Environmental data acquisition, analysis and transmission gateway equipment

Abstract

The utility model discloses an environmental data acquisition, analysis and transmission gateway device, which integrates a visual module, a storage module, an NPU module and a gateway module in a system, can realize video stream localization processing, replaces an external video server, pushes the video stream to a cloud platform through the gateway module, reduces the cloud processing burden, and improves the efficiency. In addition, the system replaces a traditional combination of a data acquisition instrument, a video recorder and a router through single equipment, and equipment cost is greatly saved.

Description

Technical Field

[0001] This utility model relates to the field of gateway device technology, and in particular to an environmental data acquisition, analysis and transmission gateway device. Background Technology

[0002] Environmental data acquisition instruments are integrated devices used to collect various environmental parameters in real time, such as air quality, water quality, and soil, and then upload the data to the cloud after data processing and analysis, providing scientific basis for environmental protection and governance.

[0003] Traditional environmental data acquisition devices typically only include a power management unit, interface unit, data processing unit, and 4G transmission unit, with weak AI analysis capabilities. For example, the environmental data acquisition transmitter disclosed in CN214253415U only has an RS485 sensor interface, lacks an integrated video input interface, and uses a low-performance MCU without a dedicated NPU / GPU, making it unable to run video decoding and AI model inference, resulting in a complete lack of video analysis functionality. Furthermore, in terms of AI analysis, traditional data acquisition devices, if connected to an external video module, only support video recording and storage, lacking intelligent analysis capabilities (such as behavior recognition and abnormal event detection). This necessitates supervisory personnel to review and randomly check videos, leading to low efficiency and a high rate of missed detections. Utility Model Content

[0004] To address the aforementioned issues, this utility model proposes an environmental data acquisition, analysis, and transmission gateway device, which primarily solves the problems of insufficient AI analysis capabilities in existing environmental data acquisition instruments and high costs associated with expanding the device's functional modules.

[0005] To solve the above-mentioned technical problems, the technical solution of this utility model is as follows:

[0006] An environmental data acquisition, analysis, and transmission gateway device, comprising:

[0007] The sensor module is used to collect multimodal environmental data;

[0008] The vision module is used to acquire video data;

[0009] A storage module is used to store the video data;

[0010] The NPU module is used to deploy a local model library and to call and analyze the video data through the local model library.

[0011] The MCU module is used to perform statistics, storage, and cleaning on the environmental data and the processed video data, and output target data.

[0012] The gateway module is used to transmit the target data to the cloud platform via an automatically switching multi-protocol network.

[0013] In some implementations, the NPU module includes a Rockchip RK3568J processor, which has a peripheral video port and is connected to the signal output terminal of the vision module via the video port.

[0014] In some implementations, the MCU module is an ARM Cortex-M7 microcontroller, which communicates bidirectionally with the Rockchip RK3568J processor.

[0015] In some implementations, the gateway module integrates a WiFi unit, a 4G unit, a 5G unit, and an Ethernet interface to switch communication links according to the network environment.

[0016] In some implementations, the storage module is a solid-state drive (SSD).

[0017] In some implementations, the vision module is directly connected to the gateway module.

[0018] The beneficial effects of this utility model are as follows: by integrating a vision module, storage module, NPU module, and gateway module into the system, local processing of video streams can be achieved, replacing external video servers. The streams are pushed to the cloud platform through the gateway module, reducing the processing burden on the cloud. Furthermore, this system replaces the traditional combination of data acquisition device + video recorder + router with a single device, greatly saving equipment costs. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the architecture of the environmental data acquisition, analysis, and transmission gateway device disclosed in an embodiment of the present utility model. Figure 1 ;

[0020] Figure 2 This is a schematic diagram of the architecture of the environmental data acquisition, analysis, and transmission gateway device disclosed in an embodiment of the present utility model. Figure 2 . Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this utility model clearer and more explicit, the content of this utility model will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely for explaining this utility model and not for limiting it. Furthermore, it should be noted that, for ease of description, only the parts related to this utility model are shown in the accompanying drawings, not all of them.

