Multifunctional environment monitoring node circuit

Abstract

The utility model relates to a multifunctional environment monitoring node circuit, which is characterized by comprising a sensor module group, a signal processing and fusion module, a low-power wide area network communication unit, a power management module and a fault diagnosis and self-recovery module which work cooperatively through electric connection. The sensor module group integrates a plurality of environment sensors, including a gas sensor, a humidity sensor, a temperature sensor and an illumination intensity sensor; the signal processing and fusion module comprises an analog signal conditioning circuit, an analog-to-digital converter and a data fusion processing circuit based on a field programmable gate array. The circuit can comprehensively monitor and fuse various environmental parameters, accurately reflect the environmental state, and is rich in function and stable and reliable in operation.

Description

Technical Field

[0001] This utility model relates to a multifunctional environmental monitoring node circuit. Background Technology

[0002] With the rapid development of urban environmental management, industrial safety production, and precision agriculture, the demand for real-time monitoring of environmental parameters is increasing. Currently, the following technical solutions are mainly used in the field of environmental monitoring:

[0003] An STM32-based environmental monitoring system uses an STM32 chip as its core and connects to sensors for temperature, humidity, light intensity, and PM2.5 to collect parameters, which are then displayed on an LCD screen. While this solution offers real-time performance and cost-effectiveness, it only supports monitoring a limited number of parameters (such as temperature, humidity, and PM2.5) and relies on wired transmission, thus limiting deployment flexibility.

[0004] Industrial pollution source monitoring systems involve installing sensors for flow, water quality, and gas at discharge points or production stages. Monitoring data is then uploaded to an environmental protection platform via data acquisition terminals. However, these systems are limited to specific pollution sources (such as wastewater and exhaust gas), cannot perform comprehensive multi-parameter analysis, and rely on fixed transmission lines, making it difficult to cover complex industrial scenarios.

[0005] ZigBee wireless sensor networks: These networks utilize ZigBee technology to remotely transmit parameters such as temperature, humidity, and light intensity. However, ZigBee technology has weak anti-interference capabilities (the 2.4GHz band is susceptible to interference from devices like Wi-Fi), a short transmission distance (typically only a few hundred meters), and is prone to data loss in complex electromagnetic environments, such as industrial or urban areas, making it difficult to meet the needs of large-scale monitoring.

[0006] The aforementioned existing technologies generally suffer from the following problems:

[0007] Complex cabling: Traditional systems rely heavily on wired connections, and laying cables in large areas or complex environments is costly and difficult to maintain;

[0008] Limited monitoring functionality: Some devices only support monitoring of a single parameter or a limited number of parameters, and the accuracy of non-contact measurement is insufficient, failing to meet the comprehensive evaluation needs of multiple scenarios;

[0009] Poor transmission stability: Wireless transmission (such as ZigBee) has weak anti-interference ability, and wired transmission distance is limited, resulting in insufficient monitoring range and data reliability;

[0010] Power supply depends on external power source: nodes need to frequently replace batteries or external power sources, resulting in high maintenance costs in remote or unattended scenarios.

[0011] Therefore, there is an urgent need for an environmental monitoring node circuit that integrates multi-parameter monitoring, long-distance wireless transmission, self-powered operation, and multi-parameter fusion functions to address the shortcomings of existing technologies. Utility Model Content

[0012] The purpose of this invention is to provide a multifunctional environmental monitoring node circuit that can comprehensively monitor and integrate various environmental parameters, accurately reflect the environmental status, and has rich functions, stable and reliable operation.

[0013] To achieve the above objectives, the technical solution adopted by this utility model is: a multifunctional environmental monitoring node circuit, characterized in that it includes: a sensor module group, a signal processing and fusion module, a low-power wide area network (LPWAN) communication unit, a power management module, and a fault diagnosis and self-recovery module, all of which work together through electrical connections; the sensor module group integrates multiple environmental sensors, including a gas sensor, a humidity sensor, a temperature sensor, and a light intensity sensor; the signal processing and fusion module includes an analog signal conditioning circuit, an analog-to-digital converter (ADC), and a data fusion processing circuit based on a field-programmable gate array (FPGA); the power management module includes a solar power supply unit and an energy storage battery management circuit.

