Yellow river ecology real-time monitoring method based on Internet of Things multi-sensor fusion

Abstract

The invention belongs to the technical field of Yellow River ecology real-time monitoring, and discloses a Yellow River ecology real-time monitoring method based on Internet of Things multi-sensor fusion. The method comprises the following specific use steps: S1, early-stage investigation and planning; S2, equipment type selection and purchase; S3, equipment installation and debugging; S4, data acquisition and transmission; according to the invention, through early-stage investigation and planning, the information of the monitoring area can be accurately mastered, the target is defined, the point location is reasonably planned, and the representativeness and comprehensiveness of monitoring data are guaranteed; equipment model selection and purchase are scientific and reasonable, model selection of water temperature, human body and soil sensors, high-definition cameras and the like is adaptive to a complex environment, and accurate data acquisition is ensured; the installation and debugging steps of the equipment are meticulous, and normal operation and data accuracy of the equipment are guaranteed from preparation to installation, electrification and debugging; and data acquisition and transmission are safe and efficient.

Description

Technical Field

[0001] The present invention belongs to the technical field of real-time monitoring of the Yellow River ecology, and specifically provides a real-time monitoring method of the Yellow River ecology based on multi-sensor fusion of the Internet of Things. Background Art

[0002] The real-time Yellow River ecological monitoring method based on IoT multi-sensor fusion utilizes IoT and multi-sensor fusion technologies to conduct real-time, dynamic, and comprehensive monitoring of the Yellow River's ecological environment. Existing IoT multi-sensor fusion real-time Yellow River ecological monitoring methods have significant problems in use. At the data level, sensor accuracy and stability vary, and low-cost sensors are prone to deviation in the complex environment of the Yellow River. Data is affected by electromagnetic interference and natural noise, resulting in distorted fused data. Data fusion algorithms lack adaptability and are difficult to adapt to the specific and complex environment of the Yellow River. Furthermore, data correlation is improperly handled, affecting comprehensive assessments. At the system level, sensors operating in the field for long periods of time are prone to failure, making maintenance difficult and costly. Communication network coverage is inadequate and susceptible to natural disasters, disrupting data transmission. System scalability is limited, making it difficult to integrate new sensors. Data formats and protocols vary significantly between sensor manufacturers, increasing system complexity and the risk of failure. At the application level, the selection of monitoring indicators is irrational, with an overemphasis on certain indicators, resulting in incomplete assessments. The lack of scientific basis for indicator weightings affects assessment results. Data visualization is poor, making it difficult to meet the needs of diverse users. Most importantly, the monitoring system's decision-making support capabilities are limited. It only provides raw data and simple analysis, lacks in-depth mining and intelligent analysis. When faced with ecological emergencies in the Yellow River, it is unable to provide effective response measures and suggestions in a timely manner, making it difficult to provide strong support for the ecological protection and management of the Yellow River. Summary of the Invention

[0003] The purpose of the present invention is to provide a real-time monitoring method for the Yellow River ecology based on multi-sensor fusion of the Internet of Things to solve the problems raised in the above background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things. The specific steps of the method are as follows: S1: Preliminary Research and Planning: Organize professionals to conduct on-site inspections of the Yellow River Basin monitoring area to understand topographical, hydrological, soil, and human activity information, communicate and clarify monitoring objectives, and accordingly plan sensor and camera installation locations; S2: Equipment selection and procurement: Choose high-precision, waterproof and corrosion-resistant water temperature sensors; select appropriate human body sensors based on the region; select multi-parameter, anti-interference soil sensors; use high-definition night vision cameras; purchase supporting equipment to ensure compatibility and stability; S3: Equipment installation and commissioning: Prepare tools and materials according to the instructions and complete basic construction; install and commission each device to ensure that sensors such as water temperature can collect data normally, cameras can capture images clearly, and parameters are calibrated to ensure data accuracy; Installation preparation: Prepare the tools and materials required for installation according to the equipment installation manual; perform foundation construction at the installation site, build the installation bracket, and lay power cables and communication cables; S4: Data collection and transmission: Each device collects data according to the set rules, transmits it to the IoT gateway for processing and packaging, and then securely transmits it to the cloud server after encryption; S5: Data processing and analysis: After receiving data, the cloud server performs pre-processing, denoising and filtering, integrates and analyzes multi-source data, and then uses methods to model and predict, explore ecological problems and patterns, and assist in the ecological monitoring of the Yellow River. S6: Real-time monitoring and early warning: Develop or use an existing platform to visually display Yellow River monitoring data; establish early warning rules, and when triggered, issue warning information through multiple channels to help relevant personnel quickly take countermeasures; S7: System maintenance and optimization: Develop inspection plans to maintain equipment, establish data backup and storage mechanisms to prevent data loss, upgrade the system based on development, update firmware, optimize algorithms, and improve the interface to ensure efficient and accurate monitoring.

