Computing device based on multi-sensor data acquisition

Abstract

The invention discloses a computing device based on multi-sensor data acquisition, which relates to the field of embedded technology and comprises a hardware module, a virtualization module, a protocol processing module and a data output module. The hardware module is provided with interfaces such as CAN and UART, and supports multi-protocol sensor access; the virtualization module generates an independent container by using a Docker technology, so that resource isolation is realized, and stable data processing is guaranteed; the protocol processing module analyzes the data and extracts characteristic values; and the data output module converts the data into a standardized JSON format by a user-defined protocol, and supports receipt and retransmission. The device adopts a low-power-consumption ARM processor, supports container dynamic operation, realizes protocol plug-and-play expansion, solves the problems of high cost, complex deployment and the like of a traditional device, and is suitable for lightweight scenes such as industrial Internet of Things, edge computing and the like.

Description

Technical Field

[0001] The present invention relates to the field of embedded technology, and particularly relates to a computing device based on multi-sensor data acquisition. Background Art

[0002] In the fields of industrial Internet of Things, intelligent monitoring systems, and edge computing, large signal acquisition systems need to connect to diverse sensor devices, such as water level gauges, flow meters, pressure sensors, temperature sensors, and electrical parameter monitoring devices. These devices usually adopt different communication protocols, resulting in significant differences in data formats and interaction rules. To achieve unified management and efficient processing of data, traditional solutions rely on multi-source heterogeneous protocol conversion devices with built-in protocol conversion modules. However, traditional devices have significant defects, such as high cost, complex deployment and update, insufficient lightweight, and poor environmental compatibility. Therefore, it is particularly important to invent a computing device based on multi-sensor data acquisition.

[0003] The prior art has the following defects, specifically reflected in: 1. In the prior art, the data processing logics of different sensors share the same operating environment, which is prone to program anomalies or system crashes due to software dependency conflicts, resulting in poor data processing stability. When adding new sensor types or communication protocols, it is necessary to globally adjust the underlying software environment, such as updating system dependencies, recompiling code, and even involving hardware interface transformation. The system upgrade cycle is long and the technical threshold is high, making it difficult to adapt to rapidly changing application requirements.

[0004] 2. In the prior art, although it can convert data formats, it relies on hard-coded methods to process different protocols such as Modbus-TCP and CANOpen, and does not form a standardized unified format, resulting in the need for the backend system to develop exclusive parsing modules for each protocol. The processing logic is complex and the efficiency is low. For each newly added protocol or sensor type, it is necessary to independently design a protocol parsing module and integrate it into the system. The repeated development of hardware interfaces and software codes leads to an increase in R & D costs, extremely high adaptation costs, and great maintenance difficulties. Summary of the Invention

[0005] The purpose of the present invention is to provide a computing device based on multi-sensor data acquisition, which solves the problems existing in the background art.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a computing device based on multi-sensor data acquisition, including: a hardware module, which is provided with a variety of peripheral interfaces for connecting sensor devices with different communication protocols, and the peripheral interfaces include CAN, UART, I2C, SPI, and network interfaces.

[0007] A virtualization module, which is used to generate independent containers based on Docker technology to provide an isolated processing environment for different types of sensor data.

[0008] A protocol processing module is used to deploy corresponding communication interfaces inside each of the Docker containers, and receive and parse the raw data uploaded by the sensors.

[0009] A data output module is used to formulate a custom communication protocol, convert the parsed sensor data into text data in a unified format, and output it.

[0010] Preferably, the peripheral interface supports communication protocols such as Modbus-TCP, CANOpen, DeviceNet, and IEC61850, and is compatible with the access of water level gauges, flow meters, pressure sensors, and temperature sensors.

[0011] Preferably, the hardware module uses a low-power ARM architecture processor, is configured with high-speed flash memory and dynamic memory, and supports the lightweight deployment and operation of the Docker containers.

[0012] Preferably, the Docker containers implement isolation of the operating environments for different sensor data processing logics through a resource isolation mechanism, and the resource isolation includes independent allocation of CPU resources, memory space, and file systems.

