Beidou AI edge computing gateway for emergency monitoring

Abstract

The invention relates to a Beidou AI edge computing gateway for emergency monitoring. The Beidou AI edge computing gateway comprises a universal sensor signal processing unit, a Beidou positioning unit, a visual signal processing unit, a CPU processing unit and an AI core processing unit, the CPU processing unit processes received first data output by the universal sensor signal processing unit and second data output by the Beidou positioning unit and then inputs the processed data to the AI core processing unit, and the visual signal processing unit outputs third data to the AI core processing unit; an AI model in the AI core processing unit performs AI operation on the first data, the second data and the third data so as to form real-time data information, accurate future trend forecast data information is generated, and whether an early warning is sent out or not is judged. According to the invention, corresponding algorithm models can be deployed according to different requirements, so that not only can the monitoring of slope landslide or collapse be carried out, but also the prediction of different types of abnormal conditions such as meteorology, fire, traffic, smart city management and the like can be carried out.

Description

Technical Field

[0001] The present invention relates to the field of emergency monitoring, and in particular to a Beidou AI edge computing gateway for emergency monitoring. Background Art

[0002] In the field of emergency monitoring, Beidou receiver terminals and Beidou short message communication terminals are currently widely used, and relevant data are transmitted to the back-end platform for centralized calculation and processing; however, the relevant terminals have significant deficiencies in operability and convenience of comprehensive data calculation and processing. The back-end platform uniformly processes massive data, resulting in excessive resource pressure on the back-end platform, reduced emergency response efficiency, and inability to quickly respond to the needs of dynamic changes in various environments. At the same time, there is a delay in data transmission between the terminal and the back-end platform, which further reduces the data processing efficiency. Therefore, how to solve this problem is currently a matter that needs to be considered. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a Beidou AI edge computing gateway for emergency monitoring, which solves the deficiencies of the prior art.

[0004] The object of the present invention is achieved by the following technical solutions: a Beidou AI edge computing gateway for emergency monitoring, the gateway is deployed outdoors, and includes a general sensor signal processing unit, a Beidou positioning unit, a visual signal processing unit, a CPU processing unit and an AI core processing unit; The universal sensor signal processing unit outputs the first data to the CPU processing unit, the Beidou positioning unit outputs the second data to the CPU processing unit, the CPU processing unit processes the received first data and second data and inputs them to the AI ​​core processing unit, and the visual signal processing unit outputs the third data to the AI ​​core processing unit; A variety of AI models are deployed in the AI ​​core processing unit. According to the types of the first data and the third data, corresponding AI models are selected to perform AI operations on the first data, the second data and the third data to form real-time and standardized data information. By mining the historical data of the three types of data and sequentially extracting data patterns, accurate future trend forecast data information is generated, and whether to issue an early warning is determined based on the future trend forecast data information.

[0005] The first data includes various types of data received from various sensors, and the data is pre-processed by cleaning, filtering and denoising through a universal sensor signal processing unit to remove interference factors that affect data quality and obtain data information that is easy to understand and analyze.

[0006] The second data includes receiving signals from the Beidou satellite system, filtering and amplifying the received information through the Beidou positioning unit to eliminate interference and enhance signal quality, decoding and parsing the signals through a built-in algorithm, extracting the navigation message therein, and calculating the pseudorange and Doppler frequency shift parameters between the satellite and the receiving device in combination with its own clock and stored ephemeris data, and using these parameters and the satellite's orbital parameters to calculate the three-dimensional coordinates and time information of the receiving device.

[0007] The third data includes the video stream image data received from the shooting device. The visual signal processing unit performs anti-shake processing on the received video stream image to eliminate image blur and instability caused by jitter or other factors, and adjusts the light intensity to ensure that clear and bright images can be obtained under different lighting conditions, and finally outputs video stream data that meets the standards.

[0008] The CPU processing unit parses the signal output by the general sensor signal processing unit to extract the target information, and verifies the positioning data output by the Beidou positioning unit. According to the preset data conversion rules, the parsed signal and the verified positioning data are encoded in a specific standard format and input into the AI ​​core processing unit.

[0009] The determining whether to issue an early warning according to the future trend forecast data information includes: if the future trend forecast data information triggers the set early warning condition, issuing an early warning, otherwise remaining silent until the future trend forecast data information updated in real time triggers the set early warning condition.

[0010] The gateway also includes a data storage unit, a data transmission unit and a Beidou short message communication unit; the data storage unit is used to store various types of data output by the AI ​​core processing unit; the data transmission unit transmits the data to the local user, and also transmits the data to the back-end cloud server through various communication methods for further processing and analysis; the Beidou short message communication unit is connected to the CPU processing unit to provide a communication method independent of the ground network. When the data transmission unit is restricted in transmission, the data is sent to the local user in the form of a Beidou short message, and is transmitted to the back-end cloud server for further processing and analysis, and at the same time receives data sent by the local user and the cloud server.

