Smart urban water affair early warning system and method integrating internet of things and internet

Abstract

The present invention relates to the field of water affair monitoring and early warning, and provides a smart urban water affair early warning system and method integrating the Internet of Things and the Internet, for solving the problems of existing urban water affair systems. The present invention comprises a sensing layer, a communication layer, a data layer and a decision-making layer. The sensing layer constructs, on the basis of the Internet of Things technology, an integrated sky-ground water conservancy Internet of Things sensing system covering water sources, pipeline tunnels, water plants, and river collection points, to collect multi-source data. The communication layer is used for sending to the data layer a large amount of multi-source data collected by the sensing layer. The data layer constructs, on the basis of the large amount of collected multi-source data, an urban water affair hydrological database, including a foundation database, a hydrological database, an engineering database, a water quality database, a management database and a remote sensing database. The decision-making layer is used for performing analysis and decision-making on the large number of multi-source data collected by the sensing layer, performing water quality prediction on all the collection points on the basis of each type of database, and when prediction results exceed a threshold, integrating a BIM platform and a GIS platform to display an alarm.

Description

An urban smart water affairs early warning system and method integrating the Internet of Things and the Internet Technical Field

[0001] The present invention relates to water affairs monitoring and early warning technology, and belongs to the intersection field of municipal engineering, environmental system simulation and prediction technology and computer technology. Background Art

[0002] Water is a fundamental natural resource and a strategic economic resource for cities, a crucial element in controlling their ecology and environment. Urban water management is not only the lifeblood of urban economic and social development, but also a crucial component in achieving sustainable urban development. With economic development and the acceleration of urbanization, the rational use of water resources has become an unavoidable and crucial issue in urban development. In the process of urbanization, water companies are also facing increasing challenges. The shortcomings of existing urban water management systems can be summarized as follows:

[0003] ① The existing water monitoring technology has many human factors, and the observation accuracy and reliability are difficult to guarantee. The observation efficiency is low, the station network density is insufficient, the monitoring frequency is low, and single-point collection is the main method. The means are single and passive, and it is impossible to fully, truly and accurately reflect the overall perception. The continuity, accuracy and stability of the data need to be further improved. The imperfect information perception system has caused the incompleteness of basic data and cannot meet the needs of business applications; ② Basic data such as river and lake systems, topography, water conservancy projects, and historical data are still in a paper-based and fragmented state, and a systematic and comprehensive digital database has not been established; ③ It has become the norm for water conservancy authorities and business departments at all levels to establish and independently operate single-level systems, resulting in the inability to fully share water conservancy big data information, easily forming information islands, which is extremely unfavorable for regional coordination and the role of decision-making systems.

[0004] Summary of the Invention

[0005] In response to the problems existing in the existing urban water system, the present invention provides an urban smart water early warning system and method that integrates the Internet of Things and the Internet.

[0006] One aspect of the present invention provides an urban smart water early warning system that integrates the Internet of Things and the Internet, including a perception layer, a communication layer, a data layer, and a decision-making layer;

[0007] The perception layer, based on IoT technology, builds an integrated sky-ground water conservancy IoT perception system covering water sources, pipe network tunnels, water plants, and river collection points. It utilizes pressure sensors, level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radar, and electronic identification equipment for precise pipeline positioning. Combined with drone oblique photography, satellite remote sensing imagery, and third-party data, it enables the collection of large amounts of multi-source data.

[0008] The communication layer is used to send the large amount of multi-source data collected by the perception layer to the data layer. Based on the basic communication network transmission environment of the Internet, local area network, and narrowband communication, it uses switching equipment, firewall network equipment, including application servers, database servers, model servers, and backup servers, and combines 2 / 3 / 4 / 5G network communications to build a comprehensive communication layer suitable for smart water services;

[0009] The data layer builds an urban water affairs and water situation database based on a large amount of multi-source data collected, including a basic database, a water situation database, a construction situation database, a water quality database, a management database, and a remote sensing database. The data layer is used to uniformly organize and manage data resources, achieve data standardization and unified expression, and provide support for data exchange, comprehensive application, and big data decision-making analysis.