[0013] Preferably, the Docker containers support dynamic creation and deletion. When a new sensor type or communication protocol is added, new containers are generated by deploying the corresponding protocol parsing images, realizing plug-and-play protocol expansion.

[0014] Preferably, when parsing the raw data, the protocol processing layer extracts characteristic values such as the sensor device ID, alarm status, alarm time, and alarm number, and encapsulates them into output data in a unified format according to the custom communication protocol.

[0015] Preferably, the data output module converts the sensor data into a standardized JSON text format including device identification, channel number, data value, and timestamp, and the JSON text format is used for unified parsing and processing by the backend system.

[0016] Preferably, the data output module supports a data receipt mechanism. When the client fails to receive data, it triggers the container retransmission logic, and the retransmission logic includes a maximum retransmission times limit.

[0017] Preferably, the custom communication protocol includes at least the following fields: company number, transmission characteristic value, timestamp, receipt flag, current transmission times, maximum transmission times, and additional information, and the fields are used to identify the data source, transmission direction, time attribute, and interaction status.

[0018] The beneficial effects of the present invention are as follows: 1. In the present invention, the virtualized Docker technology is applied, which provides an isolated and dedicated processing environment for different types of signals, avoids environmental conflicts, ensures the stability and accuracy of different data processing, improves the reliability of data processing. When deploying a new type of signal processing task, only a new container needs to be created and the corresponding communication interfaces and protocols need to be deployed, without large-scale modification of the entire system, which improves the scalability and flexibility of the system.

[0019] 2. In the present invention, by customizing the communication protocol, the sensor data of different transmission protocols such as Modbus-TCP and CANOpen are converted into a unified text format, such as JSON, eliminating data format differences, simplifying the backend processing logic, improving the efficiency of data processing, reducing the processing cost and time consumption caused by inconsistent data formats, and laying a solid foundation for subsequent data analysis work. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 It is a schematic diagram of the system structure connection of the present invention.

[0022] Figure 2 It is a schematic diagram of the implementation steps flow of the method of the present invention.

[0023] Figure 3 It is a schematic diagram of the custom communication protocol of the present invention DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0025] Refer to Figure 1 、 2 As shown, the present invention provides a computing device based on multi-sensor data acquisition, including: a hardware module, which is provided with a variety of peripheral interfaces for connecting sensor devices of different communication protocols, and the peripheral interfaces include CAN, UART, I2C, SPI, and network ports.

[0026] In a specific embodiment, the peripheral interface supports Modbus-TCP, CANOpen, DeviceNet, and IEC61850 communication protocols and is compatible with the access of water level gauges, flow meters, pressure sensors, and temperature sensors.

[0027] In a specific embodiment, the hardware module adopts a low-power ARM architecture processor, configures high-speed flash memory and dynamic memory, and supports the lightweight deployment and operation of the Docker containers.

[0028] The virtualization module is used to generate independent containers based on Docker technology and provide an isolated processing environment for different types of sensor data.

[0029] In the present invention, the virtualization Docker technology is applied to provide an isolated and dedicated processing environment for different types of signals, avoiding environmental conflicts, ensuring the stability and accuracy of different data processing, improving the reliability of data processing. When deploying a new type of signal processing task, only need to create a new container and deploy the corresponding communication interface and protocol, without large-scale modification of the entire system, enhancing the scalability and flexibility of the system.

[0030] In a specific embodiment, the Docker containers achieve isolation of the operating environments for different sensor data processing logics through a resource isolation mechanism, and the resource isolation includes independent allocation of CPU resources, memory space, and file system.

[0031] In a specific embodiment, the Docker containers support dynamic creation and deletion. When a new sensor type or communication protocol is added, new containers are generated by deploying the corresponding protocol parsing image, realizing plug-and-play protocol expansion.

[0032] The protocol processing module is used to deploy the corresponding communication interface inside each Docker container to receive and parse the raw data uploaded by the sensors.

[0033] In a specific embodiment, when parsing the raw data, the protocol processing layer extracts characteristic values such as the sensor device ID, alarm status, alarm time, and alarm number, and encapsulates them into output data in a unified format according to the custom communication protocol.