[0011] The present invention has the following advantages: a Beidou AI edge computing gateway for emergency monitoring, since the AI ​​algorithms and models deployed on the AI ​​edge computing gateway device can be flexibly combined and replaced, the corresponding algorithm models can be deployed according to different needs; in this way, not only can slope landslides or collapses be monitored, but also different types of abnormal situation predictions such as meteorology, fire, transportation, smart city management, etc. can be performed. This diversified prediction capability enables the AI ​​edge computing gateway device to meet various types of emergency management needs, thereby providing more comprehensive and powerful technical support for social security and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of the present application provided below in conjunction with the drawings is not intended to limit the scope of protection of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application. The present invention is further described below in conjunction with the drawings.

[0014] like Figure 1 As shown, the present invention specifically relates to a Beidou AI edge computing gateway for emergency monitoring, which includes a general sensor signal processing unit, a Beidou positioning unit, a visual signal processing unit, a CPU processing unit, an AI core processing unit (NPU processing unit), a data storage unit, a data transmission unit and a Beidou short message communication unit.

[0015] Furthermore, the universal sensor signal processing unit includes a radar signal processing unit for receiving a signal sent by a certain radar; it is used to receive and process the raw data collected by the slope displacement monitoring radar, and ensure the accuracy and reliability of the data through a series of preprocessing steps. These preprocessing steps include data cleaning, filtering, denoising, etc., to remove interference factors that may affect the data quality. After processing, these data are converted into spatial data information that is easy to understand and analyze for further analysis and application. These spatial data information can be used to assess the stability of the slope, predict potential landslide risks, and provide important support for related geological disaster early warning systems. After the preprocessing stage, the output spatial data information will be imported into a professional geographic information system (GIS) or related data analysis software for more in-depth mining and analysis. These systems can use advanced algorithms and models to analyze spatial data in multiple dimensions and scales, revealing the complex laws and potential risk factors of slope displacement.

[0016] For example, by conducting time series analysis on spatial data information, we can identify the changing trend and rate of slope displacement, and then judge the stability of the slope. At the same time, by combining geological, meteorological, hydrological and other multi-source data, we can build a more accurate slope stability assessment model, providing a scientific basis for landslide warning and disaster prevention.

[0017] In addition, spatial data information can also be used to generate three-dimensional visualization models of slopes, which can help researchers and decision makers understand the morphological and structural characteristics of slopes more clearly through intuitive graphical displays. These models not only help to deeply understand the deformation mechanism of slopes, but also provide important references for the design and construction of slope management projects. Therefore, receiving and processing the raw data of slope displacement monitoring radar, through preprocessing and in-depth analysis, the output spatial data information has a wide range of application value in slope stability assessment, landslide warning and geological disaster prevention and control.

[0018] Furthermore, the signal received by the universal sensor processing unit may also be a temperature signal sent by a temperature sensor for fire warning, or a hydrological signal for water level warning, and so on.

[0019] Beidou Positioning Unit: By receiving signals from the Beidou satellite system and processing them using the Beidou positioning unit in the edge computing gateway, we can obtain accurate spatial location information. This process involves decoding and calculating the received satellite signals to determine the specific location of the device on the earth. As a key device, the edge computing gateway can process these signals in real time and convert the processed data into usable spatial location information. This technology has a wide range of applications in navigation, geographic information systems, intelligent transportation and many other fields. Specifically, the signals transmitted by the Beidou satellite system contain rich navigation and positioning information, which are transmitted to the ground through electromagnetic waves and received by the antenna and receiver in the edge computing gateway. The Beidou positioning unit starts working and performs a series of complex processing on the signals. The Beidou positioning unit filters and amplifies the received signals to eliminate interference and enhance signal quality. Subsequently, the signals are decoded and parsed using built-in algorithms and models to extract the navigation messages. These navigation messages contain key data such as the satellite's orbital parameters and time information, which are the basis for calculating spatial position.

[0020] After obtaining the navigation message, the Beidou positioning unit will perform a series of mathematical operations in combination with its own clock and stored ephemeris data. These operations include calculating the pseudorange, Doppler shift and other parameters between the satellite and the receiving device, and using these parameters and the orbital parameters of the satellite to solve the three-dimensional coordinates and time information of the receiving device through specific algorithms (such as least squares method, etc.). Finally, the spatial position information processed by the Beidou positioning unit in the edge computing gateway will be output to the user in the form of numbers or graphics. This information can be used in a variety of application scenarios such as navigation, positioning, and tracking, bringing convenience to people's daily life and work.