[0010] The decision-making layer is used to analyze and make decisions on the large amount of multi-source data collected by the perception layer, and to predict water quality for all collection points based on each type of database. When the prediction result exceeds the limit, it combines the BIM platform (mainly providing engineering building geometry and attribute information) and the GIS platform (mainly providing macro-geographic information) to display an alarm.

[0011] Preferably, it also includes an application layer, which is the part directly facing users, to achieve unified organizational structure, user management and authority management, and to achieve integrated collaboration of various system layers within the portal framework through single sign-on, function integration and message integration.

[0012] Preferably, water sources include groundwater and reservoirs; pipeline tunnels include urban drainage pipelines, underpasses, key water plants, and key drainage households; water plants include: water plants and sewage treatment plant outlets; rivers include key river sections.

[0013] Preferably, the basic database stores the drainage network structure, river channel physical information, and monitoring equipment placement locations, wherein the river channel physical information includes width and length;

[0014] The water regime database stores information collected by level meters, flow meters, and pressure sensors;

[0015] The working situation database stores information collected by rain gauges and thermometers;

[0016] The water quality database stores information collected by online water quality monitoring equipment and pipeline robots;

[0017] The management database stores information collected by video surveillance;

[0018] The remote sensing database stores information collected by drone oblique photography and remote sensing satellites.

[0019] Another aspect of the present invention provides an urban smart water affairs early warning method integrating the Internet of Things and the Internet, which is implemented based on the urban smart water affairs early warning system integrating the Internet of Things and the Internet. The method includes:

[0020] S1. Deploy pressure sensors, level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radar, and electronic identification equipment for precise pipeline positioning at the sensing site. Combined with drone oblique photography, satellite remote sensing imagery, and third-party data, large amounts of multi-source data are collected and wirelessly transmitted to the data layer.

[0021] S2, build a basic database, water situation database, engineering situation database, water quality database, management database and remote sensing database based on the large amount of multi-source data collected in S1;

[0022] S3. Combine the BIM platform and GIS platform, use big data analysis, conduct early warning analysis based on big data and deep learning algorithms on the data of each type of database, obtain analysis results, and send the analysis results to the decision-making level;

[0023] S4. When the analysis result exceeds the warning indicator threshold, the platform will display it, give an alarm, and output the warning instruction to the collection point.

[0024] Preferably, after step S1, the following steps are performed:

[0025] In the preprocessing step, the data collected by the perception layer is optimized through multi-source data fusion derivation, feature engineering, or outlier missing value filling, and then the S2 database construction step is executed.

[0026] Preferably, the early warning indicator threshold is obtained by querying the surface water environment quality standard value table.

[0027] Beneficial effects of the present invention: The system of the present invention utilizes an integrated sky-ground water conservancy Internet of Things perception system, which can effectively cover key urban water affairs detection targets such as urban drainage pipe networks, underpasses, key river sections, groundwater, water plants, reservoirs, key water users, key drainage users, and sewage treatment plant outlets. Within the coverage area of ​​the system, problems such as water pollution and flood disasters can be perceived, analyzed, and warned, enabling response strategies to be taken as early as possible to prevent more serious consequences from being undetected in time. By utilizing different types of sensor equipment, full-process, automated, and real-time perception of urban water affairs information can be achieved, and various databases can be constructed for scientific research.

[0028] This invention overcomes the bottlenecks of traditional water monitoring technologies, which suffer from limited coverage and a lack of intelligent analysis and judgment capabilities, and fully addresses the needs of urban water emergency response. Leveraging IoT and internet technologies, through high-performance intelligent sensor components, wireless transmission networks, and signal acquisition systems, this system employs multi-parameter, multi-sensor components, intelligent data processing, and dynamic data management methods to build an economical, practical, efficient, and intelligent urban smart water emergency response system. This system enables multi-dimensional, three-dimensional perception and hazard warning for urban water services, and has significant practical significance for urban water governance.