[0014] Furthermore, the gas sensor is used to detect the concentrations of carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOx), and volatile organic compounds (VOCs);

[0015] The humidity sensor is a capacitive or resistive sensor with an accuracy of ±2%RH;

[0016] The temperature sensor is a thermistor or a semiconductor sensor, with a measurement range of -40℃ to 125℃ and an accuracy of ±0.5℃.

[0017] The light intensity sensor is composed of a photodiode or a photoresistor, and its measurement range is 0-100000 Lux.

[0018] Furthermore, the analog signal conditioning circuit is used to amplify, filter, and linearize the analog signal output by the sensor;

[0019] The analog-to-digital converter is a 24-bit high-resolution SAR ADC or a sigma-delta ADC, and its sampling frequency can be configured according to the sensor characteristics.

[0020] The data fusion processing circuit is implemented through a field-programmable gate array, including multiple AND gates, OR gates, and XOR gates, used to fuse data from various environmental sensors and output a comprehensive environmental status assessment result.

[0021] Furthermore, the field-programmable gate array (FPGA) includes an AND gate with a number of environmental sensors. The two inputs of each AND gate are connected to the signal input of the corresponding environmental sensor and a weighted level signal, respectively. The outputs of the multiple AND gates are connected to the input of an OR gate, and the output of the OR gate is a binary weighted sum of the output data from the multiple environmental sensors. This enables the determination of the priority of different environmental sensors.

[0022] In the field-programmable gate array, for two environmental sensors A and B, A and B are respectively connected to the two input terminals of an XOR gate. If the output is 0, the two numbers are equal; if the output is 1, the two numbers are not equal, thereby realizing the determination of the equality of the output data of the two environmental sensors.

[0023] In the field-programmable gate array, for two environmental sensors A and B, A is connected to one input of an AND gate, and B is first passed through an NOT gate and then connected to the other input of the AND gate. If the output of the AND gate is 1, it means A > B; if the output of the AND gate is 0, the size is determined by combining the output of the XOR gate; thus, the size comparison of the output data of the two environmental sensors is realized.

[0024] Furthermore, the low-power wide-area network communication unit is implemented using a LoRa module, which operates in the Sub-GHz band and communicates wirelessly with remote servers or data centers.

[0025] Furthermore, the solar power supply unit includes a monocrystalline silicon or polycrystalline silicon solar panel and a maximum power point tracking (MPPT) circuit for converting solar energy into electrical energy;

[0026] The energy storage battery management circuit includes a lithium-ion battery and a charging management chip, supporting constant voltage charging, constant current charging modes, and monitoring of battery voltage, current, and temperature.

[0027] Furthermore, the fault diagnosis and self-recovery module includes a circuit status monitoring unit, a fault diagnosis logic circuit based on a complex programmable logic device (CPLD), and a self-recovery control circuit.

[0028] Furthermore, the circuit status monitoring unit includes a voltage monitoring circuit, a current monitoring circuit, and a temperature monitoring circuit, which respectively sample the voltage, current, and temperature of key circuit nodes through a comparator and an ADC;

[0029] The fault diagnosis logic circuit is implemented by a complex programmable logic device, and its input terminals are respectively connected to the output terminals of the voltage monitoring circuit, the current monitoring circuit, and the temperature monitoring circuit.