[0005] Preferably, the specific steps of the preliminary investigation and planning in S1 are as follows: Step 1: Ecological survey: Organize professionals to conduct on-site inspections of the Yellow River Basin monitoring area to understand local topography, hydrological characteristics, soil types, and patterns of human activity; Step 2: Demand Analysis: Communicate with relevant departments and scientific research institutions related to Yellow River ecological protection to clarify monitoring objectives, water quality trends, the impact of human activities on the ecology, and soil health conditions; determine the accuracy, measurement range and other parameter requirements of each sensor based on the needs; Step 3: Site planning: Based on the survey results and monitoring needs, plan the installation locations of sensors and cameras; set up monitoring points in areas where water quality is easily polluted, where there is frequent human activity, and where soil properties change significantly to ensure that the monitoring data is representative and comprehensive.

[0006] Preferably, the equipment selection and procurement in S2 refers to the selection of sensors. The water temperature sensor must have high precision and high stability, and the measurement range must cover the common water temperature range of the Yellow River. It must be waterproof and anti-corrosion, and adaptable to complex water quality environments. The human body sensor should select infrared or microwave sensors based on the size of the monitoring area and the characteristics of personnel activities to ensure appropriate detection range and sensitivity and accurately detect the flow of personnel. The soil sensor must be able to measure multiple parameters such as soil temperature, humidity, and pH at the same time, and have strong anti-interference and good stability. The camera should be high-definition, low-light, wide dynamic range, and have night vision and remote zoom and rotation functions to ensure clear monitoring under different lighting conditions.

[0007] Preferably, the specific steps of equipment installation and debugging in S3 are as follows: Step 1: Installation preparation; Prepare all the necessary tools and materials for installation in advance, including wrenches, screwdrivers, cables, and cable ties, according to the equipment installation manual. Go to the installation site to carry out basic construction, build a stable mounting bracket, lay power cables and communication cables appropriately, and secure and protect the cables to ensure line safety and facilitate subsequent maintenance. Step 2: Equipment installation; Water temperature sensor installation: Carefully place the water temperature sensor in a suitable location in the water, ensuring it is fully submerged and in full contact with the water. Avoid areas with turbulent water flow and locations prone to damage, and secure it with a fixing device. Human body sensor installation: According to the monitoring range and angle requirements, install the human body sensor at a high or appropriate location in the human activity area, including corners and lampposts; after installation, adjust the detection direction and angle of the sensor to ensure that it can accurately cover the monitoring area; Soil sensor installation: Insert the soil sensor vertically into the soil according to the specified depth and spacing, and avoid shaking during the insertion process; Real-time camera installation: Install the camera and adjust its angle and focal length, and observe the real-time image to ensure that the camera can clearly monitor the target area; Step 3: Power on the device; After all equipment is installed, turn on the power, power each sensor and camera, and observe the status of the equipment indicator lights to confirm whether the equipment is powered on and started normally; Step 4: Equipment debugging; Use professional debugging software or platforms to debug each sensor and camera, check whether the sensor can collect data normally, check whether the image captured by the camera is clear and whether there is any obstruction or blur, calibrate the sensor and set parameters, adjust the measurement range and accuracy parameters according to actual conditions, and ensure the accuracy of the measurement data; if any problems are found during the debugging process, investigate and resolve them in a timely manner.

[0008] Preferably, the specific steps of data collection and transmission in S4 are as follows: Step 1: Set collection rules; Data collection rules are set for each sensor and camera based on monitoring needs. The water temperature sensor is set to collect water temperature data every hour at a fixed time interval. The human body sensor is set to trigger conditions and immediately send data upon detecting human activity. The soil sensor measures soil parameters at specific times of the day according to a preset cycle. The real-time camera is set to capture snapshots at scheduled times or enable motion detection and snapshot functions based on monitoring priorities. Step 2: Data is aggregated to the gateway. After collecting data according to the set rules, each sensor and camera sends the data to the IoT gateway. The IoT gateway acts as a data aggregation center, preliminarily screening, classifying, and organizing the data received from different devices, removing obvious errors or invalid data, and packaging the data in a unified format for subsequent transmission. Step 3: Securely transmit to the cloud; After the IoT gateway completes the initial data processing and packaging, it selects the appropriate communication method based on the on-site network conditions, including wireless; 4G / 5G, LoRa; network or wired fiber optic network, to transmit the data to the cloud server; during the data transmission process, encryption technology is used to encrypt the data to ensure that the data is not stolen or tampered with during the transmission process, thereby ensuring the security and confidentiality of the data.

[0009] Preferably, the data processing and analysis in S5 refers to the data preprocessing after the cloud server receives the data, removing outliers and interference signals through denoising, filtering, and normalization operations, such as smoothing the water temperature data to eliminate short-term fluctuations and improve data quality; then multi-sensor data fusion is carried out, and algorithms are used to integrate multi-source data such as water temperature, human activity, soil parameters and video surveillance. Among them, the impact of human activities on the water temperature of the Yellow River is analyzed by combining water temperature and personnel activity data; soil parameters are associated with surrounding environment video information to evaluate the relationship between soil conditions and ecological changes; finally, data analysis and mining are carried out, and with the help of statistical analysis, machine learning and other methods, a model is established to predict changes in water quality, human activity patterns and soil health status, and to explore potential ecological problems and laws.