[0029] The core invention effects of the present invention are mainly reflected in the following five points:

[0030] (1) A smart urban water emergency response system based on big data technology was proposed, which achieved real-time early warning of pollution risks and flood disasters in urban water systems, breaking through the bottleneck of traditional water monitoring technology with limited coverage and lack of intelligent analysis and judgment capabilities;

[0031] (2) An integrated air-ground water conservancy IoT sensing system was proposed. This system uses multiple types of real-time online monitoring equipment and combines remote sensing imagery and third-party data to achieve a "soft-hard integration" of soft technology and hardware equipment, thus realizing the automatic collection and wireless transmission of water conservancy monitoring data.

[0032] (3) The present invention divides the collected multi-source data into multiple basic databases through data integration, realizes data standardization and unified expression, and provides support for data exchange, comprehensive application, and big data decision analysis;

[0033] (4) The present invention uses a variety of machine learning data analysis methods to fully tap into data resources. Based on big data and deep learning algorithms, early warning analysis operations are performed to achieve optimal scheduling of water resources and emergency response.

[0034] (5) The present invention combines the BIM platform and the GIS platform to construct a multifunctional intelligent decision-making group, using "one map" to achieve full information coverage of urban water elements and support accurate and scientific decision-making of urban water systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is an architecture diagram of the urban smart water early warning system integrating the Internet of Things and the Internet according to the present invention;

[0036] FIG2 is a flowchart of the urban smart water early warning system integrating the Internet of Things and the Internet according to the present invention. DETAILED DESCRIPTION

[0037] 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 any creative efforts shall fall within the scope of protection of the present invention.

[0038] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other.

[0039] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0040] Specific embodiment 1: The following describes this embodiment with reference to FIG1 . This embodiment describes an urban smart water early warning system that integrates the Internet of Things and the Internet, including a perception layer, a communication layer, a data layer, a decision layer, and an application layer.

[0041] The perception layer, based on Internet of Things technology, builds an integrated sky-ground water conservancy Internet of Things perception system covering water sources, pipeline tunnels, water plants and river collection points. It uses pressure sensors, liquid level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radars, and pipeline precise positioning electronic identification equipment, combined with drone oblique photography, satellite remote sensing imagery and third-party data to realize the collection of large amounts of multi-source data; provide accurate and fast data support for the city's smart water emergency response system, and form a timely, comprehensive, accurate and stable intelligent online monitoring system.

[0042] Water sources include groundwater and reservoirs; pipeline tunnels include urban drainage pipelines, underpasses, key water plants, and key drainage households; water plants include: water plants and sewage treatment plant outlets; rivers include key river sections.

[0043] The communication layer is used to send the large amount of multi-source data collected by the perception layer to the data layer. Based on the basic communication network transmission environment of the Internet, local area network, and narrowband communication, it uses switching equipment, firewall network equipment, including application servers, database servers, model servers, and backup servers, and combines 2 / 3 / 4 / 5G network communications to build a comprehensive communication layer suitable for smart water services;

[0044] The data layer constructs an urban water affairs and water situation database based on a large amount of multi-source data collected, including a basic database, a water situation database, a construction situation database, a water quality database, a management database and a remote sensing database; the data layer is used for the unified organization and management of data resources, to achieve data standardization and unified expression, and to provide support for data exchange, comprehensive application, and big data decision-making analysis.

[0045] The basic database stores the drainage network structure, river channel physical information, and monitoring equipment placement locations. The river channel physical information includes width and length.