[0030] The self-recovery control circuit switches the backup solar panel into the circuit by controlling the relay switching inside the control node, or adjusts the working mode of the node to reduce power consumption and wait for the solar panel to resume normal operation.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] This invention integrates a sensor module group encompassing various high-precision environmental sensors, including gas sensors, humidity sensors, temperature sensors, and light intensity sensors, enabling comprehensive and accurate monitoring of environmental parameters. Furthermore, these sensors are well-integrated and work collaboratively in the circuit design, improving the overall performance and reliability of the equipment. Simultaneously, by implementing a data fusion processing circuit on an FPGA, this invention comprehensively considers multiple environmental parameters, providing a more accurate reflection of environmental conditions and offering users reliable environmental quality information. In addition, this invention achieves low-power, long-distance data transmission and solar self-powering, enabling the node to operate stably for extended periods in complex environments. This invention also incorporates a fault diagnosis and self-recovery module, effectively enabling rapid fault location and analysis, and restoring the node to its normal operating state. Therefore, this invention possesses strong practicality and broad application prospects. Attached Figure Description

[0033] Figure 1 This is a block diagram illustrating the implementation principle of the multifunctional environmental monitoring node circuit provided in this embodiment of the utility model.

[0034] Figure 2 This is a circuit diagram of the sensor module group in an embodiment of this utility model;

[0035] Figure 3 This is a circuit diagram of the analog signal conditioning circuit in an embodiment of this utility model;

[0036] Figure 4 This is a circuit diagram of the analog-to-digital converter (ADC) in an embodiment of this utility model;

[0037] Figure 5 This is a circuit diagram of the data fusion processing circuit in an embodiment of this utility model;

[0038] Figure 6 This is a schematic diagram of the FPGA internal implementation circuit in this embodiment of the utility model;

[0039] Figure 7 This is a circuit diagram of the low-power wide-area network (LPWAN) communication unit in an embodiment of this utility model;

[0040] Figure 8 This is a circuit diagram of the power management module in an embodiment of this utility model;

[0041] Figure 9 This is a circuit diagram of the voltage monitoring circuit in an embodiment of this utility model;

[0042] Figure 10 This is a circuit diagram of the current monitoring circuit in an embodiment of this utility model. Detailed Implementation

[0043] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0044] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0045] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0046] like Figure 1 As shown, this embodiment provides a multifunctional environmental monitoring node circuit, including: a sensor module group, a signal processing and fusion module, a low-power wide-area network (LPWAN) communication unit, a power management module, and a fault diagnosis and self-recovery module. Each module works collaboratively through electrical connections. The sensor module group integrates multiple environmental sensors, including a gas sensor, a humidity sensor, a temperature sensor, and a light intensity sensor. The signal processing and fusion module includes an analog signal conditioning circuit, an analog-to-digital converter (ADC), and a data fusion processing circuit based on a field-programmable gate array (FPGA). The power management module includes a solar power supply unit and an energy storage battery management circuit.

[0047] 1. Sensor module group

[0048] like Figure 2 As shown, the sensor module group integrates multiple high-precision environmental sensors, including but not limited to:

[0049] Gas sensors are used to detect air quality, such as the concentration of harmful gases like carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen oxides (NOx), as well as the content of volatile organic compounds (VOCs).

[0050] Humidity sensor: A high-precision capacitive or resistive humidity sensor that can monitor changes in ambient humidity in real time with an accuracy of ±2%RH.

[0051] Temperature sensor: Employs a thermistor or semiconductor temperature sensor, with a measurement range of -40℃ to 125℃ and an accuracy of ±0.5℃.

[0052] Light intensity sensor: Composed of photodiode or photoresistor, it can measure light intensity in the range of 0-100000 Lux and is used to assess ambient light conditions.

[0053] 2. Signal Processing and Fusion Module

[0054] Analog signal conditioning circuit: This circuit amplifies, filters, and linearizes the analog signals output from different sensors. For the low-level analog signals from the gas sensor, operational amplifiers are used for multi-stage amplification, while active filtering circuits are employed to remove high-frequency noise interference. The circuit diagram of the analog signal conditioning circuit is shown below. Figure 3 As shown.

[0055] Analog-to-Digital Converter (ADC): A high-resolution (at least 16-bit) successive approximation register (SAR) ADC or sigma-delta ADC is used to convert the conditioned analog signal into a digital signal. The ADC sampling frequency can be flexibly configured according to the characteristics of different sensors to ensure the accuracy and real-time performance of data acquisition. This embodiment uses a 24-bit high-resolution ADC. The circuit diagram of the analog-to-digital converter (ADC) is shown below. Figure 4 As shown.