[0021] Visual signal processing unit (ISP image signal processor): The main task is to receive video stream image data from the camera. To ensure image quality, the ISP first performs anti-shake processing on these video stream images to eliminate image blur and instability caused by camera shaking or other factors. Then, it adjusts the light intensity to ensure clear and bright images under different lighting conditions. After these processing steps, the ISP outputs standard-compliant video stream data for subsequent processing and analysis. In this way, the Beidou edge computing gateway can provide high-quality video stream images and provide reliable support for various application scenarios. As video stream data carefully processed by the ISP, it not only improves the clarity and stability of the image, but also optimizes the data format to adapt to different application requirements. These data are then quickly and accurately transmitted to where they are needed through the efficient data transmission system inside the Beidou edge computing gateway.

[0022] CPU processing unit: Receives output signals from the radar signal processing unit and the Beidou positioning unit, and passes these signals to the neural network processing unit (NPU) in strict accordance with the established standard format. During the receiving process, the signal output by the radar signal processing unit is first parsed to extract key information such as the target's position, speed, and direction to ensure the accuracy and completeness of this information. At the same time, the positioning data provided by the Beidou positioning unit is verified to confirm its accuracy and timeliness to meet the needs of subsequent processing.

[0023] Next, according to the preset data conversion rules, the parsed radar signal and the verified Beidou positioning data are encoded in a specific standard format. This step is crucial because it ensures the consistency and readability of the data, facilitating efficient and accurate processing by the NPU; after the encoding is completed, the formatted data is sent to the NPU through an efficient and stable data transmission channel. During the transmission process, necessary measures will also be taken to protect the integrity and security of the data to prevent data tampering or leakage during transmission.

[0024] After receiving this data, the NPU will use its powerful computing power to further analyze and process it. It can deeply integrate and intelligently analyze radar signals and positioning data based on pre-trained models and algorithms, thereby achieving accurate identification and tracking of targets. This process not only improves the automation and intelligence level of the system, but also greatly enhances the real-time and accuracy of the system.

[0025] Ultimately, the results processed by the NPU will be output to users or subsequent processing systems in a more intuitive and easy-to-understand form. In this way, users can make more accurate and timely decisions and judgments based on these results to meet the needs of various application scenarios.

[0026] AI core processing unit (NPU processing unit): This unit is configured to run various neural networks, which perform AI operations on the data output by the radar processing unit, Beidou positioning unit and visual signal processing unit to form real-time and standardized spatial data information; at the same time, it conducts in-depth mining and training on massive historical data, including radar data, Beidou positioning data and visual signal data. By analyzing these data, NPU can extract the rules and use these rules to quickly generate accurate future trend forecast data information.

[0027] In the construction of smart cities, NPU can process data from all corners of the city in real time, including traffic flow, environmental monitoring, public safety, etc., and generate accurate spatial data information through AI calculations to help city managers make scientific decisions. At the same time, NPU can also conduct in-depth mining of massive historical data in the city, such as changes in traffic flow over the years and climate data, to discover the laws behind the data and provide strong data support for urban planning.

[0028] In the field of autonomous driving, NPU can process data from vehicle sensors (such as radar, cameras, etc.) in real time, and combine Beidou positioning data to accurately perceive the vehicle's surrounding environment. Through deep learning algorithms, NPU can identify pedestrians, vehicles, road signs, etc., and provide decision-making basis for the autonomous driving system. At the same time, through the mining and training of massive historical driving data, NPU can continuously optimize its own prediction capabilities and improve the safety and stability of the autonomous driving system.

[0029] Data storage unit: used for local storage of various types of data output by the AI ​​core processing unit, so as to be used as valuable data resources for future edge computing.

[0030] Data transmission unit: Data is transmitted to local users through various communication methods, such as 4G, Lora, etc., so that they can understand the on-site situation in a timely manner and effectively manage and respond to relevant emergencies. At the same time, data is also transmitted to the back-end cloud server through various communication methods for further processing and analysis. In the process of data transmission, in order to ensure the security and integrity of the data, advanced encryption technology is used to encrypt the data to prevent the data from being illegally intercepted or tampered with during the transmission process. At the same time, a data verification mechanism is also set up to ensure that the received data is completely consistent with the original data, thereby avoiding decision-making errors caused by data errors.

[0031] Beidou short message communication unit: connected to the CPU processing unit, providing a communication method independent of the ground network. When the data transmission unit is limited in transmission, the data is sent to the local user in the form of Beidou short messages, and transmitted to the back-end cloud server for further processing and analysis. At the same time, it receives data sent by local users and cloud servers.

