Intelligent Internet of Things non-intrusive sensor controller

Abstract

The invention relates to an intelligent internet of things non-intrusive sensor controller. The system comprises a data acquisition unit, a data processing unit, a communication transmission unit and a remote operation and maintenance control unit, collecting first pipeline data, second signal data and third terminal data, and performing processor edge calculation, result screening and abnormal value elimination on the three types of data to obtain regular data; judging the battery voltage and the switching value according to a preset threshold value, and generating an alarm identifier; classifying and caching the regular data and the alarm identifier to obtain a standardized data frame; acquiring the data frame by adopting a modulation mode; synchronously transmitting the second signal data and generating a gateway core jump packet, and simultaneously completing terminal power-on and obtaining cloud platform instruction information; corresponding data parameters are adjusted according to the instruction, a cloud platform control instruction is received by means of an alarm identifier, a relay is driven to act after the instruction is transmitted through a LoRa channel, and the equipment state is read in real time based on regular data; and low-power-consumption data acquisition and remote control in a scattered scene are realized.

Description

A smart IoT non-intrusive sensor controller Technical Field

[0001] This invention belongs to the field of intelligent control technology, specifically relating to a non-intrusive sensor controller for the Internet of Things. Background Technology

[0002] Currently, the field of industrial IoT monitoring and control still has the following areas for improvement: In industrial production, energy transmission, infrastructure operation and maintenance, real-time monitoring and remote control of pipeline operating status, environmental parameters, and equipment working conditions are key to ensuring stable system operation and reducing operation and maintenance costs. However, existing related technical solutions still have many pain points that urgently need to be addressed, such as: poor deployment adaptability. Traditional wired monitoring systems require a large amount of cabling construction, which is not only costly and time-consuming, but also easily limited by factors such as site terrain and equipment distribution. It is difficult to implement in decentralized, remote, or no mains power supply scenarios. In addition, some monitoring solutions require destructive installation of pipelines and equipment, affecting the structural integrity and operational safety of the original facilities.

[0003] The contradiction between power consumption and maintenance costs is prominent. Existing wireless monitoring equipment often suffers from high power consumption, requiring frequent battery replacements or on-site charging. This results in a large workload and high costs for long-term maintenance, especially in remote areas where the difficulty and cost of equipment maintenance are further increased, making it difficult to meet the needs of long-term stable monitoring.

[0004] Insufficient data acquisition accuracy and reliability, complex industrial environments, electromagnetic interference, temperature fluctuations and other factors can easily lead to a large amount of noise in the acquired data. Existing solutions lack a sound data processing mechanism and do not effectively integrate functions such as noise filtering and outlier removal, often resulting in data distortion, false alarms and missed alarms, which affect the accuracy of subsequent decision-making.

[0005] The communication and networking stability is poor. Some wireless monitoring systems use a single communication method, which has weak anti-interference ability, limited transmission distance, and lacks automatic networking and self-healing mechanisms for disconnection. The networking configuration of terminal equipment is cumbersome. Once a network interruption occurs, manual intervention is required to restore the connection, which seriously affects the continuous operation of the system.

[0006] The operation and maintenance efficiency is low. Existing solutions mostly rely on on-site operation for equipment parameter configuration and fault diagnosis, lacking remote operation and maintenance capabilities and resulting in delayed fault response. At the same time, the alarm mechanism is simple, covering only a few abnormal scenarios, and the transmission delay of control commands is high, making it impossible to achieve rapid adjustment of equipment status and difficult to adapt to the efficient operation and maintenance needs of industrial scenarios.

[0007] To address the aforementioned issues, there is an urgent need for a non-intrusive, low-power, highly reliable sensor control solution that supports remote intelligent operation and maintenance, in order to overcome the limitations of existing technologies and improve the level of intelligence in industrial IoT monitoring and control. Summary of the Invention

