Multifunctional detection and data management system based on intelligent sensing ball

Abstract

The invention discloses a multifunctional detection and data management system based on an intelligent sensing ball, and relates to the technical field of intelligent detection and data management. According to the multifunctional detection and data management system based on the intelligent sensing ball, the detection range is expanded by utilizing the characteristics of simple and rapid deployment, rapid response, strong expandability, reasonable structure and flexible control of the intelligent sensing ball, and the detection range is expanded under the condition that the outer ball shell is static. The motor can drive the sensing ball inner ball frame to achieve the purpose that the camera obtains graphs in all directions and detects and senses a target in all directions, the detection direction and angle can be flexibly adjusted in a dynamic environment, better monitoring data is provided for various complex application scenes, rescue efficiency is effectively improved, and the system is suitable for being popularized and used while the data transmission stability is guaranteed through an mqtt protocol. And visual display is performed according to a data acquisition result, so that the requirements of omnibearing, multi-angle and real-time monitoring and decision support are effectively met.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent detection and data management, and specifically to a multi-functional detection and data management system based on an intelligent perception ball. Background Art

[0002] With the development of the Internet of Things and intelligent detection technologies, traditional detection devices have problems such as limited coverage, fixed detection angles, and unstable data transmission. Existing detection devices usually rely on single sensors or fixed installation methods, and are generally carried on personnel wearable devices. They are rarely scattered over a large area in a certain region and networked to perform detection tasks, and cannot meet the dynamic monitoring requirements in complex environments. In addition, existing data management systems mostly adopt simple data collection and storage methods, lacking intelligent data processing and visualization functions, and it is difficult to meet the requirements of all-round, multi-angle, real-time monitoring and decision-making support.

[0003] Therefore, a multi-functional detection and data management system based on an intelligent perception ball is specifically proposed. By utilizing the characteristics of simple and rapid deployment, quick response, strong scalability, reasonable structure, and flexible control of the intelligent perception ball, the detection range is expanded. While ensuring the stability of data transmission using the MQTT protocol, it adapts to the dynamic monitoring requirements in complex environments, and performs visual display based on the data collection results, effectively meeting the requirements of all-round, multi-angle, real-time monitoring and decision-making support. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a multi-functional detection and data management system based on an intelligent perception ball, which solves the problems raised in the above background art.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A multi-functional detection and data management system based on an intelligent perception ball, including:

[0006] An equipment acquisition layer, which communicates with the cloud service layer through the MQTT protocol, and is used for acquiring sensor data and camera thermal imaging data;

[0007] A cloud service layer, which is docked with the data storage layer, and is used for receiving sensor data and camera thermal imaging data;

[0008] A data storage layer, both the data storage layer and the cloud service layer are docked with the front-end application layer, and the data storage layer is used for storing real-time sensor data and historical sensor data;

[0009] A front-end application layer, which is used for performing front-end visual display based on sensor data and camera thermal imaging data.

[0010] The present invention is further configured such that: the cloud service layer includes a location query service, an MQTT data receiving service, an MQTT video stream processing service, a thermal imaging processing service, a historical data query service, and a real-time data query service.

[0011] The present invention is further configured such that: the location query service is used to query the location information of the real-time sensor data;

[0012] The MQTT data receiving service is used to receive sensor data and store the sensor data into the data storage layer;

[0013] The MQTT video stream processing service is used to receive and process video stream data;

[0014] The thermal imaging processing service is used to receive and process thermal imaging data;

[0015] The historical data query service is used to query the historical sensor data in the data storage layer;

[0016] The real-time data query service is used to query the real-time sensor data.

[0017] The present invention is further configured such that: the front-end application layer includes a map visualization module, a real-time video stream module, a thermal imaging video module, a historical data table module, and a sensor selection module.

[0018] The present invention is further configured such that: the map visualization module is used to perform map visualization display of the location of the sensor;

[0019] The real-time video stream module is used to perform visualization display of the video stream data;

[0020] The thermal imaging video module is used to perform visualization display of the thermal imaging data;

[0021] The historical data table module is used to perform data chart display based on the historical sensor data fed back by the historical data query service;

[0022] The sensor selection module is used to select the sensor to be queried to obtain the real-time sensor data feedback of the real-time data query service regarding the sensor.