[0010] Preferably, the specific steps of real-time monitoring and early warning in S6 are as follows: Step 1: Build a display platform and present data in real time; Develop or select a suitable IoT monitoring platform to display processed and analyzed data in intuitive forms such as charts, maps, and videos. Monitoring personnel can use computers and mobile phones to view water temperature, soil conditions, personnel flow, and monitoring footage at each monitoring point in the Yellow River in real time. Step 2: Set up warning rules on the platform; On the monitoring platform, safety thresholds and warning rules are set for various data based on the ecological monitoring needs of the Yellow River. These include safe ranges for water temperature and soil pH, as well as the reasonable frequency and behavior patterns of human activities. Once data exceeds the set limits, the system automatically triggers an alert. Step 3: Trigger an alert and release information; When the warning rules are triggered, the system quickly sends warning information to relevant personnel through SMS, email, APP, and push channels. The information covers the warning type, level, occurrence time, location and possible impact, facilitating timely response.

[0011] Preferably, the specific steps of system maintenance and optimization in S7 are as follows: Step 1: Plan equipment inspection; Develop a detailed regular equipment inspection plan, clearly define the inspection cycle, inspection personnel, and responsibilities; arrange for professional personnel to visit various monitoring points on the Yellow River as planned to conduct comprehensive inspections and maintenance of the equipment; Step 2: Perform equipment inspection and maintenance; After arriving at the monitoring point, professionals will carefully check the operating status of the equipment, check whether the appearance is damaged, check whether the connection parts are loose, and replace any damaged parts in time to ensure the normal operation of the equipment; Step 3: Implement data management; Establish a comprehensive data backup and storage mechanism, assign dedicated personnel to regularly back up monitoring data on cloud servers to prevent data loss; reasonably set storage periods based on data importance and frequency of use, and classify and store historical data; Step 4: Promote system upgrade and optimization; Pay attention to changes in IoT technology and monitoring needs, and regularly upgrade and optimize the monitoring system; update sensor and camera firmware programs to improve equipment performance and functions; optimize data processing and analysis algorithms to improve system operation efficiency and monitoring accuracy.

[0012] The beneficial effects of the present invention are as follows: 1. Through preliminary research and planning, the present invention can accurately grasp the information of the monitoring area, clarify the goals, reasonably plan the points, and ensure the representativeness and comprehensiveness of the monitoring data; the equipment selection and procurement are scientific and reasonable, and the water temperature, human body, soil sensors and high-definition cameras are selected to adapt to complex environments to ensure accurate data collection; the equipment installation and debugging steps are meticulous, from preparation to installation, power on, and debugging to ensure the normal operation of the equipment and data accuracy; data collection and transmission are safe and efficient, and data is collected, packaged, and encrypted and transmitted according to rules to ensure data integrity and security; data processing and analysis deeply explore ecological problems and laws, providing strong support for monitoring; real-time monitoring and early warning help relevant personnel respond quickly through intuitive display of data and timely early warning; system maintenance and optimization ensure the long-term stable operation of the system, and continuously improve monitoring efficiency and accuracy through inspections, data backup, upgrades and optimizations, and other measures to provide solid technical support for the ecological protection of the Yellow River.

[0013] 2. In terms of data collection and transmission, the present invention sets collection rules as needed to ensure the pertinence and timeliness of data; the gateway preliminarily processes the data and encapsulates it to ensure data standardization; encrypted transmission ensures data security; in the data processing and analysis stage, pre-processing is first used to improve data quality, and then multi-source data is integrated to mine associations, and finally ecological changes are predicted with the help of models to provide a scientific basis for decision-making; in real-time monitoring and early warning, a platform is built to intuitively display data for real-time viewing; early warning rules are set, and data anomalies automatically trigger early warnings, and relevant personnel are notified in a timely manner through various means to facilitate rapid response; in terms of system maintenance and optimization, inspections are planned to ensure the normal operation of equipment; inspections and maintenance are carried out to promptly handle faults; data management is implemented to prevent data loss; upgrades and optimizations are promoted to improve system performance and monitoring accuracy; this method comprehensively, efficiently and accurately realizes real-time monitoring of the Yellow River ecology, which helps to promptly discover ecological problems and take measures, providing strong support for the ecological protection of the Yellow River. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 Schematic diagram of the overall use of the detection method of the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] like Figure 1 As shown, the embodiment of the present invention provides a method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things. The specific steps of using this method are as follows: S1: Preliminary Research and Planning: Organize professionals to conduct on-site inspections of the Yellow River Basin monitoring area to understand topographical, hydrological, soil, and human activity information, communicate and clarify monitoring objectives, and accordingly plan sensor and camera installation locations; S2: Equipment selection and procurement: Choose high-precision, waterproof and corrosion-resistant water temperature sensors; select appropriate human body sensors based on the region; select multi-parameter, anti-interference soil sensors; use high-definition night vision cameras; purchase supporting equipment to ensure compatibility and stability; S3: Equipment installation and commissioning: Prepare tools and materials according to the instructions and complete basic construction. Install and commission all equipment to ensure that water temperature sensors and other sensors are collecting data normally, cameras are capturing images clearly, and parameters are calibrated to ensure data accuracy. Installation preparation: Prepare the necessary tools and materials according to the equipment installation manual. Perform basic construction at the installation site, such as setting up mounting brackets and laying power and communication cables.