[0008] To address the aforementioned problems in existing technologies, this invention provides a non-intrusive intelligent IoT sensor controller. The objective of this invention can be achieved through the following technical solution: a data acquisition unit, a data processing unit, a communication transmission unit, and a remote operation and maintenance control unit. The data acquisition unit acquires first pipeline data, second signal data, and third terminal data through a preset LoRa acquisition terminal. The data processing unit utilizes the first pipeline data, second signal data, and third terminal data, performs edge computing processing through corresponding processors, filters the processing results, removes outliers using the filtering results, and obtains regularized data. Based on a preset threshold, it performs... The system determines and acquires an alarm identifier; it classifies and caches the standardized data and the alarm identifier to acquire a standardized data frame; the communication transmission unit establishes a bidirectional communication connection through LoRa wireless technology and acquires the standardized data frame using modulation; it synchronously transmits the second signal data to generate a network key-pinch packet; simultaneously, it powers on the terminal and synchronously acquires instruction information from the cloud platform; the remote operation and maintenance control unit adjusts the corresponding data parameters based on the instruction information; it acquires control instructions from the cloud platform using the alarm identifier, transmits them through the LoRa channel, drives the relay to perform corresponding actions, and reads the device status in real time based on the standardized data.

[0009] As a preferred technical solution of the present invention, the specific process of performing edge computing processing and filtering the processing results by the corresponding processor includes: using the processor to call the built-in filtering algorithm to filter noise from the first pipeline data, the second signal data, and the third terminal data to obtain raw data segments that meet the threshold; and performing preliminary filtering operations on the temperature, pressure, and humidity data based on preset range and preset data interval filtering conditions for temperature, pressure, and humidity to obtain compliant data.

[0010] Specifically, the outlier removal using the screening results includes: extracting data based on the compliance data, comparing the extracted temperature, pressure, and humidity data with historical data to identify abrupt data points that deviate from the trend curve; verifying the abrupt data points using the standard deviation test, obtaining the verification results, and removing the abrupt data points as outliers.

[0011] Specifically, the acquisition of the alarm identifier includes: based on the battery voltage value of the regularized data extraction terminal, comparing the battery voltage value with a preset low power threshold to generate a power alarm identifier; monitoring the switch status in the second signal data in real time, generating a switch change alarm identifier using contact change signal information and marking the change timestamp.

[0012] Specifically, the classification caching process includes: classifying the regularized data, combining it with the unique identifier of the corresponding device to obtain a classification dataset; storing the classification dataset, sorting it using a time-series storage method, and obtaining standardized data frames.

[0013] Specifically, the process of establishing a two-way communication connection through LoRa wireless technology includes: configuring the communication parameters of the LoRa module and establishing a star network connection with the LoRa+4G gateway based on the format requirements of the standardized data frame; the gateway concurrently receiving the standardized data frames of the terminal through the LoRa downlink communication channel.

[0014] Specifically, the process of generating a heartbeat packet involves: extracting the status information from the second signal data and integrating the unique identifier, generating a data packet using a preset heartbeat packet format on the cloud platform, and sending the data packet at regular intervals.

[0015] Specifically, the power-on process of the terminal includes: reading the device address and network frequency band parameters preset by the hardware DIP switch; scanning the surrounding LoRa+4G gateway signals based on the preset LoRa networking protocol; initiating a bidirectional communication connection request; reporting standardized data frames based on the communication connection request result; and obtaining the terminal's network registration in the star network.

[0016] Specifically, obtaining instruction information from the cloud platform includes: using a gateway to listen to instruction data packets issued by the cloud platform; parsing the instruction data packets to extract three types of instructions: remote configuration instructions, device control instructions, and gateway restart instructions, and then classifying and forwarding these three types of instructions.

[0017] Specifically, the process of adjusting the corresponding data parameters includes: adjusting the data acquisition cycle using the remote configuration command, and updating the terminal's acquisition frequency parameters; modifying the gateway's configuration parameters based on the remote configuration command and restarting the gateway communication module.

[0018] Specifically, obtaining the control commands from the cloud platform includes: generating control commands based on the alarm identifier, converting the control commands into a command format supported by the LoRa protocol, and labeling the device address of the target IO control terminal.

[0019] Specifically, the real-time reading of device status includes: acquiring device status data through a local interface and an Ethernet port; and retrieving the terminal's collected data, IO port status, and alarm records using the cached regularized data to obtain real-time device status records.