[0056] Data fusion processing circuit: Implemented based on a Field-Programmable Gate Array (FPGA), it uses a custom algorithm to fuse digital signals from different sensors. By analyzing the correlation and weighting relationships between the sensor data, it derives a comprehensive assessment result reflecting the environmental condition, such as the Air Quality Index (AQI). The circuit diagram of the data fusion processing circuit is shown below. Figure 5 As shown. The internal circuit principle of the FPGA is as follows. Figure 6 As shown.

[0057] 1) Determine the priority of the sensors:

[0058] In the FPGA, there are AND gates with a number of environmental sensors. The two inputs of each AND gate are connected to the signal input of the corresponding environmental sensor and a weighted level signal, respectively. The outputs of the multiple AND gates are connected to the input of an OR gate, and the output of the OR gate is the binary weighted sum of the output data of the multiple environmental sensors. This enables the determination of the priority of different environmental sensors.

[0059] Taking three sensors as an example. The outputs of the three sensors are A, B, and C, with corresponding weights of 4, 2, and 1 respectively. That is, the outputs of these three sensors can be viewed as a 3-bit binary number, and their corresponding weights are 2. 2:2 1 :2 0 .

[0060] The sensor signal is weighted using three AND gates (such as those in the 74LS08 chip). The signal from sensor A is then weighted by the weight bit 2. 2 (This weighted bit can be represented by a fixed high-level signal) Perform an AND operation; similarly, AND the signal from sensor B with weighted bit 2. 1 2. Signal and weight bit of sensor C 0 Perform AND operations separately. The weighting relationship can be represented by corresponding resistors or other circuits, such as using voltage dividers with different resistance values ​​to represent different weight levels.

[0061] Then connect the outputs of these three AND gates to the inputs of an OR gate (such as the OR gate in the 74LS32 chip). The output of the OR gate is the binary weighted sum of the three sensor data.

[0062] 2) Determining the magnitude of sensor readings

[0063] Equality comparison: In an FPGA, for two environmental sensors A and B, A and B are connected to the two inputs of an XOR gate. If the output is 0, the two numbers are equal; if the output is 1, the two numbers are not equal, thus realizing the equality judgment of the output data of the two environmental sensors.

[0064] Size comparison: In an FPGA, for two environmental sensors A and B, A is connected to one input of an AND gate, and B is first passed through a NOT gate and then connected to the other input of the AND gate. If the output of the AND gate is 1, it means A > B; if the output of the AND gate is 0, the size is determined by combining the output of the XOR gate; thus, the size comparison of the output data of the two environmental sensors is realized.

[0065] 3. Low-Power Wide Area Network (LPWAN) Communication Unit

[0066] The LPWAN communication unit uses a LoRa module to achieve wireless communication with remote servers or data centers. LoRa modules operate in the Sub-GHz band (such as 433MHz or 868MHz), offering advantages such as long-distance transmission (up to several kilometers to tens of kilometers) and low power consumption, making them suitable for stable transmission of environmental monitoring data in complex environments. The circuit diagram of the LPWAN communication unit is shown below. Figure 7 As shown.

[0067] 4. Power Management Module

[0068] The power management module includes a solar power unit and an energy storage battery management circuit.

[0069] Solar power unit: Equipped with high-efficiency solar panels to convert solar energy into electrical energy. The solar panels use monocrystalline or polycrystalline silicon materials with a conversion efficiency of ≥20% and are equipped with maximum power point tracking (MPPT) circuitry to improve solar energy utilization efficiency.

[0070] Energy storage battery management circuit: Utilizing lithium-ion batteries as energy storage components, it is equipped with a charging management chip to achieve charge / discharge protection, power monitoring, and equalization management of the battery. The charging management chip supports multiple charging modes, such as constant voltage charging and constant current charging, and can monitor battery voltage, current, and temperature parameters in real time to ensure safe and stable battery operation. The circuit diagram of the power management module is shown below. Figure 8 As shown.