[0017] S4: Data collection and transmission: Each device collects data according to the set rules, transmits it to the IoT gateway for processing and packaging, and then securely transmits it to the cloud server after encryption; S5: Data processing and analysis: After receiving data, the cloud server performs pre-processing, denoising and filtering, integrates and analyzes multi-source data, and then uses methods to model and predict, explore ecological problems and patterns, and assist in the ecological monitoring of the Yellow River. S6: Real-time monitoring and early warning: Develop or use an existing platform to visually display Yellow River monitoring data; establish early warning rules, and when triggered, issue warning information through multiple channels to help relevant personnel quickly take countermeasures; S7: System maintenance and optimization: Develop inspection plans to maintain equipment, establish data backup and storage mechanisms to prevent data loss, upgrade the system based on development, update firmware, optimize algorithms, and improve the interface to ensure efficient and accurate monitoring.

[0018] The specific steps of the preliminary investigation and planning in S1 are as follows: Step 1: Ecological survey: Organize professionals to conduct on-site inspections of the Yellow River basin monitoring area to understand local topography, hydrological characteristics, soil types, and patterns of human activity. For example, record the flow rate and riverbed depth of different sections of the Yellow River, the texture and fertility of the surrounding soil, and time periods and areas with intensive human activities.

[0019] Step 2: Demand Analysis: Communicate with relevant departments and scientific research institutions related to Yellow River ecological protection to clarify monitoring objectives, water quality trends, the impact of human activities on the ecology, and soil health conditions; determine the accuracy, measurement range and other parameter requirements of each sensor based on the needs; Step 3: Site planning: Based on the survey results and monitoring needs, plan the installation locations of sensors and cameras; set up monitoring points in areas where water quality is easily polluted, where there is frequent human activity, and where soil properties change significantly to ensure that the monitoring data is representative and comprehensive.

[0020] Among them, the equipment selection and procurement in S2 refers to the selection of sensors. The water temperature sensor must have high precision and high stability, with a measurement range covering the common water temperature range of the Yellow River, and be waterproof and corrosion-resistant to adapt to complex water quality environments. The human body sensor should be selected based on the size of the monitoring area and the characteristics of human activities, such as infrared or microwave sensors, to ensure the appropriate detection range and sensitivity to accurately detect the flow of people. The soil sensor must be able to simultaneously measure multiple parameters such as soil temperature, humidity, and pH, and have strong anti-interference and good stability. The camera should be high-definition, low-light, wide dynamic range, and equipped with night vision and remote zoom and rotation functions to ensure clear monitoring under different lighting conditions. In addition, it is necessary to purchase supporting equipment such as IoT gateways and communication modules to ensure equipment compatibility and stability.

[0021] The specific steps for installing and debugging the equipment in S3 are as follows: Step 1: Installation preparation; Prepare all the necessary tools and materials for installation in advance, including wrenches, screwdrivers, cables, and cable ties, according to the equipment installation manual. Go to the installation site to carry out basic construction, build a stable mounting bracket, lay power cables and communication cables appropriately, and secure and protect the cables to ensure line safety and facilitate subsequent maintenance. Step 2: Equipment installation; Water temperature sensor installation: Carefully place the water temperature sensor in a suitable location in the water, ensuring it is fully submerged and in full contact with the water. Avoid areas with turbulent water flow and locations prone to damage, and secure it with a fixing device. Human body sensor installation: According to the monitoring range and angle requirements, install the human body sensor at a high or appropriate location in the human activity area, including corners and lampposts; after installation, adjust the detection direction and angle of the sensor to ensure that it can accurately cover the monitoring area; Soil sensor installation: Insert the soil sensor vertically into the soil at the specified depth and spacing. Avoid shaking during insertion to ensure close contact between the sensor and the soil to prevent air gaps from affecting measurement accuracy. Real-time camera installation: Install the camera and adjust its angle and focal length. Observe the real-time image to ensure that the camera can clearly monitor the target area. Connect the communication cable between the camera and the IoT gateway to ensure a secure connection. Step 3: Power on the device; After all equipment is installed, turn on the power to power the sensors and cameras. Observe the status of the device indicators to confirm whether the equipment is powered on normally. Step 4: Equipment debugging; Use professional debugging software or platforms to debug each sensor and camera, check whether the sensor can collect data normally, check whether the image captured by the camera is clear and whether there is any obstruction or blur, calibrate the sensor and set parameters, adjust the measurement range and accuracy parameters according to actual conditions, and ensure the accuracy of the measurement data; if any problems are found during the debugging process, investigate and resolve them in a timely manner.