[0020] The beneficial effects of this invention are as follows: by adopting a non-intrusive deployment design and LoRa wireless communication technology, it eliminates the need to damage the on-site pipeline and equipment structure, freeing it from the dependence on wiring in traditional wired solutions. It is suitable for industrial scenarios that are distributed, remote, without mains power, and where wiring is difficult, significantly reducing deployment difficulty and construction costs. Relying on low-power hardware design and intelligent sleep mechanism, the sensing terminal can achieve ultra-long standby time, reducing the frequency of power supply replacement and on-site maintenance, lowering long-term operation and maintenance costs, and ensuring long-term stable operation of the system.

[0021] By combining edge computing with multiple data processing mechanisms, functions such as filtering and denoising, range selection, trend comparison and anomaly verification are integrated to effectively eliminate interference signals and abnormal data, ensuring the accuracy and reliability of the collected data and providing strong support for subsequent decision-making.

[0022] Based on the LoRa+4G hybrid networking architecture and star network topology, coupled with automatic networking, self-healing after disconnection and multi-terminal concurrent communication design, the anti-interference capability and coverage of communication are improved, ensuring the continuity and stability of data transmission in complex industrial environments.

[0023] With its multi-dimensional alarm mechanism and remote intelligent operation and maintenance function, it comprehensively covers various abnormal scenarios in equipment operation, supports remote parameter configuration, equipment control and status query, and can quickly respond to faults without on-site supervision, thereby improving operation and maintenance efficiency and management flexibility.

[0024] By standardizing hardware interfaces, communication protocols, and equipment structure design, and unifying terminal installation dimensions and configuration methods, it is easy to quickly replace and expand equipment on-site, thereby enhancing the maintainability and adaptability of the system. Attached Figure Description

[0025] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0026] Figure 1 is a flowchart illustrating a non-intrusive smart IoT sensor controller according to the present invention; Figure 2 is a network communication topology diagram according to the present invention. Detailed Implementation

[0027] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0028] Please refer to Figures 1-2. A smart IoT non-intrusive sensor controller includes: a data acquisition unit, a data processing unit, a communication transmission unit, and a remote operation and maintenance control unit. The data acquisition unit acquires first pipeline data, second signal data, and third terminal data through a preset LoRa acquisition terminal. The data processing unit uses the first pipeline data, second signal data, and third terminal data to perform edge computing processing and filter the processing results through corresponding processors. Outliers are removed using the filtering results to obtain regularized data. Battery voltage and switching quantities are judged based on preset thresholds to obtain alarm indicators. The regularized data and alarm indicators are classified and cached to obtain standardized data frames. The communication transmission unit establishes a bidirectional communication connection through LoRa wireless technology and obtains the standardized data frames using modulation. The second signal data is transmitted synchronously to generate a network key-pump packet. Simultaneously, the terminal is powered on, and instruction information from the cloud platform is acquired synchronously. The remote operation and maintenance control unit adjusts corresponding data parameters based on the instruction information. Control instructions from the cloud platform are acquired using the alarm indicators, transmitted through the LoRa channel, driving relays to perform corresponding actions, and the device status is read in real time based on the regularized data.

[0029] As a preferred technical solution of the present invention, the specific process of performing edge computing processing and filtering the processing results by the corresponding processor includes: using the processor to call the built-in filtering algorithm to filter noise from the first pipeline data, the second signal data, and the third terminal data to obtain raw data segments that meet the threshold; and performing preliminary filtering operations on the temperature, pressure, and humidity data based on preset range and preset data interval filtering conditions for temperature, pressure, and humidity to obtain compliant data.

[0030] In this embodiment, the processor uses the ARM Cortex-M3 chip built into the LoRa+ 4G communication gateway. This chip has edge computing capabilities and can efficiently call the built-in filtering algorithm to perform data processing. A first-order low-pass filtering algorithm is used, and its formula is as follows: , where Xi is the currently collected raw data, Xi−1′ is the data after the previous filtering, α is the filtering coefficient (0<α<1, to adapt to the noise characteristics of industrial environment), and Xi′ is the data after noise filtering this time.