[0034] The data output module is used to formulate a custom communication protocol, convert the parsed sensor data into text data in a unified format, and output it.

[0035] In a specific embodiment, the data output module converts sensor data into a standardized JSON text format including device identification, channel number, data value, and timestamp, and the JSON text format is used for unified parsing and processing by the backend system.

[0036] In a specific embodiment, the data output module supports a data receipt mechanism. When the client fails to receive data, it triggers the container retransmission logic, and the retransmission logic includes a maximum retransmission times limit.

[0037] In a specific embodiment, the custom communication protocol refers to Figure 3 , and at least includes the following fields: company number, transmission characteristic value, timestamp, receipt flag, current transmission times, maximum transmission times, additional information, and the fields are used to identify the data source, transmission direction, time attribute, and interaction status.

[0038] In the present invention, through the custom communication protocol, sensor data of different transmission protocols such as Modbus-TCP and CANOpen is converted into a unified text format, such as JSON, eliminating data format differences, simplifying the backend processing logic, improving the efficiency of data processing, reducing the processing cost and time consumption caused by inconsistent data formats, and laying a solid foundation for subsequent data analysis work.

[0039] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of this technology make various modifications or supplements to the described specific embodiments or use similar ways to replace them. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should belong to the protection scope of the present invention.

Claims

1. A computing device based on multi-sensor data acquisition, characterized in that, Including: A hardware module, which is provided with a variety of peripheral interfaces for connecting sensor devices with different communication protocols. The peripheral interfaces include CAN, UART, I2C, SPI, and network ports; A virtualization module, which is used to generate independent containers based on Docker technology to provide an isolated processing environment for different types of sensor data; A protocol processing module, which is used to deploy corresponding communication interfaces inside each Docker container to receive and parse the raw data uploaded by sensors; A data output module, which is used to formulate a custom communication protocol to convert the parsed sensor data into text data in a unified format and output it.

2. The computing device based on multi-sensor data acquisition according to claim 1, wherein, The peripheral interfaces support communication protocols such as Modbus-TCP, CANOpen, DeviceNet, and IEC61850, and are compatible with the access of water level gauges, flow meters, pressure sensors, and temperature sensors.

3. A computing device based on multi-sensor data acquisition according to claim 1, characterized in that, The hardware module uses a low-power ARM architecture processor, configures high-speed flash memory and dynamic memory, and supports the lightweight deployment and operation of the Docker containers.

4. A computing device based on multi-sensor data acquisition according to claim 1, characterized in that, The Docker containers achieve isolation of the operating environments for different sensor data processing logics through a resource isolation mechanism. The resource isolation includes independent allocation of CPU resources, memory space, and file system.

5. A computing device based on multi-sensor data acquisition according to claim 1, wherein The Docker containers support dynamic creation and deletion. When a new sensor type or communication protocol is added, new containers are generated by deploying the corresponding protocol parsing image, realizing plug-and-play protocol expansion.

6. The computing device based on multi-sensor data acquisition according to claim 1, characterized in that, When parsing the raw data, the protocol processing layer extracts characteristic values such as the sensor device ID, alarm status, alarm time, and alarm number, and encapsulates them into output data in a unified format according to the custom communication protocol.

7. A computing device based on multi-sensor data acquisition according to claim 1, characterized in that, The data output module converts the sensor data into a standardized JSON text format including device identification, channel number, data value, and timestamp. The JSON text format is used for unified parsing and processing by the backend system.

8. The computing device based on multi-sensor data acquisition according to claim 1, wherein The data output module supports a data receipt mechanism. When the client fails to receive data, it triggers the container retransmission logic, and the retransmission logic includes a maximum retransmission times limit.

9. A computing device based on multi-sensor data acquisition according to claim 1, wherein, The custom communication protocol includes at least the following fields: company number, transmission characteristic value, timestamp, receipt flag, current transmission times, maximum transmission times, and additional information. The fields are used to identify the data source, transmission direction, time attribute, and interaction status.

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