[0023] The present invention is further configured that: the device acquisition layer includes a plurality of intelligent sensing balls, each intelligent sensing ball includes an upper hemispherical transparent shell and a lower hemispherical shell, the upper hemispherical transparent shell is fixedly connected to the top of the lower hemispherical shell by bolts, a counterweight base is fixedly installed at the bottom of the lower hemispherical shell, an inner ball frame is arranged inside the lower hemispherical shell, a first motor is fixedly installed at the bottom of the inner cavity of the inner ball frame, the output end of the first motor penetrates through the inner ball frame and is fixedly connected to the bottom of the inner cavity of the lower hemispherical shell, a rotating table is also rotatably installed inside the inner ball frame, a second motor is fixedly installed at the bottom of the rotating table, the output end of the second motor is fixedly connected to the inner surface of the inner ball frame, and a camera and a sensor carrier board are fixedly installed at the top of the rotating table.

[0024] The present invention is further configured that: a perforated PCB board protection shell is also fixedly installed at the top of the rotating table, and the perforated PCB board protection shell is arranged on the outer periphery of the camera and the sensor carrier board;

[0025] A shock-absorbing material layer is filled between the inner surface of the lower hemispherical shell and the outer periphery of the inner ball frame.

[0026] The present invention is further configured that: an AI recognition module is carried in the intelligent sensing ball, and the AI recognition module is used for fire recognition, including:

[0027] Obtain video stream data, and after compressing and processing the picture quality, send the frame image of the video to the local database and the cloud service layer;

[0028] Deploy the YOLO model locally, perform unit frame processing on the video stream, take a set number of images as a unit frame, use the YOLO model to recognize the images, if an image appears, draw a square at the fire occurrence position, save the graph to a folder, and send the image to the cloud service layer.

[0029] The present invention provides a multi-functional detection and data management system based on intelligent sensing balls. It has the following

[0030] Beneficial effects:

[0031] (1) By utilizing the characteristics of simple and fast deployment, rapid response, strong scalability, reasonable structure and flexible control of the intelligent sensing ball, the present invention realizes the expansion of the detection range. When the outer spherical shell is stationary, the inner ball frame of the sensing ball can be driven by the motor to enable the camera to obtain pictures in all directions, realizing the all-round detection and perception of the target, and can flexibly adjust the detection direction and angle in a dynamic environment, providing better monitoring data for various complex application scenarios, effectively improving the rescue efficiency. While ensuring the stability of data transmission by using the mqtt protocol, it performs visual display according to the data acquisition results, effectively meeting the requirements of all-round, multi-angle, real-time monitoring and decision support.

[0032] (2) The present invention realizes convenient fire detection by deploying an AI recognition module in the intelligent sensing ball, and realizes the convenient display of detection results through visual display, effectively improving the efficiency of fire emergency response. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the system architecture of the structure of the present invention;

[0034] Figure 2 It is a logic framework diagram of intelligent fire detection of the present invention;

[0035] Figure 3 It is an overall structure diagram of the control system of the present invention;

[0036] Figure 4 It is a composition diagram of the software control system of the sensing ball in the present invention;

[0037] Figure 5 It is a flowchart of the MQTT data receiving service in the present invention;

[0038] Figure 6 It is a flowchart of the MQTT video stream processing service in the present invention;

[0039] Figure 7 It is a flowchart of the MQTT thermal imaging video stream processing service in the present invention;

[0040] Figure 8 It is a flowchart of the location data query service in the present invention;

[0041] Figure 9 It is a flowchart of the real-time data query service in the present invention;

[0042] Figure 10 It is a flowchart of the historical data query service in the present invention;

[0043] Figure 11 It is a flowchart of the front-end map visualization module in the present invention;

[0044] Figure 12 It is a flowchart of the real-time video stream module in the present invention;

[0045] Figure 13 It is a flowchart of the thermal imaging video stream module in the present invention;

[0046] Figure 14 It is a flowchart of the historical data visualization module in the present invention;

[0047] Figure 15 It is a flowchart of the sensor selection module in the present invention;

[0048] Figure 16Schematic diagram of the front - end user interface layout in the present invention;

[0049] In the figure:

[0050] 20. Sensor data display window; 21. Thermal imaging module display window; 22. GPS positioning display window; 23. Camera video stream display window;

[0051] Figure 17 Schematic diagram of the external structure of the intelligent sensing ball in the present invention;