[0031] The first pipeline data includes pipeline surface temperature data collected by the temperature acquisition terminal using a PT100 sensor, and pipeline pressure data collected by the pressure acquisition terminal using a diffused silicon or ceramic piezoresistive pressure sensor. The second signal data consists of the on / off status of field devices collected by the IO control terminal. The third terminal data is the battery voltage monitoring data of each battery-powered terminal. These data are susceptible to noise interference in industrial environments, such as electromagnetic interference. A filtering algorithm can effectively remove irregular interference signals, retaining original data segments that meet normal fluctuation thresholds. Subsequently, based on the system's preset temperature, pressure, and temperature / humidity ranges, corresponding interval filtering conditions are set to perform preliminary filtering on the noise-filtered data, eliminating invalid data exceeding the preset ranges, and obtaining compliant data that meets actual monitoring requirements.

[0032] Specifically, the outlier removal using the screening results includes: extracting data based on the compliance data, comparing the extracted temperature, pressure, and humidity data with historical data to identify abrupt data points that deviate from the trend curve; verifying the abrupt data points using the standard deviation test, obtaining the verification results, and removing the abrupt data points as outliers.

[0033] In this embodiment, temperature, pressure, and humidity-related parameters are accurately extracted from the screened compliant data. The gateway's storage module stores historical data collected previously. The system compares the extracted data with historical data to analyze trends, patterns, and fluctuations, thereby identifying abrupt data points that deviate from the normal trend curve. To ensure the accuracy of anomaly detection, the standard deviation test is used to verify these abrupt data points. By calculating the data dispersion, it is determined whether the abrupt data points are within a reasonable statistical range. If the verification results indicate that the abrupt data point is not caused by actual operating condition changes but by abnormal interference, and exceeds the normal data fluctuation range, it is identified as an outlier and removed, ultimately forming accurate and reliable normalized data.

[0034] Specifically, the acquisition of the alarm identifier includes: based on the battery voltage value of the regularized data extraction terminal, comparing the battery voltage value with a preset low power threshold to generate a power alarm identifier; monitoring the switch status in the second signal data in real time, generating a switch change alarm identifier using contact change signal information and marking the change timestamp.

[0035] In this embodiment, after obtaining the regularized data, the system extracts the battery voltage values of each battery-powered terminal, including temperature acquisition terminals, pressure acquisition terminals, and temperature and humidity acquisition terminals, which are all built-in with high-capacity lithium thionyl chloride batteries and support battery voltage monitoring. The extracted battery voltage values are compared with the low battery threshold preset by the system in real time. When the voltage value is lower than the threshold, the system automatically generates a battery power alarm flag to remind the operation and maintenance personnel to replace the battery in time. At the same time, the system continuously monitors the digital input status in the second signal data in real time. When the IO control terminal detects a change in any DI status, it captures the contact displacement signal information, immediately generates a digital input displacement alarm flag, and accurately marks the time stamp of the displacement, providing an accurate time basis for subsequent fault troubleshooting and event tracing. For example: Battery power alarm: Vbat < Vth (generate a battery power alarm flag if it holds) Digital input displacement alarm: Si = S i−1 (generate a displacement alarm flag and mark the time stamp if it holds) Note: Vbat is the terminal battery voltage (obtained from the regularized data), Vth is the preset low battery threshold; Si is the current digital input status, and S i−1 is the digital input status in the previous cycle.

[0036] Specifically, the specific process of the classification cache includes: classifying the regularized data, combining the unique identifier of the corresponding device, and obtaining a classification data set; storing the classification data set, sorting it in a time-series storage manner, and obtaining a standardized data frame.

[0037] In this embodiment, the classification cache is a key link for the data processing unit to deliver standardized data to the communication transmission unit. The core is to achieve ordered, traceable storage and standardized encapsulation of data. After obtaining the regularized data after noise filtering and outlier removal, first, carry out refined classification processing according to the data type - split and classify the pipeline temperature data (collected by the temperature acquisition terminal through a PT100 sensor), pipeline pressure data (collected by the pressure acquisition terminal through a diffused silicon or ceramic piezoresistive pressure sensor), ambient temperature and humidity data (collected by the temperature and humidity acquisition terminal through an industrial-grade digital temperature and humidity integrated sensor), terminal battery voltage data (the self-power monitoring data of each battery-powered terminal), and device digital input data (the status data of field device start / stop, valve opening / closing, etc. collected by the IO control terminal) one by one, ensuring that different types of data do not interfere with each other and adapting to subsequent targeted transmission and application requirements.