[0046] The water regime database stores information collected by level meters, flow meters, and pressure sensors;

[0047] The working situation database stores information collected by rain gauges and thermometers;

[0048] The water quality database stores information collected by online water quality monitoring equipment and pipeline robots;

[0049] The management database stores information collected by video surveillance;

[0050] The remote sensing database stores information collected by drone oblique photography and remote sensing satellites.

[0051] The decision-making layer is used to analyze and make decisions based on the large amount of multi-source data collected by the perception layer. It predicts water quality for all collection points based on each type of database. When the prediction result exceeds the limit, it combines the BIM platform and GIS platform to display an alarm.

[0052] Comprehensively use the Internet of Things, big data, and mobile application technologies to conduct preprocessing, quickly match the data required for analysis indicators, fully tap data resources, integrate massive information with big data technology, and optimize deep learning algorithms to achieve forecasts and early warnings of events such as floods, sewage overflows, and water environment pollution, forming a scientific and reasonable scheduling decision-making system and rapid emergency measures, providing decision makers with intelligent decision-making support, and improving decision-making levels and emergency response capabilities.

[0053] The application layer, which directly faces users, implements unified organizational structure, user management, and authority management, and realizes the integration and collaboration of various system layers within the portal framework through single sign-on, function integration, and message integration.

[0054] It can make full use of information at all levels of the urban smart water emergency response system, combine maps and visualization technologies to centrally provide information sharing and services, and realize a multi-dimensional and customizable comprehensive display system for user departments and the general public.

[0055] Specific embodiment 2: This embodiment is described below with reference to FIG2. The urban smart water affairs early warning method integrating the Internet of Things and the Internet described in this embodiment is implemented based on the urban smart water affairs early warning system integrating the Internet of Things and the Internet described in embodiment 1. The method includes:

[0056] S1. Deploy pressure sensors, level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radar, and electronic identification equipment for precise pipeline positioning at the sensing site. Combined with drone oblique photography, satellite remote sensing imagery, and third-party data, large amounts of multi-source data are collected and wirelessly transmitted to the data layer.

[0057] First perform the following steps:

[0058] In the preprocessing step, the data collected by the perception layer is optimized through multi-source data fusion derivation, feature engineering, or outlier missing value filling, and then the S2 database construction step is executed.

[0059] S2, build a basic database, water situation database, engineering situation database, water quality database, management database and remote sensing database based on the large amount of multi-source data collected in S1;

[0060] S3. Combine the BIM platform and GIS platform, use big data analysis, conduct early warning analysis based on big data and deep learning algorithms on the data of each type of database, obtain analysis results, and send the analysis results to the decision-making level;

[0061] S4. When the analysis result exceeds the warning indicator threshold, the platform will display it, give an alarm, and output the warning instruction to the collection point.

[0062] The threshold value of the early warning indicator is obtained from the surface water environmental quality standard numerical table.

[0063] Throughout the early warning analysis process, based on big data and deep learning algorithms, feedback from sensory layer monitoring and water system element control is collected. By optimizing the deep learning algorithm and integrating it with the established urban water resource database and hydrological forecast and warning information, the analysis results are continuously refined. Based on this early warning and forecast information, the decision-making layer simultaneously generates preliminary plans. After the proposals are proposed, multi-party consultations and discussions are held simultaneously. Three-dimensional scenario simulations are conducted on the plans after the consultations, and the optimal scheduling plan is finally selected. Remote automated control is then implemented to adjust the scheduling and emergency response of water resource elements within the control range of the urban smart water emergency response system, which integrates the Internet of Things and the internet.

[0064] Through unified information release, all types of information that need to be released can be released through multiple channels with one click, and the information of each application system can be fully utilized. Combined with maps and visualization technology, information sharing and services can be provided in a centralized manner, realizing a multi-dimensional and customizable comprehensive display system for user departments and the general public.

