment is proposed for the present invention.

[0022] Figure 2 Schematic diagram of the data fusion perception decision module in the present invention;

[0023] Figure 3 It is a schematic diagram of the control module in the present invention;

[0024] Figure 4 It is a schematic diagram of the execution module in the present invention. DETAILED DESCRIPTION

[0025] In order to make the technical scheme of the present invention more clearly understood by those skilled in the art, the following embodiments are listed for illustration. It should be pointed out that the following embodiments do not limit the protection scope of the present invention.

[0026] See also Figure 1 , an anti-drowning identification and emergency rescue intelligent equipment of the present invention includes an identification module, a data fusion perception decision module, a control module, and an execution module;

[0027] The recognition module uses binocular cameras on the water surface to capture images on the water surface from slightly different angles at the same time, and determines the distance and position of the target by calculating the difference between the images. Under the water surface, terahertz waves are emitted by a terahertz wave transmitter. The waves penetrate the water body and interact with underwater objects, and the reflected waves are captured by the receiver. By analyzing the intensity and phase of the reflected waves, a three-dimensional image of the underwater object can be constructed, and the measured data can be transmitted to the data fusion perception decision module.

[0028] The data fusion perception decision module is used to comprehensively analyze and fuse the data provided by the recognition module to obtain more accurate target information. Combined with the surface and underwater data, a three-dimensional model of the target is constructed, and the stability and salvage difficulty of the target are evaluated. According to the state of the target and environmental conditions, the decision module will formulate the optimal salvage strategy, including selecting appropriate grabbing tools and salvage paths, generating decision signals, and transmitting the decision signals to the control module.

[0029] The control module receives instructions from the decision module and converts these instructions into specific control signals. The control module is responsible for the motion planning of the robot arm and gripper, including path planning, speed control and torque regulation. At the same time, the control module also needs to monitor the status of the equipment to ensure the stability and safety of the operation. The control module generates an execution signal and transmits the execution signal to the execution module.

[0030] The execution module is used to receive the corresponding execution signal to ensure that the mechanical gripper can rescue the person in distress.

[0031] Another embodiment of the present invention also provides an anti-drowning identification and emergency rescue method, which realizes surface and underwater target identification and positioning by integrating binocular cameras and terahertz wave detection technology. First, the binocular camera captures the stereo image on the water surface, while the terahertz wave detection system emits terahertz waves and receives their reflected signals to generate a three-dimensional image of the underwater target. Next, the data fusion perception decision module processes and analyzes the collected data, identifies and classifies the target objects, and formulates the optimal salvage strategy. Then, the control module generates a specific control signal based on the decision result to drive the manipulator and gripper to perform the salvage task. Finally, the sensor of the execution module provides real-time feedback to help the control module adjust the behavior of the manipulator and gripper to ensure the accuracy and safety of the operation. The whole process realizes efficient and safe water rescue and salvage, and improves the rescue efficiency and success rate.

[0032] In one embodiment, the recognition module includes a binocular camera module and a terahertz wave module;

[0033] The binocular camera uses infrared shortwave for detection, which can greatly improve the target recognition and tracking capabilities at night or in harsh environments, which is crucial for timely discovery and rescue of people in distress. The binocular camera usually includes an infrared light source, an infrared filter, two cameras, a lens, an image sensor, a processor, a bracket and a positioning device, a data interface, and a software algorithm;

[0034] The infrared light source is used to generate infrared short-wave light;

[0035] The cameras are used to capture two slightly different perspectives of the same scene. The two cameras are placed together with their fields of view slightly overlapping. This configuration simulates human binocular vision, so that depth information of the scene can be calculated;

[0036] The lens is used to focus and adjust the amount of light entering the camera. The quality of the lens directly affects the clarity and field of view of the image. The infrared filter is installed on the lens of the camera to filter out all non-infrared short-wave light and only allow infrared light to pass through, so that the camera is specifically used for infrared short-wave imaging;

[0037] The image sensor is used to convert light into electrical signals. Each camera includes an image sensor, which is usually a CCD (charge coupled device) or CMOS (complementary metal oxide semiconductor) sensor;

[0038] The processor is used to process the data collected from the two image sensors, perform image correction, synchronization, de-distortion and other image processing tasks, and the collected image data can be used for later analysis, such as accident reconstruction, rescue effect evaluation or equipment performance optimization. The binocular camera module usually includes a processor or image processing unit;

[0039] The bracket and positioning device are used to maintain a fixed distance and angle between the two cameras, ensuring that the images captured by the two cameras are synchronized and can be used for accurate stereo vision calculation;

[0040] The data interface is used to transmit the processed image data to the main control system or other equipment;

[0041] The software algorithm is used to extract depth information from images captured by two cameras, including stereo matching, disparity calculation and depth map generation.