[0038] All LoRa acquisition terminals and I / O control terminals are equipped with at least 8-bit hardware DIP switches, which can be manually configured to assign a unique device address. This address serves as the device's identifier throughout the data flow. During the classification process, each type of data is forcibly associated with the unique identifier of the corresponding acquisition device. For example, pipeline temperature data is bound to the DIP switch address of the temperature acquisition terminal, and device switch data is bound to the DIP switch address of the I / O control terminal. Through this one-to-one data-device association mechanism, it is ensured that any piece of data can be accurately traced back to its source acquisition terminal, providing a clear tracing basis for subsequent fault diagnosis and data verification, thereby forming multiple sets of classified datasets with clear structure and well-defined attribution.

[0039] After data classification, these classified datasets are stored in the built-in flash memory of the Lora+ 4G communication gateway. The gateway is equipped with 64KB or 128KB of flash memory, a storage specification designed to balance power consumption and storage requirements. This ensures that it meets the caching needs of organized data and alarm indicators within a certain period, without causing power redundancy due to excessively large storage modules, perfectly adapting to the dual requirements of low power consumption and data retention in industrial scenarios. The storage process strictly adopts a time-series storage method, using the timestamp of data acquisition as the sorting basis to arrange each set of classified datasets in an orderly manner.

[0040] Following a pre-defined unified data format, the sorted datasets of various categories are integrated and encapsulated to generate standardized data frames. The standardized data frame format is optimized through protocol design and includes core fields such as a unique device identifier, data type identifier, data collection timestamp, data value, and alarm flags. The field order and length are fixed to ensure efficient and error-free communication and parsing between the gateway, terminal, and cloud platform. This standardized encapsulation process not only unifies the data transmission format but also reduces the bit error rate during data transmission via the LoRa wireless channel.

[0041] Specifically, the process of establishing a two-way communication connection through LoRa wireless technology includes: configuring the communication parameters of the LoRa module and establishing a star network connection with the LoRa+4G gateway based on the format requirements of the standardized data frame; the gateway concurrently receiving the standardized data frames of the terminal through the LoRa downlink communication channel.

[0042] In this embodiment, the system adopts a star network topology architecture. This architecture uses a LoRa+4G communication gateway as the core central node, and various acquisition terminals such as temperature acquisition terminals, pressure acquisition terminals, temperature and humidity acquisition terminals, and IO control terminals as leaf nodes. Data interaction and command transmission are realized around the central node. This topology can maximize the centralized management and control capabilities of the gateway and adapt to the actual needs of distributed terminal deployment in industrial scenarios.

[0043] Before establishing a communication connection, the communication parameters of the LoRa modules of each acquisition terminal need to be precisely configured according to the standardized data frame format specifications and the transmission requirements of the industrial environment. Specifically, the transmit power can be flexibly adjusted via software, adapting to different power levels based on the distance between the terminal and the gateway, and on-site obstruction conditions, with the maximum transmit power sufficient for long-distance transmission. The modulation method uniformly adopts FSK / GFSK, which features strong anti-interference capabilities and high transmission efficiency, meeting the data transmission requirements of complex electromagnetic environments in industrial scenarios. Simultaneously, key parameters such as communication frequency, baud rate, and communication timeout need to be configured to ensure that the communication parameters of all terminals are consistent with the gateway LoRa module, laying the foundation for a stable connection later.

[0044] After the parameters are configured, the LoRa module of each acquisition terminal automatically starts and actively initiates a connection request with the LoRa+4G gateway based on the preset LoRa networking protocol. The terminal scans the surrounding LoRa signals, accurately identifies the networking signal emitted by the gateway, and establishes a bidirectional and stable star network connection with the gateway after verifying that the communication parameters match correctly.

[0045] The gateway's LoRa downlink communication channel has multi-terminal concurrent communication capabilities, enabling it to simultaneously receive standardized data frames sent by multiple acquisition terminals. Leveraging the parallel communication advantages of a star topology, each leaf node terminal can independently transmit data to the central gateway without waiting for other terminals to complete their transmissions. The gateway's built-in communication scheduling mechanism processes concurrently received data in an orderly manner, classifying and caching it according to the device's unique identifier, ensuring that each terminal's standardized data frames are received by the gateway quickly and accurately.