[0065] The following is an example. The system began development in March 2021 and is used to analyze and assess water quality issues in sections of Harbin New District, Heilongjiang Province. In response to potential risks in the local water environment, the Internet of Things and Internet technologies were applied to complete the development of various decision-making function modules, forming an emergency response system covering the entire process from intelligent perception to forecasting and early warning.

[0066] (1) Provide accurate and fast data support for the city's smart water emergency response system. Relying on the integrated sky-ground water conservancy Internet of Things perception system, it collects 18 types of industry big data in the fields of water environment emergency management and smart control, including geographic information data, map image data, land resource data, water environment data, meteorological data, hydrological data, pipe network data, sewage treatment plant data, and pump station data, to achieve multi-source data fusion and derivation;

[0067] (2) Conduct in-depth research and testing on river hydrology and water quality, water shorelines, sediment pollution, wetlands, and pollution sources. Based on comprehensive monitoring data collection, use drones to take aerial photos of the water environment in Harbin New Area. The scope includes six major water systems: Songhua River, Hulan River, Shengfa Canal, Yinshuiwan Branch Canal, Limin Fourth Drainage Canal, and Zhaolan New River.

[0068] (3) Develop a new water environment big data smart platform. The platform relies on HDFS technology to improve data access throughput; relies on HBase technology to improve massive data storage capabilities; and relies on Redis cache technology to improve online computing capabilities. It adopts the Hadoop big data distributed architecture and adopts a four-layer system architecture including data perception layer, data computing layer, data service layer, and data application layer. Compared with traditional big data architecture, Hadoop applications are more advanced.

[0069] (4) Realize the real-time uploading of relevant data to the cloud platform, and utilize the Internet, local area network and other transmission environments and the combination of multi-layer servers to integrate and manage the data of rivers, meteorology, pipe networks, land, pollution sources, social economy and other data within the survey scale;

[0070] (5) Develop seven functional modules based on the smart platform, including: a distributed water environment information database, a deep perception system for key pollution sources, a three-dimensional water environment simulation system, a water quality prediction and evaluation system, a business-oriented operation platform for total pollutant control, a comprehensive water environment management and decision-making platform, and a PDA-based smartphone mobile water environment auxiliary management system. After development, the modules will be debugged and put into operation; the platform will be operated, optimized, updated, and maintained to ensure daily operation, updates, and maintenance of the software system, as well as daily operation and maintenance of data and databases.

[0071] (6) Platform information transparency, building a picture of the ecological environment: "One map" data management realizes the integration and unified management of county space, rivers, meteorology, pipelines, land, pollution sources, social economy and other data, solves the problem of "numbers from multiple sources", and ensures the unity, authority and dynamic update of environmental data; "One map" integrated display is based on GIS+ big data visualization technology, intuitively displays the spatial distribution patterns and development trends of water-related elements in the basin, supports visualization of any area and elements, and makes information "clear at a glance"; "One map" comprehensive query can quickly query and conveniently export 138 types of data such as river water quality, pipelines, discharge outlets, pollution sources, etc., and provide "information query-statistical analysis-comprehensive evaluation" one-stop service for various river basin management departments; "One map" information sharing provides unified data services, map services, special services and other shared services to various management departments, ensuring "numbers from one source" and forming a new situation of interconnection, data sharing and business collaboration.

[0072] Although the present invention is described herein with reference to specific embodiments, it should be understood that these embodiments are merely illustrative of the principles and applications of the invention. It should be understood that many modifications may be made to the illustrative embodiments, and that other arrangements may be devised, without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that the various dependent claims and features described herein may be combined in ways other than those described in the original claims. It should also be understood that features described in conjunction with individual embodiments may be used in conjunction with other described embodiments.