[0022] During the preparatory stage for installation, tools and materials are prepared and the foundation is laid to ensure subsequent installation. During equipment installation, precise operation is performed based on the specific characteristics of each device. For example, water temperature sensors are positioned away from areas with turbulent water flow, human body sensors are adjusted at an angle, soil sensors ensure close contact with the soil, and cameras ensure clear monitoring to maximize device performance. After the device is powered on, observing the indicator lights allows for quick confirmation that the device is powered on. During equipment commissioning, specialized tools are used to check data acquisition and image quality, calibrate sensors, and set parameters to ensure accurate measurement data. Any problems should be promptly identified and resolved to ensure stable equipment operation and lay a solid foundation for subsequent monitoring work.

[0023] The specific steps for data collection and transmission in S4 are as follows: Step 1: Set collection rules; Data collection rules are set for each sensor and camera based on monitoring needs. The water temperature sensor is set to collect water temperature data every hour at a fixed time interval. The human body sensor is set to trigger conditions and immediately send data upon detecting human activity. The soil sensor measures soil parameters at specific times of the day according to a preset cycle. The real-time camera is set to capture snapshots at scheduled times or enable motion detection and snapshot functions based on monitoring priorities. Step 2: Data aggregation to the gateway; After collecting data according to set rules, each sensor and camera sends the data to the IoT gateway. The IoT gateway acts as a data aggregation center, preliminarily screening, classifying, and organizing the data received from different devices, removing obvious errors or invalid data, and packaging the data in a unified format for subsequent transmission. Step 3: Securely transmit to the cloud; After the IoT gateway completes the initial data processing and packaging, it selects the appropriate communication method based on the on-site network conditions, including wireless; 4G / 5G, LoRa; network or wired fiber optic network, to transmit the data to the cloud server; during the data transmission process, encryption technology is used to encrypt the data to ensure that the data is not stolen or tampered with during the transmission process, thereby ensuring the security and confidentiality of the data.

[0024] Setting collection rules can precisely adapt to different monitoring needs. Water temperature, human body, soil sensors, and cameras each perform their respective functions, efficiently acquiring targeted data. When data is aggregated to the gateway, preliminary processing of multi-source data is performed, removing erroneous and invalid data and packaging it in a unified format, improving data quality and transmission efficiency. When securely transmitting data to the cloud, the appropriate communication method is selected based on on-site conditions to ensure stable data transmission. Encryption technology is also used to safeguard data security and prevent theft and tampering during transmission. The overall process ensures accurate data collection, efficient and secure transmission, and facilitates the smooth implementation of monitoring work.

[0025] Among them, the data processing and analysis in S5 refers to the data preprocessing after the cloud server receives the data. Through denoising, filtering, and normalization operations, outliers and interference signals are removed, such as smoothing the water temperature data to eliminate short-term fluctuations and improve data quality; then multi-sensor data fusion is carried out, and algorithms are used to integrate multi-source data such as water temperature, human activity, soil parameters and video surveillance. Among them, the impact of human activities on the water temperature of the Yellow River is analyzed by combining water temperature and personnel activity data; soil parameters are correlated with surrounding environment video information to evaluate the relationship between soil conditions and ecological changes; finally, data analysis and mining are carried out, and with the help of statistical analysis, machine learning and other methods, a model is established to predict changes in water quality, human activity patterns and soil health status, and to explore potential ecological problems and laws.

[0026] During data preprocessing, operations such as denoising, filtering, and normalization effectively remove outliers and interference signals, improving data quality and laying a solid foundation for subsequent analysis. Multi-sensor data fusion integrates data from multiple sources, synthesizing diverse information. For example, combining water temperature with human activity data, and correlating soil parameters with video information, allows for in-depth analysis of complex ecological relationships and uncovers more valuable information. Data analysis and mining leverage advanced methods to build models that accurately predict changes in water quality, human activity patterns, and soil health, identifying potential ecological issues and patterns in advance. This provides a scientific basis for the ecological protection and management of the Yellow River and contributes to more efficient ecological governance.

[0027] The specific steps of real-time monitoring and early warning in S6 are as follows: Step 1: Build a display platform and present data in real time; Develop or select a suitable IoT monitoring platform to display processed and analyzed data in intuitive forms such as charts, maps, and videos. Monitoring personnel can use computers and mobile phones to view water temperature, soil conditions, personnel flow, and monitoring footage at each monitoring point in the Yellow River in real time. Step 2: Set up warning rules on the platform; On the monitoring platform, safety thresholds and warning rules are set for various data based on the ecological monitoring needs of the Yellow River. These include safe ranges for water temperature and soil pH, as well as the reasonable frequency and behavior patterns of human activities. Once data exceeds the set limits, the system automatically triggers an alert. Step 3: Trigger an alert and release information; When the warning rules are triggered, the system quickly sends warning information to relevant personnel through SMS, email, APP, and push channels. The information covers the warning type, level, occurrence time, location, and possible impact, so that timely response can be made.