[0046] Specifically, the process of generating a heartbeat packet involves: extracting the status information from the second signal data and integrating the unique identifier, generating a data packet using a preset heartbeat packet format on the cloud platform, and sending the data packet at regular intervals.

[0047] In this embodiment, the gateway, as the core node for system data aggregation and communication interaction, needs to continuously report its own and associated terminal's operating status to the cloud platform to ensure the overall system monitorability. The gateway first accurately extracts key status information from the second signal data. This information includes the on / off status of field devices collected by the IO control terminal (such as the on / off status of pipeline valves, the start / stop status of actuators, etc.), as well as the connection status signals fed back by each terminal through the LoRa communication link. Simultaneously, the gateway integrates its own unique identifier (including gateway ID, hardware serial number, etc.) and the core information of each associated terminal (such as terminal device address, terminal type, and the timestamp of the most recent data report, etc.) to ensure that the heartbeat packet contains complete identity recognition and status traceability elements.

[0048] The gateway strictly adheres to the heartbeat packet format specifications pre-defined by the cloud platform, structurally encapsulating the extracted status information and integrated identification information. During encapsulation, data is organized according to a fixed field order: gateway identifier, project code, timestamp, number of online terminals, key device status, and communication link quality. Key device status is recorded in binary bit identifier form, and communication link quality includes parameters such as LoRa signal strength and 4G network signal quality, ensuring uniform data format, efficient parsing, and compliance with the standardized requirements for industrial IoT data transmission.

[0049] The gateway sends heartbeat packets at fixed time intervals preset by the system. These intervals can be flexibly adjusted via remote configuration commands issued by the cloud platform to adapt to the real-time monitoring requirements of different scenarios. During transmission, the gateway accesses the cellular network through its built-in 4G full-network module and transmits the encapsulated heartbeat packet to a designated port on the cloud platform. Upon receiving the heartbeat packet, the cloud platform extracts key information through protocol parsing, updates the gateway's online status and the stability of 4G and LoRa communication connections in real time, and simultaneously monitors the online status and core operating status of each associated terminal.

[0050] If the cloud platform does not receive a heartbeat packet from the gateway within a set time, it will automatically trigger an offline alarm mechanism to promptly remind maintenance personnel to investigate communication faults. Simultaneously, the terminal status information in the heartbeat packet allows for rapid location of offline terminals or abnormal devices, providing precise data for fault response. This timed heartbeat feedback mechanism constructs a continuous monitoring loop for the communication link.

[0051] Specifically, the power-on process of the terminal includes: reading the device address and network frequency band parameters preset by the hardware DIP switch; scanning the surrounding LoRa+4G gateway signals based on the preset LoRa networking protocol; initiating a bidirectional communication connection request; reporting standardized data frames based on the communication connection request result; and obtaining the terminal's network registration in the star network.

[0052] In this embodiment, all LoRa acquisition terminals and IO control terminals are equipped with at least an 8-bit hardware DIP switch. After power-on, the terminals automatically read the device address and network frequency band parameters preset by the DIP switch to complete their initial configuration. Subsequently, based on the preset LoRa networking protocol, the terminals initiate a signal scanning function to search for LoRa+4G gateway signals in the surrounding area. When a valid gateway signal is detected, the terminal initiates a bidirectional communication connection request to the gateway, simultaneously sending its own device address, parameter configuration, and other information to the gateway. The gateway verifies the received connection request and terminal information, and establishes a stable communication link after successful verification. Based on the successful communication connection request, the terminal immediately reports its first standardized data frame. After receiving and confirming the frame, the gateway enters the terminal information into the network node list, completing the terminal's network registration in the star network and enabling the terminal to officially access the system network.

[0053] Specifically, obtaining instruction information from the cloud platform includes: using a gateway to listen to instruction data packets issued by the cloud platform; parsing the instruction data packets to extract three types of instructions: remote configuration instructions, device control instructions, and gateway restart instructions, and then classifying and forwarding these three types of instructions.