[0032] As the central management platform of the entire system, the backend cloud server is responsible for receiving and processing various spatial location information, alarm and warning information from each edge node. After the information is transmitted to the central management platform, the platform will conduct detailed analysis and processing to ensure that each information can receive a timely and accurate response. In this way, the central management platform can effectively monitor and manage the operating status of the entire system to ensure the stability and security of the system.

[0033] The AI ​​core processing unit, data transmission unit, back-end cloud platform and local user interface of the present invention construct an efficient and scalable data processing system that can quickly receive, process and store data from the AI ​​core and local users. These data will be used for further analysis and mining to extract valuable information and provide strong support for the decision-making of enterprises. In addition, in order to improve the utilization efficiency of data, an intelligent recommendation system is also introduced. The system can intelligently recommend relevant data and information based on the user's historical behavior and current needs, helping users find the required content faster and improve work efficiency.

[0034] For local users, an intuitive and easy-to-use data display interface is provided, allowing users to easily view and manage field data. At the same time, a variety of data analysis tools are also provided to help users gain a deeper understanding of the connotation and rules of the data, providing a scientific basis for field management and decision-making.

[0035] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used for various other combinations, modifications and improvements, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art do not deviate from the spirit and scope of the present invention, and should be within the scope of protection of the claims attached to the present invention.

Claims

1. A Beidou AI edge computing gateway for emergency monitoring, characterized by: The gateway is deployed outdoors and includes a general sensor signal processing unit, a Beidou positioning unit, a visual signal processing unit, a CPU processing unit and an AI core processing unit; The universal sensor signal processing unit outputs the first data to the CPU processing unit, the Beidou positioning unit outputs the second data to the CPU processing unit, the CPU processing unit processes the received first data and second data and inputs them to the AI ​​core processing unit, and the visual signal processing unit outputs the third data to the AI ​​core processing unit; A variety of AI models are deployed in the AI ​​core processing unit. The corresponding AI model is selected according to the types of the first data and the third data. AI operations are performed on the first data, the second data and the third data to form real-time and standardized data information. By mining the historical data of the three types of data and sequentially extracting data patterns, accurate future trend forecast data information is generated, and whether to issue an early warning is determined based on the future trend forecast data information.

2. A Beidou AI edge computing gateway for emergency monitoring according to claim 1, characterized in that: The first data includes various types of data received from various sensors, and the data is pre-processed by cleaning, filtering and denoising through a universal sensor signal processing unit to remove interference factors that affect data quality and obtain data information that is easy to understand and analyze.

3. A Beidou AI edge computing gateway for emergency monitoring according to claim 1, characterized in that: The second data includes receiving signals from the Beidou satellite system, filtering and amplifying the received information through the Beidou positioning unit to eliminate interference and enhance signal quality, decoding and parsing the signals through a built-in algorithm, extracting the navigation message therein, and calculating the pseudorange and Doppler frequency shift parameters between the satellite and the receiving device in combination with its own clock and stored ephemeris data, and using these parameters and the satellite's orbital parameters to calculate the three-dimensional coordinates and time information of the receiving device.

4. A Beidou AI edge computing gateway for emergency monitoring according to claim 1, characterized in that: The third data includes the video stream image data received from the shooting device. The visual signal processing unit performs anti-shake processing on the received video stream image to eliminate image blur and instability caused by jitter or other factors, and adjusts the light intensity to ensure that clear and bright images can be obtained under different lighting conditions, and finally outputs video stream data that meets the standards.

5. The Beidou AI edge computing gateway for emergency monitoring according to claim 1, characterized in that: The CPU processing unit parses the signal output by the general sensor signal processing unit to extract the target information, and verifies the positioning data output by the Beidou positioning unit. According to the preset data conversion rules, the parsed signal and the verified positioning data are encoded in a specific standard format and input into the AI ​​core processing unit.

6. The Beidou AI edge computing gateway for emergency monitoring according to claim 1, characterized in that: The determining whether to issue an early warning according to the future trend forecast data information includes: if the future trend forecast data information triggers the set early warning condition, issuing an early warning, otherwise remaining silent until the future trend forecast data information updated in real time triggers the set early warning condition.

7. A Beidou AI edge computing gateway for emergency monitoring according to any one of claims 1 to 6, characterized in that: The gateway also includes a data storage unit, a data transmission unit and a Beidou short message communication unit; the data storage unit is used to store various types of data output by the AI ​​core processing unit; the data transmission unit transmits the data to the local user, and also transmits the data to the back-end cloud server through various communication methods for further processing and analysis; the Beidou short message communication unit is connected to the CPU processing unit to provide a communication method independent of the ground network. When the data transmission unit is restricted in transmission, the data is sent to the local user in the form of a Beidou short message, and is transmitted to the back-end cloud server for further processing and analysis, and at the same time receives data sent by the local user and the cloud server.

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