Claims

1. An urban intelligent water service early warning system integrating the Internet of Things and the Internet, characterized in that Includes perception layer, communication layer, data layer and decision-making layer; The perception layer, based on IoT technology, builds an integrated sky-ground water conservancy IoT perception system covering water sources, pipe network tunnels, water plants, and river collection points. It utilizes pressure sensors, level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radar, and electronic identification equipment for precise pipeline positioning. Combined with drone oblique photography, satellite remote sensing imagery, and third-party data, it enables the collection of large amounts of multi-source data. The communication layer is used to send the large amount of multi-source data collected by the perception layer to the data layer. Based on the basic communication network transmission environment of the Internet, local area network, and narrowband communication, it uses switching equipment, firewall network equipment, including application servers, database servers, model servers, and backup servers, and combines 2 / 3 / 4 / 5G network communications to build a comprehensive communication layer suitable for smart water services; The data layer builds the urban water affairs and water situation database based on the large amount of multi-source data collected, including the basic database, water situation database, engineering situation database, water quality database, management database and remote sensing database; The data layer is used for unified organization and management of data resources, achieving data standardization and unified expression, and providing support for data exchange, comprehensive applications, and big data decision-making analysis; The decision-making layer is used to analyze and make decisions based on the large amount of multi-source data collected by the perception layer. It predicts water quality for all collection points based on each type of database. When the prediction result exceeds the limit, it combines the BIM platform and GIS platform to display an alarm.

2. The urban intelligent water service early warning system integrating the Internet of Things and the Internet according to claim 1, characterized in that, It also includes the application layer, the part that directly faces the user, to achieve unified organizational structure, user management and authority management, and to achieve integrated collaboration of all system layers within the portal framework through single sign-on, function integration and message integration.

3. The urban intelligent water service early warning system integrating the Internet of Things and the Internet according to claim 1, characterized in that, Water sources include groundwater and reservoirs; pipeline tunnels include urban drainage pipelines, underpasses, key water plants, and key drainage households; water plants include: water plants and sewage treatment plant outlets; rivers include key river sections.

4. The urban intelligent water service early warning system integrating the Internet of Things and the Internet according to claim 1, characterized in that, The basic database stores the drainage network structure, river channel physical information, and monitoring equipment placement locations. The river channel physical information includes width and length. The water regime database stores information collected by level meters, flow meters, and pressure sensors; The working situation database stores information collected by rain gauges and thermometers; The water quality database stores information collected by online water quality monitoring equipment and pipeline robots; The management database stores information collected by video surveillance; The remote sensing database stores information collected by drone oblique photography and remote sensing satellites.

5. A method for urban intelligent water service early warning integrating the Internet of Things and the Internet, which is implemented based on the urban intelligent water service early warning system integrating the Internet of Things and the Internet according to any one of claims 1 to 4, and is characterized in that, The method includes: S1. Deploy pressure sensors, level meters, flow meters, rain gauges, video surveillance, underground pipeline ground-penetrating radar, and electronic identification equipment for precise pipeline positioning at the sensing site. Combined with drone oblique photography, satellite remote sensing imagery, and third-party data, large amounts of multi-source data are collected and wirelessly transmitted to the data layer. S2, build a basic database, water situation database, engineering situation database, water quality database, management database and remote sensing database based on the large amount of multi-source data collected in S1; S3. Combine the BIM platform and the GIS platform, and use big data analysis to perform early warning analysis operations on the data of each type of database based on big data and deep learning algorithms to obtain the analysis results, and send the analysis results to the decision-making layer; S4. When the analysis result exceeds the early warning index threshold, display it on the platform, give an alarm, and output and feedback the early warning instruction to the collection point.

6. The urban intelligent water service early warning method integrating the Internet of Things and the Internet according to claim 5, characterized in that, After step S1, first execute the following steps: Preprocessing step: Optimize the data collected by the perception layer through means such as multi-source data fusion derivation, feature engineering, or outlier and missing value filling, and then execute step S2 to construct the database.

7. The urban intelligent water service early warning method integrating the Internet of Things and the Internet according to claim 5, characterized in that, The early warning index threshold is obtained by querying from the surface water environmental quality standard value table.

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