[0054] In this embodiment, the Lora+4G gateway establishes a communication connection with the cloud platform through a 4G full-network compatible module, continuously monitoring the instruction data packets issued by the cloud platform. The gateway supports multiple protocols, and its built-in protocol parsing module can decrypt and parse the received instruction data packets, extracting the instruction content according to a preset protocol format. Based on the different functions of the instructions, the extracted instructions are divided into three categories: remote configuration instructions, device control instructions, and gateway restart instructions. Subsequently, according to the target object corresponding to the instruction, the gateway forwards the remote configuration instructions and device control instructions to the corresponding acquisition terminal or IO control terminal, and sends the gateway restart instruction to its own execution module, realizing remote management and control of the terminal devices and the gateway by the cloud platform.

[0055] Specifically, the process of adjusting the corresponding data parameters includes: adjusting the data acquisition cycle using the remote configuration command, and updating the terminal's acquisition frequency parameters; modifying the gateway's configuration parameters based on the remote configuration command and restarting the gateway communication module.

[0056] In this embodiment, when temperature acquisition terminals, pressure acquisition terminals, and temperature and humidity acquisition terminals receive remote configuration commands from the cloud platform, if the command involves adjusting the data acquisition cycle, the terminals immediately modify their own acquisition cycle parameters according to the command requirements, and simultaneously update the data reporting frequency to ensure that the acquisition and reporting rhythms are consistent. The default acquisition cycle of the terminals can be flexibly configured according to the command. For the gateway, when it receives a remote configuration command involving the modification of its own configuration parameters, the gateway main control module modifies the corresponding configuration parameters according to the command content, including key parameters such as 4G APN, server address / port, and heartbeat cycle. After the parameter modification is completed, the gateway automatically restarts the communication module to make the new configuration parameters take effect, realizing remote and flexible adjustment of system configuration.

[0057] Specifically, obtaining the control commands from the cloud platform includes: generating control commands based on the alarm identifier, converting the control commands into a command format supported by the LoRa protocol, and labeling the device address of the target IO control terminal.

[0058] In this embodiment, after the system generates a power alarm flag or a switch change alarm flag, the cloud platform automatically generates corresponding control commands based on the anomaly type and specific circumstances corresponding to the alarm flag. Examples include shutdown control commands for abnormal equipment states and valve switch adjustment commands. To ensure that control commands can be transmitted normally in the LoRa communication network, the cloud platform converts the generated control commands into a LoRa-supported command format and performs standardized encoding. All IO control terminals are configured with a unique LoRa address via hardware DIP switches. The converted control commands clearly indicate the device address of the target IO control terminal, ensuring that the commands can accurately locate the terminal device that needs to perform the control operation, avoiding mis-sending or mis-execution of commands.

[0059] Specifically, the real-time reading of device status includes: acquiring device status data through a local interface and an Ethernet port; and retrieving the terminal's collected data, IO port status, and alarm records using the cached regularized data to obtain real-time device status records.

[0060] In this embodiment, maintenance personnel can read the device status in real time through two methods. The first method is to obtain data through the gateway's local interface or Ethernet port. The gateway is equipped with one RS485 local interface and one 10 / 100M adaptive Ethernet port. Maintenance personnel can connect to local instruments via the RS485 interface or connect to the device via the Ethernet port using the Modbus TCP protocol to directly obtain real-time status data of the gateway and each data acquisition terminal, including communication status, operating status, and hardware working status. The second method utilizes the standardized data cached by the gateway. The gateway's storage module caches various types of standardized data. Maintenance personnel can retrieve historical data collected by each data acquisition terminal, port status information of the IO control terminal, and past alarm records through system commands. The real-time acquired status data is then integrated and analyzed with the retrieved cached data to form a complete real-time device status record.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A smart Internet of Things non-intrusive sensor controller, characterized in that, include: The system comprises a data acquisition unit, a data processing unit, a communication transmission unit, and a remote operation and maintenance control unit. The data acquisition unit acquires first pipeline data, second signal data, and third terminal data through a preset LoRa acquisition terminal. The data processing unit uses the first pipeline data, second signal data, and third terminal data to perform edge computing processing through corresponding processors and filters the processing results. The filtering results are used to remove outliers and obtain regularized data. The battery voltage and switch input are judged based on preset thresholds to obtain alarm indicators; Based on the regularized data and the alarm identifier, the data is classified and cached to obtain a standardized data frame; the communication transmission unit establishes a two-way communication connection through LoRa wireless technology and obtains the standardized data frame using a modulation method. The second signal data is transmitted synchronously to generate a network key-trip packet; at the same time, the terminal is powered on and the instruction information of the cloud platform is acquired synchronously; the remote operation and maintenance control unit adjusts the corresponding data parameters based on the instruction information; the control instructions of the cloud platform are acquired using the alarm identifier, transmitted through the LoRa channel, drive the relay to perform corresponding actions, and read the device status in real time based on the regularized data.