[0022] This embodiment proposes an environmental data acquisition, analysis, and transmission gateway device, such as... Figure 1 and 2 As shown, it includes:

[0023] Sensor module 1 is used to collect multimodal environmental data, such as particulate matter concentration, harmful gases, and water pollution.

[0024] Vision module 2 is used to acquire video data. This vision module 2 can use a high-definition camera to acquire 2K or 4K video.

[0025] Storage module 3 is used to store video data, and storage module 3 can be selected as a solid-state drive;

[0026] NPU module 4 is used to deploy a local model library and call and analyze video data through the local model library (such as the lightweight YOLOv5s model). It mainly serves as the video processing center of this system. Through AI video analysis, it can detect the quantity of materials leaving the warehouse, cross-line areas, and human behavior. When an anomaly is detected, it can automatically capture on-site photos and record short videos, push them to the management platform in seconds via 4G network, and correlate them with sewage discharge data to quickly pinpoint the cause of the problem.

[0027] MCU module 5 is used to statistically analyze, store, and clean environmental data and processed video data, and output target data, serving as the central hub for data processing.

[0028] Gateway module 6 is used to transmit target data to cloud platform 7 via an automatically switching multi-protocol network.

[0029] In one example, NPU module 4 includes a Rockchip RK3568J processor. The Rockchip RK3568J processor has a peripheral video port, which is connected to the signal output of vision module 2. In this example, the Rockchip RK3568J processor used in NPU module 4 integrates four cores. It features a 2.0GHz processor, a 0.8TOPS NPU, and a Mali-G52 GPU. Furthermore, based on the Tongxin UOS Industrial Edition (Linux kernel adapted), it comes pre-installed with a domestic encryption module (SM2 / SM4 algorithm) and the SQLite database DM8, and has passed Level 3 Information Security Protection Certification, meeting the requirements for independent control in the environmental protection field. The industrial-grade hardware design includes multi-protocol acquisition interfaces such as 6 isolated RS485 channels (Modbus compatible), 2 CAN bus channels (ISO 11898), and 4 high-precision ADC channels (24-bit resolution), supporting simultaneous access to 50+ sensors and industrial equipment, solving the data fragmentation problem caused by the single interface of traditional equipment. It also has video processing capabilities, expanding with an M.2 interface to support SSD solid-state drives and 4K cameras (RTSP / ONVIF protocol), enabling localized video stream processing and replacing external video servers.

[0030] MCU module 5 is an ARM Cortex-M7 microcontroller, which communicates bidirectionally with the Rockchip RK3568J processor.

[0031] Gateway module 6 integrates a WiFi unit, a 4G unit, a 5G unit, and an Ethernet interface, which are used to switch communication links according to the network environment.

[0032] Optionally, the vision module 2 is directly connected to the gateway module 6. The video data collected by the vision module 2 can be directly transmitted to the cloud platform 7 through the gateway module 6 without being processed by the NPU module 4 or the MCU module 5. The cloud platform 7 can monitor the real-time images of the deployment area in real time, saving the computing resources of the NPU module 4 or the MCU module 5.

[0033] The pin connections and data flow between NPU module 4 (RH3568J) and other modules are described below:

[0034] Vision Module 2: The CS10_D0N / P (A1-A4 pins) of NPU Module 4 receives the MIPI-CSI4Lane data stream from the camera, which carries raw video input in YUV422 format at 4K@30fps. A 1.5Gbps / lane differential clock signal is received by the CS10_CLKN / P (B1-B2 pins) to ensure timing accuracy of data sampling. When standby mode is enabled, the NPU's USB3.0_DM / DP (C1-C2 pins) receives video streams from ONVIF-compatible cameras via the SuperSpeed ​​protocol. GPIO1_C7 (D1 pin) serves as a control output, sending a 3.3VTTL high-level signal to the external MOSFET to activate the camera power supply system.