[0028] Establishing a display platform and presenting real-time data allows monitoring personnel to conveniently access key information from various Yellow River monitoring points via computers or mobile phones, breaking the constraints of time and space and providing timely insights into on-site dynamics. Setting early warning rules within the platform and setting safety thresholds based on the ecological needs of the Yellow River allows for early detection of anomalies, buying time for response. Once an alert is triggered and information is released, the system quickly notifies relevant personnel through multiple channels, providing comprehensive information that allows them to quickly understand the situation and determine the appropriate response direction. This series of steps forms a complete closed-loop system, effectively improving the timeliness, accuracy, and response capabilities of Yellow River ecological monitoring, thereby safeguarding the ecological safety of the Yellow River.

[0029] The specific steps of system maintenance and optimization in S7 are as follows: Step 1: Plan equipment inspection; Develop a detailed regular equipment inspection plan, clearly define the inspection cycle, inspection personnel, and responsibilities; arrange for professional personnel to visit various monitoring points on the Yellow River as planned to conduct comprehensive inspections and maintenance of the equipment; Step 2: Perform equipment inspection and maintenance; After arriving at the monitoring point, professionals will carefully check the operating status of the equipment, check whether the appearance is damaged, check whether the connection parts are loose, and replace any damaged parts in time to ensure the normal operation of the equipment; Step 3: Implement data management; Establish a comprehensive data backup and storage mechanism, assign dedicated personnel to regularly back up monitoring data on cloud servers to prevent data loss; reasonably set storage periods based on data importance and frequency of use, and classify and store historical data; Step 4: Promote system upgrade and optimization; Pay attention to changes in IoT technology and monitoring needs, and regularly upgrade and optimize the monitoring system; update sensor and camera firmware programs to improve equipment performance and functions; optimize data processing and analysis algorithms to improve system operation efficiency and monitoring accuracy; improve the monitoring platform interface design and functional modules based on user feedback to enhance user experience.

[0030] Planning equipment inspections allows for proactive planning, ensuring that professionals carry out their work in an orderly manner and promptly identifying potential equipment issues. Performing equipment inspections and maintenance ensures stable operation, reduces the likelihood of failures, and extends equipment lifespan. Implementing data management with comprehensive backup and storage mechanisms prevents data loss, while properly setting storage periods and categorizing data facilitates data access and analysis. Promoting system upgrades and optimizations keeps pace with technological developments, enhances equipment performance and functionality, and improves system efficiency and monitoring accuracy. Platform improvements based on user feedback enhance the user experience and facilitate efficient monitoring.

[0031] Implementation Background: To strengthen the monitoring and protection of the Yellow River's ecological environment, a research team decided to use a real-time monitoring method based on IoT multi-sensor fusion to conduct ecological monitoring in a monitoring area in the Yellow River basin.

[0032] Implementation steps: Preliminary research and planning: Organize professional personnel to conduct on-site inspections of the monitoring area to understand the terrain, hydrology, soil and human activity information.

[0033] Communicate with relevant departments for the ecological protection of the Yellow River to clarify monitoring objectives, such as water quality change trends and the impact of human activities on the ecology.

[0034] Plan the installation locations of sensors and cameras based on survey results and monitoring requirements.

[0035] Equipment selection and procurement: Choose high-precision, waterproof and corrosion-resistant water temperature sensors to ensure they can adapt to complex water quality environments.

[0036] Select appropriate human body sensors based on the size of the monitoring area and the characteristics of human activities.

[0037] Select multi-parameter, anti-interference soil sensors to measure soil temperature, humidity, pH, etc.

[0038] Purchase high-definition night vision cameras to ensure clear monitoring under different lighting conditions.

[0039] Equipment installation and debugging: According to the equipment installation instructions, prepare tools and materials, carry out basic construction, build installation brackets, and lay power cables and communication cables.

[0040] Install the water temperature sensor, ensuring it is completely submerged and in full contact with the water; install the human body sensor and adjust the detection direction and angle; install the soil sensor at the specified depth and spacing; install and debug the camera to ensure a clear image.

[0041] Turn on the power, observe the status of the device indicator light, and confirm that the device is powered on and started normally.

[0042] Use professional debugging software to debug each sensor and camera, calibrate parameters, and ensure data accuracy.

[0043] Data collection and transmission: Set data collection rules for each sensor and camera, such as the water temperature sensor collects data once an hour, and the human body sensor sends data immediately when it detects human activity.

[0044] After each device collects data according to the rules, it is sent to the IoT gateway for preliminary screening, classification and organization.

[0045] The IoT gateway selects the appropriate communication method based on the on-site network conditions to securely transmit data to the cloud server.

[0046] Data processing and analysis: The cloud server preprocesses the received data to remove outliers and interference signals.

[0047] Use algorithms to integrate multi-source data, analyze the impact of human activities on the water temperature of the Yellow River, and evaluate the relationship between soil conditions and ecological changes.