[0071] 5. Fault Diagnosis and Self-Recovery Module

[0072] The fault diagnosis and self-recovery module includes a circuit status monitoring unit, a fault diagnosis logic circuit, and a self-recovery control circuit.

[0073] The circuit status monitoring unit includes voltage monitoring, current monitoring, and temperature monitoring circuits, which monitor the voltage, current, and temperature of key circuit nodes within the node in real time. By setting voltage detection points and current detection resistors on the power line, and using comparators and analog-to-digital converters to sample and analyze the voltage and current signals, the unit immediately triggers a fault diagnosis process upon detecting any abnormalities (such as overvoltage, overcurrent, or overtemperature). The circuit diagrams for the voltage monitoring circuit and the current monitoring circuit are shown below. Figure 9 , 10 As shown.

[0074] Fault diagnosis logic circuit: Implemented based on a complex programmable logic device (CPLD), its inputs are connected to the outputs of voltage monitoring circuit, current monitoring circuit, and temperature monitoring circuit, respectively. Based on feedback from the circuit status monitoring unit, the fault diagnosis logic circuit quickly locates and analyzes the cause of the fault. If an abnormal output voltage of the solar panel is detected, the fault diagnosis logic circuit will analyze possible causes such as shading, damage to the solar panel surface, or connection circuit failure.

[0075] Self-recovery control circuit: After determining the cause of the fault, it automatically takes corresponding self-recovery measures according to the fault type and severity. For example, for a drop in output voltage caused by shading of the solar panel surface, the self-recovery control circuit can switch the relay inside the control node to connect a backup solar panel to the circuit, or adjust the node's operating mode (such as reducing the sensor sampling frequency, reducing the communication frequency, etc.) to reduce power consumption and wait for the solar panel to return to normal operation.

[0076] In this embodiment, the multifunctional environmental monitoring node circuit supplies power to the sensor module group through 3.3V and 5V interfaces; the PB12 interface of the gas sensor is connected to the v+ and v- terminals of the analog signal conditioning circuit; the SCL and SDA interfaces of the temperature, humidity, and light intensity sensors are connected to the SCL and SDA interfaces of the main control board; the analog signal conditioning circuit provides 3.3V voltage through the AMS1117 chip; the SCLK and CS interfaces of the ADC are connected to the FPGA, and the DOUT interface is connected to the A terminal of the FPGA; the A and B terminals of the FPGA are connected to the v+ and v- terminals of the analog signal conditioning circuit, and the B and D terminals are connected to the SCLK and CS interfaces of the ADC; the power management module supplies power to the entire system; the ADIN interface of the voltage monitoring circuit is connected to the dataout0 terminal of the fault diagnosis logic circuit, and the IP+ and IP- interfaces of the current monitoring circuit are connected to the dataout1 and dataout2 terminals of the fault diagnosis logic circuit.

[0077] The collaborative workflow of each module in the multifunctional environmental monitoring node circuit is as follows:

[0078] After the node starts, the sensor module group collects environmental parameters in real time → the signal processing and fusion module conditions, converts and fuses the data → the LPWAN communication unit uploads the fused data to the server → the power management module dynamically adjusts the power supply strategy → the fault diagnosis and self-recovery module monitors the circuit status in real time and triggers self-recovery when abnormal (see device flowchart).

[0079] In summary, this invention achieves comprehensive, reliable, and low-maintenance environmental monitoring through multi-sensor integration, FPGA data fusion, LoRa long-distance transmission, solar self-powered operation, and fault self-recovery technology, making it suitable for various scenarios such as urban, industrial, and agricultural environments.

[0080] The above description is merely a preferred embodiment of this utility model and is not intended to limit the utility model in any other way. Any person skilled in the art may make changes or modifications to the disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of this utility model without departing from its scope of protection shall still fall within the protection scope of this utility model.

Claims

1. A multifunctional environmental monitoring node circuit, characterized in that, include: The system comprises a sensor module group, a signal processing and fusion module, a low-power wide-area network communication unit, a power management module, and a fault diagnosis and self-recovery module. These modules work collaboratively via electrical connections. The sensor module group integrates multiple environmental sensors, including a gas sensor, a humidity sensor, a temperature sensor, and a light intensity sensor. The signal processing and fusion module includes an analog signal conditioning circuit, an analog-to-digital converter, and a data fusion processing circuit based on a field-programmable gate array (FPGA). The power management module includes a solar power supply unit and an energy storage battery management circuit.