[0052] In the figure:

[0053] 1. Intelligent sensing ball;

[0054] Figure 18 Schematic diagram of the internal structure of the intelligent sensing ball in the present invention;

[0055] 101. Upper - hemisphere transparent shell; 102. Lower - hemisphere shell; 103. Counterweight base; 104. Inner ball frame; 105. First motor; 106. Rotating table; 107. Second motor; 108. Camera and sensor carrier board; 109. Perforated PCB board protective shell;

[0056] Figure 19 Schematic diagram of the inner ball frame, the first motor, the rotating table, the second motor, the camera and sensor carrier board, and the perforated PCB board protective shell in the present invention. Detailed implementation manners

[0057] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention.

[0058] Please refer to Figure 1-19 , the embodiments of the present invention provide the following technical solutions: A multi - functional detection and data management system based on an intelligent sensing ball, including a device acquisition layer, a cloud service layer, a data storage layer, and a front - end application layer.

[0059] As a preferred solution, the device acquisition layer communicates with the cloud service layer through the MQTT protocol. The device acquisition layer is used to collect sensor data and camera thermal imaging data. The device acquisition layer includes a number of intelligent sensing balls 1. The intelligent sensing balls 1 are configured with LoRa / WiFi modules to communicate with the cloud service layer. The intelligent sensing ball 1 includes an upper hemispherical transparent shell 101 and a lower hemispherical shell 102. The upper hemispherical transparent shell 101 is fixedly connected to the top of the lower hemispherical shell 102 by bolts. The upper hemispherical transparent shell 101 is used to make it have light transmittance so that the camera can sense the surrounding environment. The lower hemispherical shell 102 is made of 3D printing material and has a certain toughness and strength. A counterweight base 103 is fixedly installed at the bottom of the lower hemispherical shell 102. In order to make the center of gravity of the lower hemisphere below when it is dropped, the counterweight base 103 is made of metal material with a large density, so that the intelligent sensing ball 1 has the characteristics of a tumbler, realizing that when the intelligent sensing ball 1 is stationary on the ground, the center of gravity at the bottom is below, and the angle between its sphere central axis and the plumb line is kept within 15 degrees, and it has a certain anti-deformation ability. An inner ball frame 104 is arranged inside the lower hemispherical shell 102. A first motor 105 is fixedly installed at the bottom of the inner cavity of the inner ball frame 104. The output end of the first motor 105 penetrates through the inner ball frame 104 and is fixedly connected to the bottom of the inner cavity of the lower hemispherical shell 102. A rotating table 106 is also rotatably installed inside the inner ball frame 104. A second motor 107 is fixedly installed at the bottom of the rotating table 106. The models of both the first motor 105 and the second motor 107 are 24BYJ-48. The output end of the second motor 107 is fixedly connected to the inner surface of the inner ball frame 104. A camera and sensor carrier plate 108 is fixedly installed at the top of the rotating table 106. The rotating table 106 can rotate by an angle of plus or minus 120 degrees, so as to realize the rotation function of the second motor 107 driving the camera and sensor carrier plate 108 to rotate around the x-axis. A perforated PCB board protective shell 109 is also fixedly installed at the top of the rotating table 106, and the perforated PCB board protective shell 109 is arranged on the outer periphery of the camera and sensor carrier plate 108. The perforated PCB board protective shell 109 has a reserved camera hole, which is convenient for nesting the camera to collect graphics of the environment, playing the role of beauty and protecting the internal electronic components. In order to make the intelligent sensing ball 1 safely dropped from a height of about 0-3 meters, a shock-absorbing material layer is filled between the inner surface of the lower hemispherical shell 102 and the outer periphery of the inner ball frame 104.

[0060] Among them, the sensors carried on the camera and sensor carrier plate 108 include but are not limited to visible light cameras, thermal imaging cameras, carbon monoxide sensors, smoke sensors, temperature sensors and humidity sensors.