[0048] Statistical analysis, machine learning and other methods are used to build models to predict changes in water quality, human activity patterns and soil health.

[0049] Real-time monitoring and early warning: Develop or select a suitable IoT monitoring platform to display the processed and analyzed data in an intuitive form.

[0050] Set up early warning rules on the monitoring platform, such as specifying the safe range of water temperature and soil pH.

[0051] When the warning rule is triggered, the system sends warning information to relevant personnel via SMS, email, APP push, etc.

[0052] System maintenance and optimization: Develop a detailed regular equipment inspection plan and arrange professional personnel to inspect and maintain the equipment.

[0053] Establish a complete data backup and storage mechanism to prevent data loss.

[0054] Regularly upgrade and optimize the monitoring system, update sensor and camera firmware programs, and optimize data processing and analysis algorithms.

[0055] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0056] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things, characterized by: The specific steps of using this method are as follows: S1: Preliminary Research and Planning: Organize professionals to conduct on-site inspections of the Yellow River Basin monitoring area to understand topographical, hydrological, soil, and human activity information, communicate and clarify monitoring objectives, and accordingly plan sensor and camera installation locations; S2: Equipment selection and procurement: Choose high-precision, waterproof and corrosion-resistant water temperature sensors; select appropriate human body sensors based on the region; select multi-parameter, anti-interference soil sensors; use high-definition night vision cameras; purchase supporting equipment to ensure compatibility and stability; S3: Equipment installation and commissioning: Prepare tools and materials according to the instructions and complete basic construction; install and commission each device to ensure that the water temperature sensor can collect data normally and the camera can capture clear images. Calibrate parameters to ensure data accuracy. S4: Data collection and transmission: Each device collects data according to the set rules, transmits it to the IoT gateway for processing and packaging, and then securely transmits it to the cloud server after encryption; S5: Data processing and analysis: After receiving data, the cloud server performs pre-processing, denoising and filtering, integrates and analyzes multi-source data, and then uses methods to model and predict, explore ecological problems and patterns, and assist in the ecological monitoring of the Yellow River. S6: Real-time monitoring and early warning: Develop or use an existing platform to visually display Yellow River monitoring data; establish early warning rules, and when triggered, issue warning information through multiple channels to help relevant personnel quickly take countermeasures; S7: System maintenance and optimization: Develop inspection plans to maintain equipment, establish data backup and storage mechanisms to prevent data loss, upgrade the system based on development, update firmware, optimize algorithms, and improve the interface to ensure efficient and accurate monitoring.

2. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The specific steps of the preliminary investigation and planning in S1 are as follows: Step 1: Ecological survey: Organize professionals to conduct on-site inspections of the Yellow River Basin monitoring area to understand the local topography, hydrological characteristics, soil types, and human activity patterns; Step 2: Needs Analysis: Communicate with relevant departments and scientific research institutions related to Yellow River ecological protection to clarify monitoring objectives, water quality trends, the impact of human activities on the ecology, and soil health conditions; Determine the accuracy and measurement range parameter requirements of each sensor based on demand; Step 3: Location planning: Based on the survey results and monitoring requirements, plan the installation locations of sensors and cameras. Monitoring points are set up in areas where water quality is easily polluted, where there are frequent human activities, and where soil properties change significantly to ensure that the monitoring data is representative and comprehensive.

3. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The equipment selection and procurement in S2 refers to the selection of sensors. The water temperature sensor must have high precision and high stability, a measurement range covering the common water temperature range of the Yellow River, and be waterproof and corrosion-resistant to adapt to complex water quality environments. The human body sensor should be selected based on the size of the monitoring area and the characteristics of human activities. Infrared or microwave sensors should be selected to ensure appropriate detection range and sensitivity to accurately detect human movement. The soil sensor must be able to simultaneously measure soil temperature, humidity, pH and other parameters, and have strong anti-interference and good stability. The cameras are selected with high definition, low illumination, wide dynamic range, night vision, and remote zoom and rotation functions to ensure clear monitoring under different lighting conditions.

4. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The specific steps for equipment installation and debugging in S3 are as follows: Step 1: Installation preparation; Prepare all the necessary tools and materials for installation in advance, including wrenches, screwdrivers, cables, and cable ties, according to the equipment installation manual. Go to the installation site to carry out basic construction, build a stable mounting bracket, lay power cables and communication cables appropriately, and secure and protect the cables to ensure line safety and facilitate subsequent maintenance. Step 2: Equipment installation; Water temperature sensor installation: Carefully place the water temperature sensor in a suitable location in the water, ensuring it is fully submerged and in full contact with the water. Avoid areas with turbulent water flow and locations prone to damage, and secure it with a fixing device. Human body sensor installation: According to the monitoring range and angle requirements, install the human body sensor at a high or appropriate location in the human activity area, including corners and lampposts; after installation, adjust the detection direction and angle of the sensor to ensure that it can accurately cover the monitoring area; Soil sensor installation: Insert the soil sensor vertically into the soil according to the specified depth and spacing, and avoid shaking during the insertion process; Real-time camera installation: Install the camera and adjust its angle and focal length, and observe the real-time image to ensure that the camera can clearly monitor the target area; Step 3: Power on the device; After all equipment is installed, turn on the power, power each sensor and camera, and observe the status of the equipment indicator lights to confirm whether the equipment is powered on and started normally; Step 4: Equipment debugging; Use professional debugging software or platforms to debug each sensor and camera, check whether the sensor can collect data normally, check whether the image captured by the camera is clear and whether there is any obstruction or blur, calibrate the sensor and set parameters, and adjust the measurement range and accuracy parameters according to actual conditions to ensure the accuracy of the measurement data; If any problems are found during debugging, they should be promptly investigated and resolved.

5. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The specific steps for data collection and transmission in S4 are as follows: Step 1: Set collection rules; Data collection rules are set for each sensor and camera based on monitoring needs. The water temperature sensor is set to collect water temperature data every hour at a fixed time interval. The human body sensor is set to trigger conditions and immediately send data upon detecting human activity. The soil sensor measures soil parameters at specific times of the day according to a preset cycle. The real-time camera is set to capture snapshots at scheduled times or enable motion detection and snapshot functions based on monitoring priorities. Step 2: Data aggregation to the gateway; After collecting data according to set rules, each sensor and camera sends the data to the IoT gateway. The IoT gateway acts as a data aggregation center, preliminarily screening, classifying, and organizing the data received from different devices, removing obvious errors or invalid data, and packaging the data in a unified format for subsequent transmission. Step 3: Securely transmit to the cloud; After the IoT gateway completes the initial data processing and packaging, it selects the appropriate communication method based on the on-site network conditions, including wireless; 4G / 5G, LoRa; network or wired fiber optic network, to transmit the data to the cloud server; during the data transmission process, encryption technology is used to encrypt the data to ensure that the data is not stolen or tampered with during the transmission process, thereby ensuring the security and confidentiality of the data.

6. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The data processing and analysis in S5 refers to the data preprocessing performed after the cloud server receives the data. Through denoising, filtering, and normalization operations, outliers and interference signals are removed, such as smoothing water temperature data to eliminate short-term fluctuations and improve data quality; then multi-sensor data fusion is carried out, and algorithms are used to integrate multi-source data such as water temperature, human activity, soil parameters, and video surveillance. Among them, the impact of human activities on the water temperature of the Yellow River is analyzed by combining water temperature and human activity data; soil parameters are correlated with surrounding environmental video information to evaluate the relationship between soil conditions and ecological changes; finally, data analysis and mining are carried out, and with the help of statistical analysis and machine learning methods, a model is established to predict changes in water quality, human activity patterns, and soil health status, and to explore potential ecological problems and laws.

7. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The specific steps of real-time monitoring and early warning in S6 are as follows: Step 1: Build a display platform and present data in real time; Develop or select a suitable IoT monitoring platform to display processed and analyzed data in intuitive forms such as charts, maps, and videos. Monitoring personnel can use computers and mobile phones to view water temperature, soil conditions, personnel flow, and monitoring footage at each monitoring point in the Yellow River in real time. Step 2: Set up warning rules on the platform; On the monitoring platform, safety thresholds and warning rules are set for various data based on the ecological monitoring needs of the Yellow River. These include safe ranges for water temperature and soil pH, as well as the reasonable frequency and behavior patterns of human activities. Once data exceeds the set limits, the system automatically triggers an alert. Step 3: Trigger an alert and release information; When the warning rules are triggered, the system quickly sends warning information to relevant personnel through SMS, email, APP, and push channels. The information covers the warning type, level, occurrence time, location and possible impact, facilitating timely response.

8. The method for real-time monitoring of the Yellow River ecology based on multi-sensor fusion of the Internet of Things according to claim 1 is characterized by: The specific steps for system maintenance and optimization in S7 are as follows: Step 1: Plan equipment inspection; Develop a detailed regular equipment inspection plan, clearly define the inspection cycle, inspection personnel, and responsibilities; arrange for professional personnel to visit various monitoring points on the Yellow River as planned to conduct comprehensive inspections and maintenance of the equipment; Step 2: Perform equipment inspection and maintenance; After arriving at the monitoring point, professionals will carefully check the operating status of the equipment, check whether the appearance is damaged, check whether the connection parts are loose, and replace any damaged parts in time to ensure the normal operation of the equipment; Step 3: Implement data management; Establish a comprehensive data backup and storage mechanism and assign dedicated personnel to regularly back up monitoring data on the cloud server to prevent data loss; According to the importance and frequency of data use, the storage period should be reasonably set, and historical data should be classified, stored and managed; Step 4: Promote system upgrade and optimization; Pay attention to changes in IoT technology and monitoring needs, and regularly upgrade and optimize the monitoring system; update sensor and camera firmware programs to improve equipment performance and functions; optimize data processing and analysis algorithms to improve system operation efficiency and monitoring accuracy.

Images