A smart hydrological and water resources monitoring system based on the Internet of Things

Abstract

This invention discloses an intelligent hydrological and water resources monitoring system based on the Internet of Things (IoT), belonging to the field of hydrological and water resources monitoring technology. It includes an intelligent monitoring terminal, an edge computing gateway, and a cloud management platform. The intelligent monitoring terminal uses LoRa+NB-IoT dual-mode communication technology to achieve real-time and automatic acquisition of hydrological data across the entire watershed. A solar power unit meets its continuous operation needs in environments without mains power. The edge computing gateway performs local cleaning, threshold judgment, and compression processing on the acquired data, improving data accuracy and reducing network transmission costs. A breakpoint resume function ensures data integrity. The cloud management platform stores, classifies, and visualizes the data, allowing managers to intuitively grasp the hydrological and water resources status of the watershed. This system has the advantages of comprehensive monitoring coverage, real-time and accurate data, convenient deployment and maintenance, and timely early warning, providing reliable data support for water resources management decisions.

Description

Technical Field

[0001] This invention relates to the field of hydrological and water resources management technology, specifically to an intelligent hydrological and water resources monitoring system based on the Internet of Things. Background Technology

[0002] Currently, hydrological and water resource monitoring largely relies on manual inspections or fixed monitoring equipment at single points. This results in problems such as delayed data acquisition, limited coverage, and a lack of real-time data support for scheduling decisions, making it difficult to cope with sudden floods, droughts, and other water supply and demand imbalances. Furthermore, traditional monitoring systems are energy-intensive, difficult to deploy in remote areas without mains power, and cannot achieve intelligent management across the entire watershed, around the clock. Therefore, there is an urgent need for a system that can improve the intelligence and precision of hydrological and water resource management, providing technical support for the sustainable use of water resources. This system could be widely applied in areas such as watershed water resource management, intelligent irrigation in irrigation districts, and urban flood control and drainage. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides an intelligent hydrological and water resources monitoring system based on the Internet of Things.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solution: The present invention includes an intelligent monitoring terminal, an edge computing gateway, and a cloud management platform, which interact with each other through a wireless communication network, as detailed below: Intelligent monitoring terminal: Deployed at monitoring points in rivers, reservoirs, groundwater wells, and irrigated farmland within the watershed, it consists of a hydrological sensor array, a solar power supply unit, a positioning module, and a low-power communication module. The hydrological sensor array includes water level sensors, flow sensors, water quality sensors, and soil moisture sensors, used to comprehensively collect hydrological and water resource-related data from the monitoring points. The solar power supply unit uses monocrystalline silicon solar panels and lithium battery energy storage to meet the terminal's continuous operation needs in environments without mains power, reducing system energy consumption. The positioning module uploads the terminal's location information in real time to prevent theft or relocation and facilitate equipment management. The low-power communication module uses LoRa+NB-IoT dual-mode communication. In areas with good signal, NB-IoT is prioritized for high-frequency data transmission to ensure high data transmission efficiency, while LoRa is used for long-distance network transmission in remote mountainous areas to expand the monitoring coverage.

[0005] Edge computing gateway: Deployed as a relay station within the monitoring area, it is responsible for receiving data collected from various intelligent monitoring terminals and performing local edge computing processing. Its core functions include: data cleaning, eliminating abnormal data caused by sensor malfunctions to improve the accuracy of monitoring data; threshold judgment, immediately triggering local alerts when data such as water level, flow rate, and water quality exceed preset warning values, ensuring timely warnings; and data compression, compressing redundant data before uploading to the cloud to reduce network transmission costs. Simultaneously, the edge computing gateway has a breakpoint resume function; when the network is interrupted, it automatically stores the collected data and re-uploads it to the cloud after the network is restored, ensuring data integrity.

[0006] Cloud-based management platform: As the core data processing and display unit of the system, it is equipped with a hydrological data management system. The hydrological data management system stores, classifies, and visualizes the received monitoring data, generating real-time hydrological monitoring reports and historical trend curves, enabling managers to intuitively grasp the hydrological and water resource status within the basin.

[0007] The specific operation process of the above system is as follows: Terminal deployment: Within the target watershed, river water level and flow monitoring terminals are deployed at 1km intervals, reservoir capacity monitoring terminals are deployed on reservoir dams, soil moisture monitoring terminals are deployed in irrigated farmland, and groundwater level monitoring terminals are deployed in groundwater over-extraction areas. All terminals are connected to the edge computing gateway via LoRa networking.

[0008] Parameter configuration: Preset warning thresholds for each monitoring point on the cloud management platform, such as setting the river water level warning value to 3.5m and the water quality ammonia nitrogen content warning value to 1.0mg / L; import the regional weather forecast interface to provide a reference for comprehensive data analysis.