[0061] Furthermore, an AI recognition module is carried in the intelligent sensing ball 1. The AI recognition module is used for fire recognition, including:

[0062] Obtain video stream data, and after compressing and processing the image quality, send the frame images of the video to the local database and the cloud service layer. Deploy the YOLO model locally to perform unit frame processing on the video stream. Set a certain number of images as a unit frame, and use the YOLO model to identify the images. If an image appears, draw a rectangle at the location where the fire appears, save the figure to a folder, and send the image to the cloud service layer. The specific process is as attached Figure 2 As shown, the system obtains the camera image through the camera, compresses the image and sends it to the cloud through mqtt for decompression and obtains each frame of the image, and pushes it to the front-end interface through the API. If the flame is detected and recognized through the yolo model, the system will trigger the image saving instruction of mqtt, obtain each frame of the image, and at the same time push it to the interface through the API and save the recognized flame image frame to the folder and send it to the relevant personnel.

[0063] As a preferred solution, the cloud service layer is docked with the data storage layer. The cloud service layer is used to receive sensor data and camera thermal imaging data. The cloud service layer includes a location query service, an mqtt data receiving service, an mqtt video stream processing service, a thermal imaging processing service, a historical data query service, and a real-time data query service. Among them, the location query service is used to query the location information of the real-time sensor data;

[0064] The mqtt data receiving service is used to receive sensor data and store the sensor data in the data storage layer;

[0065] The mqtt video stream processing service is used to receive and process video stream data;

[0066] The thermal imaging processing service is used to receive and process thermal imaging data;

[0067] The historical data query service is used to query the historical sensor data in the data storage layer;

[0068] The real-time data query service is used to query real-time sensor data.

[0069] As a preferred solution, both the data storage layer and the cloud service layer are docked with the front-end application layer. The data storage layer is used to store real-time sensor data and historical sensor data.

[0070] As a preferred solution, the front-end application layer is used to perform front-end visualization display according to sensor data and camera thermal imaging data. The front-end application layer includes a map visualization module, a real-time video stream module, a thermal imaging video module, a historical data table module, and a sensor selection module. The map visualization module is used to perform map visualization display of the location of the sensor;

[0071] The real-time video stream module is used to perform visualization display of video stream data;

[0072] The thermal imaging video module is used for visual display of thermal imaging data;

[0073] The historical data table module is used for data chart display according to the historical sensor data fed back by the historical data query service;

[0074] The sensor selection module is used to select the sensor to be queried to obtain the real-time sensor data feedback of the real-time data query service for this sensor.

[0075] As shown in the Figure 3 appendix, the control system is mainly divided into four major parts: the device data acquisition layer, the cloud service layer, the front-end application layer, and the data storage layer. The operation process of this system ensures the efficient operation from device data acquisition, real-time processing to data storage and display. It realizes the efficient data transmission between the device and the middle layer and the cloud through the MQTT protocol, and stores and queries through the database. Finally, it provides clear real-time monitoring and analysis tools for rescue personnel through the front-end map and charts. The specific operation process of the system is as follows:

[0076] A1. Device data acquisition and processing; The intelligent perception ball collects real-time data by carrying integrated sensors such as temperature sensors, humidity sensors, and smoke sensors. The intelligent perception ball pushes the sensor data to the backend system through the MQTT protocol. The backend system subscribes to the ball / data topic and receives the sensor data. These data are parsed and stored in the database for subsequent query and analysis. At the same time, the backend system sends an acknowledgment response to the intelligent perception ball through the ball / response topic to ensure the successful reception of the data. In addition to the conventional sensor data, the intelligent perception ball is also equipped with a visible light camera to collect video streams and a thermal imaging camera to collect thermal imaging video streams. The system subscribes to the video stream and thermal imaging video stream data through an independent MQTT service to ensure that rescue personnel can obtain the on-site video in real time and identify targets in complex environments;

[0077] A2. Data storage and query: All the collected sensor data are stored in the SQL Server database, which is divided into a real-time data table sensorData and a historical data table sensorHistoryData. The database design supports efficient data storage and retrieval. The system provides three data query services:

[0078] A21. Location data query service: By querying the geographical location information in the database, the system can obtain the real-time location information of the intelligent perception ball and return it in JSON format for use by the map visualization module;

[0079] A22. Real-time Sensor Data Query Service: The front-end application layer can query the latest data of various sensors, such as temperature and humidity, smoke, etc., to help rescue personnel understand the current on-site environment;

[0080] A23. Historical Data Query Service: Users can query the historical sensor data within a specified time period. The system will return the data grouped by time, support multi-dimensional display and chart drawing to help users analyze historical trends;