[0042] The terahertz wave module includes a terahertz wave transmitter, a terahertz wave receiver, a signal processing unit, a data transmission interface, a terahertz wave lens and antenna, a power management unit, and a control system;

[0043] The terahertz wave transmitter is used to generate and emit terahertz waves. Terahertz waves are located between microwaves and infrared rays in the electromagnetic spectrum and have the ability to penetrate non-conductive materials (such as plastics, paper, wood, cloth, etc.), but have poor penetration into conductive media such as water.

[0044] The terahertz wave receiver is used to receive and detect the terahertz wave reflected or transmitted by the target object. By analyzing the received terahertz wave, information of the target object, such as shape, density, composition, etc., can be obtained.

[0045] The signal processing unit is used to process the received terahertz wave signal and convert it into usable data, which includes steps such as amplifying weak signals, removing noise, and extracting useful information.

[0046] The data transmission interface is used to transmit the processed data to the main control system or other equipment for further analysis and processing;

[0047] The terahertz wave lens and antenna are used for focusing and directing the emission and reception of terahertz waves. The design of the lens and antenna is crucial to improving the detection range and resolution of terahertz waves.

[0048] The power management unit is used to provide a stable power supply to the terahertz wave transmitter and receiver to ensure that they can work continuously and stably;

[0049] The control system is used to control the on and off of the terahertz wave transmitter and adjust the transmission parameters (such as frequency, power, pulse width, etc.);

[0050] In one embodiment, the data fusion perception decision module includes a sensor data input interface, a data preprocessing unit, a feature extraction module, a data fusion unit, a perception unit, a decision logic unit, a user interaction interface, and a communication interface;

[0051] The sensor data input interface is used to receive data from different sensors, including binocular cameras, terahertz wave detection systems, etc.;

[0052] The data preprocessing unit is used to preprocess the raw sensor data, including denoising, correction, synchronization, etc., to ensure the consistency and reliability of the data;

[0053] The feature extraction module is used to extract key features such as shape, size, color, texture, etc. from the preprocessed data to provide a basis for subsequent analysis and decision-making;

[0054] The data fusion unit is used to fuse data from different sensors to create a comprehensive environment model to provide more comprehensive information;

[0055] The perception unit is used to analyze the fused data, identify and classify target objects using machine learning and artificial intelligence technologies;

[0056] The decision logic unit is used to formulate an optimal salvage strategy and action plan according to the analysis results of the perception unit;

[0057] The user interaction interface is used to provide a user interface that enables the operator to monitor the status of the equipment, adjust settings and guide the salvage process;

[0058] The communication interface is used to communicate with other modules and external systems, transmit data and receive instructions;

[0059] In one embodiment, the control module includes a main controller, an actuator interface, a sensor interface, a communication interface, a power management unit, and a fault detection and safety protection unit;

[0060] The main controller serves as the core of the entire control system and is used to receive instructions from the data fusion perception decision module and coordinate the work of various execution components.

[0061] The actuator interface is used to interface with actuator components such as a robotic arm, gripper, and driver, receive instructions from the main controller, and convert them into signals that the actuator components can understand.

[0062] The sensor interface is used to receive feedback signals from the actuator, such as position, force, speed, etc., and transmit them to the main controller for real-time adjustment.

[0063] The communication interface is used to communicate with other modules and external systems, transmit control instructions and receive feedback information.

[0064] The power management unit is used to provide a stable power supply for the control module and ensure normal operation under different environmental conditions.

[0065] The fault detection and safety protection unit is used to monitor the operating status of the equipment, detect potential faults, and take safety measures when necessary, such as stopping operation or sounding an alarm.

[0066] In one embodiment, the execution module includes a robotic arm, gripper, drive system, sensors, connectors and interfaces, power and energy management system, protection and housing;

[0067] The robotic arm is used to perform precise operations in water, including grabbing, moving and releasing objects. The robotic arm is usually composed of multiple joints and links, each of which is driven by one or more motors.

[0068] The gripper is the actuator at the end of the robot arm, which is used to grab and release objects. The design of the gripper depends on the type of object to be grabbed, and can be a clamp, electromagnetic chuck or other form.