[0035] Storage Module 3: The SATA_TXP / N (E1-E2 pins) of NPU Module 4 establishes bidirectional communication with the SSD, enabling video stream write and read operations up to 600MB / s based on the SATA 3.0 protocol. PCIE_CLKREQ_N (F1 pin) outputs a 1.8V LVCMOS low-level signal to the SSD, triggering the storage device to resume from sleep mode. When an anomaly is detected, GPIO4_D1 (G1 pin) drives an external indicator light in open-drain output mode, periodically flashing to transmit a storage fault alarm to the external system.

[0036] MCU Module 5: The SPI1_CLK (H1 pin) of NPU Module 4 outputs a 50MHz main clock signal to the ARM Cortex-M7, synchronously controlling the bidirectional data channel SPI1_MOSI (H2 pin). This interface carries AI analysis results in JSON format and transmits them to the MCU's SPI_MISO. UART3_TX (I1 pin) continuously sends device control commands to the MCU's USART2_RX at a baud rate of 115200. When an NPU exception occurs, the rising edge interrupt signal generated by GPIO3_B5 (J1 pin) directly triggers the MCU's EXTI9 interrupt service routine.

[0037] Gateway Module 6: The PCIe_TXP / N (K1-K2 pins) of NPU Module 4 outputs PCIe 2.0x1 protocol data streams to the 4G / 5G module, establishing a 5Gbps bandwidth emergency transmission channel. RGMII_TXD0-3 (L1-L4 pins) drives the Gigabit Ethernet PHY chip with a 125MHz clock, enabling high-speed encapsulation and transmission of network data packets. GPIO2_A3 (M1 pin) outputs a 3.3V TTL level to the network switching circuit; a high level forces the data transmission path to switch to the 5G high-speed link, while maintaining the 4G basic communication connection by default.

[0038] Power supply system (not shown in the diagram): The NPU receives a 1.2V / 3A core power supply from the TPS54332 via VDD_1V2 (N1 pin), and simultaneously obtains a 3.3V / 2A peripheral power supply from the LDO regulator via VDD_3V3 (N2 pin). PMC_PWRKEY (01 pin) serves as the system-level control output. Its open-drain output characteristic supports generating a shutdown pulse signal by pressing and holding for 3 seconds, which directly acts on the power management IC to achieve hardware shutdown control.

[0039] The above embodiments are merely illustrative of the technical concept and features of this utility model, and are intended to enable those skilled in the art to understand the content of this utility model and implement it accordingly. They should not be construed as limiting the scope of protection of this utility model. All equivalent changes or modifications made based on the substance of the content of this utility model should be covered within the scope of protection of this utility model.

Claims

1. An environmental data collection analysis transmission gateway device, characterized by, include: The sensor module is used to collect multimodal environmental data; The vision module is used to acquire video data; A storage module is used to store the video data; The NPU module is used to deploy a local model library and to call and analyze the video data through the local model library. The MCU module is used to perform statistics, storage, and cleaning on the environmental data and the processed video data, and output target data. The gateway module is used to transmit the target data to the cloud platform via an automatically switching multi-protocol network.

2. The environmental data collection analysis transmission gateway device of claim 1, wherein, The NPU module includes a Rockchip RK3568J processor. The Rockchip RK3568J processor has a video port on its peripheral side, which is connected to the signal output terminal of the vision module.

3. The environmental data collection analysis transmission gateway device of claim 2, wherein, The MCU module is an ARM Cortex-M7 microcontroller, which communicates bidirectionally with the Rockchip RK3568J processor.

4. The environmental data collection analysis gateway device of claim 1, wherein, The gateway module integrates a WiFi unit, a 4G unit, a 5G unit, and an Ethernet interface, and is used to switch communication links according to the network environment.

5. The environmental data collection analysis gateway device of claim 1, wherein, The storage module is a solid-state drive.

6. The environmental data collection analysis gateway device of claim 1, wherein, The vision module is directly connected to the gateway module.

Images