[0081] A3. Real-time Monitoring and Visualization: The front-end application layer implements real-time monitoring and data display based on the React framework. By integrating the Leaflet library, the map visualization module displays the real-time location information of the intelligent perception balls. Every 10 minutes, the front-end application layer obtains the data pushed by MQTT through WebSocket for update, and supports users to click on the map markers to view device details or trigger real-time video streams;

[0082] The real-time video stream module and the thermal imaging video stream module respectively provide real-time video and thermal imaging data for the front-end application layer to display. The video frame data obtained through the API ensures the continuity of the video stream and real-time update, helping rescue personnel remotely monitor the on-site situation, conduct temperature anomaly monitoring and target recognition;

[0083] The historical data visualization module uses the Chart.js library to display the historical data of sensors in the form of charts. Users can switch different sensor data sources according to their needs and set threshold alarms to monitor the changes of sensor data in real time;

[0084] A4. Device Management and Sensor Selection System provides device management and sensor selection functions. The front-end allows users to select different intelligent perception balls through a drop-down menu. After each selection, the front-end interface will dynamically switch to display the data of the relevant devices, ensuring that rescue personnel can flexibly manage multiple devices and monitor the device status and data in real time.

[0085] As shown in Figure 4 the software control system composition diagram of the intelligent perception ball. The software control system consists of three major modules: data acquisition and processing, data query and analysis, and real-time monitoring and visualization, aiming to achieve efficient data transmission and processing through MQTT communication.

[0086] In the data acquisition and processing module, the MQTT data reception service subscribes to sensor data and stores it in the database, while triggering the video stream and thermal imaging processing services to ensure real-time data transmission and storage. The data query and analysis module is responsible for providing the location information of the rescue ball, real-time sensor data, and historical data query, supporting the front-end to visually display data for different time periods. The real-time monitoring and visualization module enables rescue personnel to view the geographical location of the rescue ball, monitor video footage, and query relevant data in real time through the front-end map, video stream, and sensor selection functions, ensuring the comprehensiveness and operability of information.

[0087] The system uses the MQTT protocol for data interaction and combines front-end visualization technologies such as React, Leaflet, and Chart.js to achieve an efficient and intuitive user experience, thereby enhancing the intelligent level and response efficiency of rescue work.

[0088] As shown in the Figure 5 MQTT data reception service flow chart, by subscribing to the ball / data topic, receiving and parsing sensor data, storing it in the database, and sending a response through the ball / response topic.

[0089] As shown in the Figure 6 MQTT video stream processing service flow chart, subscribing to video stream data and providing real-time video frame data to the front-end.

[0090] As shown in the Figure 7 MQTT thermal imaging video stream processing service flow chart, processing thermal imaging video data to ensure target recognition and monitoring in complex environments.

[0091] As shown in the Figure 8 Location data query service flow chart, obtaining the geographical location information of the rescue ball based on database query and returning data in JSON format to support front-end map visualization.

[0092] As shown in the Figure 9 Real-time data query service flow chart, providing the front-end with real-time query of the latest data of specific sensors, supporting multiple sensor types for the front-end to draw real-time data display.

[0093] As shown in the Figure 10 Historical data query service flow chart, supporting the query of sensor data within a specified time period and returning information such as Humidity, Temperature, Smokescope, etc. grouped by time for the front-end to draw historical curves.

[0094] As shown in the Figure 11The flow chart of the front-end map visualization module shown uses React + Leaflet to dynamically render the location information of the rescue balls, supports MQTT message push via WebSocket, automatically refreshes the data every 10 minutes, and enables users to click on the markers to view detailed information or trigger the video stream.

[0095] As shown in the appendix Figure 12 The flow chart of the real-time video stream module shown provides an API to obtain the latest video frames and ensures the continuity of the video stream through setInterval, supporting remote monitoring by rescue personnel.

[0096] As shown in the appendix Figure 13 The flow chart of the thermal imaging video stream module shown obtains the latest thermal imaging video frames through the API and dynamically updates the front-end display, facilitating high-temperature environment monitoring and target recognition.

[0097] As shown in the appendix Figure 14 The flow chart of the historical data visualization module shown uses Chart.js to achieve multi-dimensional visualization of historical data, supporting dynamic data source switching and threshold alarms.

[0098] As shown in the appendix Figure 15 The flow chart of the sensor selection module shown; a drop-down menu is provided on the front end to support the selection of different rescue ball devices and real-time switching of the displayed data, ensuring that rescue personnel can flexibly monitor multiple devices.