2. The multifunctional environmental monitoring node circuit according to claim 1, characterized in that, The gas sensor is used to detect the concentrations of carbon monoxide, sulfur dioxide, nitrogen oxides, and volatile organic compounds. The humidity sensor is a capacitive or resistive sensor with an accuracy of ±2%RH; The temperature sensor is a thermistor or a semiconductor sensor, with a measurement range of -40℃ to 125℃ and an accuracy of ±0.5℃. The light intensity sensor is composed of a photodiode or a photoresistor, and its measurement range is 0-100000 Lux.

3. The multifunctional environmental monitoring node circuit according to claim 1, characterized in that, The analog signal conditioning circuit is used to amplify, filter, and linearize the analog signal output by the sensor. The analog-to-digital converter is a 24-bit high-resolution SAR ADC or a sigma-delta ADC, and its sampling frequency can be configured according to the sensor characteristics. The data fusion processing circuit is implemented through a field-programmable gate array, including multiple AND gates, OR gates, and XOR gates, used to fuse data from various environmental sensors and output a comprehensive environmental status assessment result.

4. The multifunctional environmental monitoring node circuit according to claim 3, characterized in that, The field-programmable gate array (FPGA) includes an AND gate with a number of environmental sensors. The two inputs of each AND gate are connected to the signal input of the corresponding environmental sensor and a weighted level signal, respectively. The outputs of the AND gates are connected to the input of an OR gate, and the output of the OR gate is a binary weighted sum of the output data from the multiple environmental sensors. This enables the determination of the priority of different environmental sensors. In the field-programmable gate array, for two environmental sensors A and B, A and B are respectively connected to the two input terminals of an XOR gate. If the output is 0, the two numbers are equal; if the output is 1, the two numbers are not equal, thereby realizing the determination of the equality of the output data of the two environmental sensors. In the field-programmable gate array, for two environmental sensors A and B, A is connected to one input of an AND gate, and B is first passed through an NOT gate and then connected to the other input of the AND gate. If the output of the AND gate is 1, it means A > B; if the output of the AND gate is 0, the size is determined by combining the output of the XOR gate; thus, the size comparison of the output data of the two environmental sensors is realized.

5. The multifunctional environmental monitoring node circuit according to claim 1, characterized in that, The low-power wide-area network communication unit is implemented using a LoRa module, which operates in the Sub-GHz band and communicates wirelessly with remote servers or data centers.

6. The multifunctional environmental monitoring node circuit according to claim 1, characterized in that, The solar power supply unit includes a monocrystalline silicon or polycrystalline silicon solar panel and a maximum power point tracking circuit for converting solar energy into electrical energy; The energy storage battery management circuit includes a lithium-ion battery and a charging management chip, supporting constant voltage charging, constant current charging modes, and monitoring of battery voltage, current, and temperature.

7. The multifunctional environmental monitoring node circuit according to claim 1, characterized in that, The fault diagnosis and self-recovery module includes a circuit status monitoring unit, a fault diagnosis logic circuit based on complex programmable logic devices, and a self-recovery control circuit.

8. The multifunctional environmental monitoring node circuit according to claim 7, characterized in that, The circuit status monitoring unit includes a voltage monitoring circuit, a current monitoring circuit, and a temperature monitoring circuit, which respectively sample the voltage, current, and temperature of key circuit nodes through a comparator and an ADC. The fault diagnosis logic circuit is implemented by a complex programmable logic device, and its input terminals are respectively connected to the output terminals of the voltage monitoring circuit, the current monitoring circuit, and the temperature monitoring circuit. The self-recovery control circuit switches the backup solar panel into the circuit by controlling the relay switching inside the control node, or adjusts the working mode of the node to reduce power consumption and wait for the solar panel to resume normal operation.

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