[0009] System Operation: The intelligent monitoring terminal collects data every 10 minutes, which is then cleaned and compressed by the edge computing gateway before being uploaded to the cloud. The cloud platform displays hydrological data in real time and generates real-time hydrological monitoring reports and historical trend curves. When the monitoring data exceeds the warning threshold, the edge computing gateway triggers a local warning, and the cloud platform sends an SMS warning to the management personnel.

[0010] Operation and maintenance management: Managers can remotely view the operating status of equipment through a cloud platform. When the terminal has insufficient power or communication failure, the system will automatically alarm, making it easier for operation and maintenance personnel to accurately locate the fault point for repair. Beneficial effects

[0011] This invention addresses the limitation of traditional monitoring methods by strategically deploying various intelligent monitoring terminals within the watershed and employing LoRa+NB-IoT dual-mode communication technology to collect hydrological and water resource data across the entire watershed. The intelligent monitoring terminals automatically collect data periodically, process it through an edge computing gateway, and promptly upload it to the cloud, resolving the issue of delayed data collection in traditional monitoring and ensuring that management personnel have timely access to hydrological and water resource conditions.

[0012] The data analysis capabilities of the edge computing gateway effectively filter out abnormal data, ensuring the accuracy and reliability of monitoring data and providing strong support for water resource management decisions. The intelligent monitoring terminal is powered by solar energy, reducing the system's dependence on mains power. The edge computing gateway design reduces network transmission costs, and administrators can remotely manage and maintain the system through a cloud platform. This makes it suitable for deployment in remote areas, reducing system deployment and maintenance costs.

[0013] The edge computing gateway's local threshold judgment combined with the cloud platform's early warning mechanism enables rapid response to abnormal hydrological and water resource conditions, buying time for subsequent emergency response. Detailed Implementation

[0014] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship shown in the specific embodiments, and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0016] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0017] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0018] This embodiment selects a mountainous watershed as the application scenario. The watershed has complex terrain and some areas are not covered by mains power. Traditional monitoring methods are difficult to achieve full coverage. The intelligent hydrological and water resources monitoring system of this invention is now deployed.

[0019] Terminal deployment: Along a 30km stretch of river within the basin, 30 river level and flow monitoring terminals will be deployed at 1km intervals; one reservoir capacity monitoring terminal will be deployed at each of the two small reservoir dams; 500 soil moisture monitoring terminals will be deployed at a density of one terminal per 100mu (6.7 hectares) of farmland in the 50,000 mu (3,333 hectares) irrigated area; and one groundwater level monitoring terminal will be deployed at each of the 15 groundwater over-extraction monitoring points. All terminals will be connected to the edge computing gateway deployed in the central township of the basin via LoRa networking.

[0020] Parameter configuration: Preset warning thresholds for each monitoring indicator on the cloud management platform, with the river water level warning value set at 3.0m, the ammonia nitrogen content warning value set at 1.0mg / L, the soil moisture warning value set at 12%, and the groundwater level warning value set at 10m; import the meteorological forecast interface of the meteorological department in the basin area to provide a reference for comprehensive data analysis.

[0021] Equipment debugging: All intelligent monitoring terminals were debugged to confirm that the data accuracy collected by the hydrological sensor group met industry standards, with the water level sensor error not exceeding ±0.01m and the flow sensor error not exceeding ±2%. The battery life of the solar power unit under continuous rainy weather was tested to ensure that the lithium battery energy storage could support the terminal's continuous operation for 7 days. The communication effect of the low-power communication module was verified. In rural areas with good signal, the terminal prioritized NB-IoT mode to transmit data, with a transmission delay of no more than 3 seconds. In remote mountainous areas, the terminal automatically switched to LoRa mode, which could achieve stable network transmission within a 5km range. The functionality of the edge computing gateway was tested, simulating sensor failure to generate abnormal data, which the gateway could successfully identify and remove. A network interruption of 1 hour was simulated, during which the gateway could store 6 sets of data collected during the period, and automatically re-upload them to the cloud after the network was restored.

[0022] System operation process Data Acquisition and Processing: The intelligent monitoring terminal continuously collects data every 10 minutes. The river water level and flow monitoring terminal simultaneously acquires river water level, flow data, and water quality-related indicators. The soil moisture monitoring terminal collects soil moisture data at a depth of 0-20cm in farmland. The groundwater level monitoring terminal records groundwater depth data. The collected data is transmitted to the edge computing gateway via LoRa networking. The gateway first cleans the data, removing three sets of abnormal water quality data caused by poor sensor contact. Then, the remaining valid data is compressed at a compression ratio of 1:5 to reduce network transmission pressure.