[0069] The drive system is used to provide power for the robot arm and the gripper, and includes a motor, a transmission device and a control system. The drive system is responsible for controlling the movement speed and direction of the robot arm and the gripper.

[0070] The sensors include position sensors, force sensors, etc., which are used to provide status feedback of the robot arm and gripper to ensure the accuracy and safety of the operation.

[0071] The connectors and interfaces are used to connect the robotic arm, gripper and drive system to ensure that they can work together.

[0072] The power supply and energy management system is used to provide a stable power supply to the execution module and manage energy usage to ensure the efficiency and reliability of the device during long-term operation.

[0073] The protection and housing are used to provide the execution module with necessary protection and waterproof housing to prevent the external environment from damaging the internal components.

[0074] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

[0075] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An anti-drowning identification and emergency rescue intelligent equipment, characterized in that: It includes recognition module, data fusion perception decision module, control module and execution module; The recognition module is used to obtain the distance and position data of the surface and underwater targets, distinguish different targets, and transmit the data to the data fusion perception decision module; The data fusion perception decision module is used to comprehensively analyze and fuse the data provided by the recognition module to obtain more accurate target information; according to the state and environmental conditions of the target, the decision module will formulate the optimal salvage strategy, including selecting appropriate grabbing tools and salvage paths, generating decision signals, and transmitting the decision signals to the control module; The control module receives instructions from the decision module and converts these instructions into specific control signals; The execution module is used to receive the corresponding execution signal to ensure that the mechanical gripper can rescue the person in distress.

2. The intelligent equipment for drowning prevention and emergency rescue according to claim 1, characterized in that: The recognition module uses a binocular camera on the water surface to simultaneously capture images on the water surface from slightly different angles, and determines the distance and position of the target by calculating the difference between the images.

3. The intelligent equipment for drowning prevention and emergency rescue according to claim 1, characterized in that: The recognition module emits terahertz waves under the water surface through a terahertz wave transmitter. The waves penetrate the water and interact with underwater objects. The reflected waves are captured by a receiver. By analyzing the intensity and phase of the reflected waves, a three-dimensional image of the underwater object is constructed, and the measured data is transmitted to the data fusion perception decision module.

4. The intelligent equipment for drowning prevention identification and emergency rescue according to claim 1, characterized in that: The data fusion perception decision module combines the data provided by the surface camera system and the underwater terahertz wave detection system, fuses the two different data sources through an algorithm, creates a comprehensive surface and underwater environment model, and uses machine learning and artificial intelligence technology to conduct in-depth analysis of the fused data, identify and classify target objects, and make the optimal salvage decision based on the characteristics of the target and environmental conditions, and transmit the decision to the control module.

5. The intelligent equipment for drowning prevention identification and emergency rescue according to claim 1, characterized in that: The control module is responsible for the motion planning of the robot arm and gripper, including path planning, speed control and torque regulation.

6. The intelligent equipment for drowning prevention, identification and emergency rescue according to claim 1, characterized in that: The control module receives the decision signal from the data fusion perception decision module, generates precise control signals for the robot arm and gripper, converts the signal output by the control card into instructions that the motor can understand, and receives the feedback signal from the execution module through the sensor interface.

7. The intelligent equipment for drowning prevention, identification and emergency rescue according to claim 1, characterized in that: The execution module receives precise control signals from the control module, grasps objects through the gripper, and provides status feedback of the robotic arm and the gripper.

8. The intelligent equipment for drowning prevention, identification and emergency rescue according to claim 4, characterized in that: The frequency range of terahertz corresponds to 0.1~10THz (THz=10 12 Hz).

9. A drowning prevention identification and emergency rescue method, characterized in that: The following steps are involved: S1. Obtain the distance and position data of the surface and underwater targets, and distinguish different targets; use a binocular camera on the water surface to simultaneously capture images on the water surface from slightly different angles, and determine the distance and position of the target by calculating the difference between the images; emit terahertz waves under the water surface through a terahertz wave transmitter, the waves penetrate the water body and interact with the underwater objects, and the reflected waves are captured by the receiver; construct a three-dimensional image of the underwater object by analyzing the intensity and phase of the reflected waves; S2. Comprehensively analyze and integrate the data obtained in step S1 to obtain more accurate target information; formulate the optimal salvage strategy according to the state and environmental conditions of the target; S3. Control the mechanical gripper through control signals to rescue people in distress.

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