2. The system according to claim 1, characterized in that, The specific process of edge computing processing and filtering the results by the corresponding processor includes: using the processor to call the built-in filtering algorithm to filter noise from the first pipeline data, the second signal data, and the third terminal data to obtain raw data segments that meet the threshold; and performing preliminary filtering operations on the temperature, pressure, and humidity data based on preset range and preset data interval filtering conditions for temperature, pressure, and humidity to obtain compliant data.

3. The system according to claim 1, characterized in that, The outlier removal process using the screening results includes: extracting data based on the compliance data; comparing the extracted temperature, pressure, and humidity data with historical data to identify abrupt data points that deviate from the trend curve; verifying the abrupt data points using the standard deviation test; obtaining the verification results; and removing the abrupt data points as outliers.

4. The system according to claim 1, characterized in that, The process of obtaining the alarm identifier includes: extracting the battery voltage value from the regularized data extraction terminal, comparing the battery voltage value with a preset low power threshold, and generating a power alarm identifier; monitoring the switch status in the second signal data in real time, generating a switch change alarm identifier using contact change signal information, and marking the change timestamp.

5. The system according to claim 1, characterized in that, The specific process of the classification cache includes: classifying the regularized data, obtaining a classification dataset by combining the unique identifier of the corresponding device; storing the classification dataset, sorting it using a time-series storage method, and obtaining standardized data frames.

6. The system according to claim 1, characterized in that, The specific process of establishing a two-way communication connection through LoRa wireless technology includes: configuring the communication parameters of the LoRa module and establishing a star network connection with the LoRa+4G gateway based on the format requirements of the standardized data frame; the gateway concurrently receiving the standardized data frames of the terminal through the LoRa downlink communication channel.

7. The system according to claim 1, characterized in that, The process of generating a heartbeat packet involves extracting the status information from the second signal data and integrating the unique identifier, generating a data packet using a preset heartbeat packet format on the cloud platform, and sending the data packet at regular intervals.

8. The system according to claim 1, characterized in that, The terminal performs a power-on process, including: reading the device address and network frequency band parameters preset by the hardware DIP switch; scanning the surrounding LoRa+4G gateway signals based on the preset LoRa networking protocol; initiating a bidirectional communication connection request; reporting standardized data frames based on the communication connection request result; and obtaining the terminal's network registration in the star network.

9. The system according to claim 1, characterized in that, The process of obtaining instruction information from the cloud platform includes: using a gateway to listen for instruction data packets issued by the cloud platform; parsing the instruction data packets to extract three types of instructions: remote configuration instructions, device control instructions, and gateway restart instructions; and classifying and forwarding the three types of instructions.

10. The system according to claim 1, characterized in that, The specific process of adjusting the corresponding data parameters includes: adjusting the data acquisition cycle using the remote configuration command, and updating the terminal's acquisition frequency parameters; modifying the gateway's configuration parameters based on the remote configuration command and restarting the gateway communication module.

11. The system according to claim 1, characterized in that, The process of obtaining control commands from the cloud platform includes: generating control commands based on the alarm identifier, converting the control commands into a command format supported by the LoRa protocol, and labeling the device address of the target IO control terminal.

12. The system according to claim 1, characterized in that, The real-time reading of device status includes: acquiring device status data through a local interface and an Ethernet port; and retrieving the terminal's collected data, IO port status, and alarm records using the cached regularized data to obtain real-time device status records.

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