[0023] Data Upload and Display: The compressed data package is uploaded to the cloud management platform via the NB-IoT network. The cloud-based hydrological data management system categorizes and stores the data, generates hydrological monitoring reports by day, week, and month, and visualizes historical trend curves in the form of line charts, bar charts, etc. Managers can log in to the cloud platform via computer or mobile APP to view the current data of each monitoring point in real time, such as changes in river water level and flow, distribution of soil moisture in irrigation areas, and dynamic groundwater levels.

[0024] Early Warning Response and Operation & Maintenance Management: On the 15th day of system operation, a river level monitoring terminal in a remote mountainous area collected water level data of 3.2m, exceeding the preset warning value of 3.0m. The edge computing gateway immediately triggered a local audible and visual warning and simultaneously uploaded the warning information to the cloud platform. Within one minute, the cloud platform sent the warning via SMS to the mobile phones of three management personnel. The management personnel viewed the location information and real-time data changes of the monitoring point through the cloud platform, dispatched staff to the site for verification, and confirmed that the river level rise was caused by heavy rainfall. Temporary protective measures were promptly implemented. During system operation, the cloud platform monitored the equipment's operating status in real time. When a soil moisture monitoring terminal experienced insufficient power due to battery aging, the system automatically sent an alarm message. Based on the equipment location indicated by the platform, the management personnel accurately located the faulty terminal and replaced the battery, ensuring the continuous and stable operation of the system.

[0025] Application effect Since its launch six months ago, this system has achieved comprehensive and real-time monitoring of the hydrology and water resources of the mountainous watershed, increasing the monitoring coverage by 80% compared to traditional methods. The data acquisition cycle has been shortened to 10 minutes, solving the data lag problem caused by the monthly manual inspections of traditional methods. The local processing function of the edge computing gateway enables the data uploaded to the cloud to achieve an accuracy rate of 99.5%, providing a reliable basis for water resource management decisions. The application of solar power supply and LoRa networking technology avoids the high cost of laying lines in remote areas without mains power or network coverage, reducing the system deployment cost by 60% compared to traditional monitoring systems. Maintenance personnel can complete equipment status monitoring and fault diagnosis only through the cloud platform, improving maintenance efficiency by 70%.

[0026] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0027] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. An intelligent hydrological and water resources monitoring system based on the Internet of Things, characterized in that, It includes intelligent monitoring terminals, edge computing gateways, and cloud management platforms, which interact with each other through a wireless communication network.

2. The system according to claim 1, characterized in that, The intelligent monitoring terminal is deployed at monitoring points in rivers, reservoirs, groundwater wells, and irrigated farmland within the watershed. It consists of a hydrological sensor group, a solar power supply unit, a positioning module, and a low-power communication module. The hydrological sensor group includes a water level sensor, a flow sensor, a water quality sensor, and a soil moisture sensor. The water quality sensor is used to monitor pH value, dissolved oxygen, and ammonia nitrogen content. The solar power supply unit uses a monocrystalline silicon solar panel + lithium battery energy storage method. The low-power communication module adopts LoRa + NB-IoT dual-mode communication.

3. The system according to claim 1, characterized in that, The edge computing gateway is deployed as a relay station in the monitoring area and has functions such as data cleaning, threshold judgment, data compression, and breakpoint resume. The data cleaning is used to remove abnormal data caused by sensor failure. The threshold judgment is used to trigger local early warning when data such as water level, flow rate, and water quality exceed preset warning values. The data compression is used to compress redundant data before uploading it to the cloud.

4. The system according to claim 1, characterized in that, The cloud management platform is equipped with a hydrological data management system, which is used to store, classify and visualize the received monitoring data, and generate real-time hydrological monitoring reports and historical trend curves.

5. The system according to claim 1, characterized in that, The intelligent monitoring terminals are deployed as follows: river water level and flow monitoring terminals are deployed at 1km intervals within the target watershed; reservoir capacity monitoring terminals are deployed on the reservoir dam; soil moisture monitoring terminals are deployed in the irrigated farmland; and groundwater level monitoring terminals are deployed in the groundwater over-extraction area. All terminals are connected to the edge computing gateway via LoRa networking.

6. The system according to claim 1, characterized in that, The intelligent monitoring terminal collects data every 10 minutes, which is then cleaned and compressed by the edge computing gateway before being uploaded to the cloud. When the monitoring data exceeds the warning threshold, the edge computing gateway triggers a local warning, and the cloud platform sends an SMS warning to the management personnel.

7. The system according to claim 1, characterized in that, Administrators can remotely view the equipment's operating status through a cloud platform. The system will automatically alarm when the terminal experiences low power or communication failure.