[0099] As shown in the appendix Figure 16 The layout diagram of the front-end user interface shown is mainly divided into 5 major areas, namely sensor data, video stream display window, infrared thermal imaging module, gps positioning module, and perception ball selection module. By selecting different perception balls, the user interface can display the real-time sensor data and historical sensor data of this perception ball, as well as the collected video images, infrared thermal imaging images, and gps positioning screen displays in real time.

[0100] Those of ordinary skill in the art can realize that the units of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the components of each example have been generally described according to their functions in the above description. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0101] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0102] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0103] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, read-only memories (ROMs), random access memories (RAMs), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0104] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of various embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A multi-functional detection and data management system based on an intelligent sensing sphere, characterized in that: Including: Device acquisition layer, which communicates with the cloud service layer through the MQTT protocol and is used to collect sensor data and camera thermal imaging data; Cloud service layer, which is docked with the data storage layer and is used to receive sensor data and camera thermal imaging data; Data storage layer, both the data storage layer and the cloud service layer are docked with the front-end application layer, and the data storage layer is used to store real-time sensor data and historical sensor data; Front-end application layer, which is used to perform front-end visual display based on sensor data and camera thermal imaging data.

2. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 1, wherein: The cloud service layer includes a location query service, an MQTT data reception service, an MQTT video stream processing service, a thermal imaging processing service, a historical data query service, and a real-time data query service.

3. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 2, characterized in that: The location query service is used to query the location information of real-time sensor data; The MQTT data reception service is used to receive sensor data and store the sensor data into the data storage layer; The MQTT video stream processing service is used to receive and process video stream data; The thermal imaging processing service is used to receive and process thermal imaging data; The historical data query service is used to query historical sensor data in the data storage layer; The real-time data query service is used to query real-time sensor data.

4. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 3, wherein: The front-end application layer includes a map visualization module, a real-time video stream module, a thermal imaging video module, a historical data table module, and a sensor selection module.

5. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 4, characterized in that: The map visualization module is used to perform map visualization display of the location of the sensor; The real-time video stream module is used to perform visual display of video stream data; The thermal imaging video module is used to perform visual display of thermal imaging data; The historical data table module is used to perform data chart display based on the historical sensor data fed back by the historical data query service; The sensor selection module is used to select the sensor to be queried to obtain the real-time sensor data feedback of the real-time data query service for this sensor.

6. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 1, wherein: The device acquisition layer includes a number of intelligent perception balls. The intelligent perception ball includes an upper hemispherical transparent shell and a lower hemispherical shell. The upper hemispherical transparent shell is fixedly connected to the top of the lower hemispherical shell by bolts. A counterweight base is fixedly installed at the bottom of the lower hemispherical shell. An inner ball frame is arranged inside the lower hemispherical shell. A first motor is fixedly installed at the bottom of the inner cavity of the inner ball frame. The output end of the first motor penetrates through the inner ball frame and is fixedly connected to the bottom of the inner cavity of the lower hemispherical shell. A rotating table is also rotatably installed inside the inner ball frame. A second motor is fixedly installed at the bottom of the rotating table. The output end of the second motor is fixedly connected to the inner surface of the inner ball frame. A camera and a sensor carrier board are fixedly installed at the top of the rotating table.

7. The multi-functional detection and data management system based on an intelligent perception ball according to claim 6, characterized in that: A perforated PCB board protection shell is also fixedly installed at the top of the rotating table, and the perforated PCB board protection shell is arranged on the outer periphery of the camera and the sensor carrier board; A shock-absorbing material layer is filled between the inner surface of the lower hemispherical shell and the outer periphery of the inner ball frame.

8. The multi-functional detection and data management system based on an intelligent sensing sphere according to claim 7, characterized in that: An AI recognition module is installed in the intelligent perception ball. The AI recognition module is used for fire recognition and includes: Obtain video stream data, and after compressing and processing the picture quality, send the frame images of the video to the local database and the cloud service layer; Deploy the YOLO model locally, perform unit frame processing on the video stream, set a certain number of images as a unit frame, use the YOLO model to recognize the images. If an image appears, draw a square at the location where the fire appears, save the graph to a folder, and send the image to the cloud service layer.

Images