CN112446549A - Urban garbage intelligent supervision platform based on big data - Google Patents
Urban garbage intelligent supervision platform based on big data Download PDFInfo
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Abstract
The invention discloses a smart urban garbage supervision platform based on big data in the technical field of urban garbage supervision, which comprises a data exchange center subsystem and an application subsystem, wherein the data exchange center subsystem comprises a data acquisition module, a data organization module and a data analysis module and is used for completing the collection, organization and analysis of the big data and establishing a basic database; the application subsystem comprises a GIS application subsystem, an event tracking processing subsystem, an information management subsystem and a decision support subsystem. The system is designed according to the requirements of determined scientific purpose, scale and technical index to build a unified, shared, high-technical-level, high-stability system which meets the requirements of the intelligent management business of the municipal waste.
Description
Technical Field
The invention relates to the technical field of urban garbage supervision, in particular to an urban garbage intelligent supervision platform based on big data.
Background
The improvement is open, along with the continuous promotion of the urbanization process of China, the urban scale is gradually expanded, the total quantity of urban garbage is sharply increased, the pollution is caused to the urban environment, the sustainable development of cities is hindered, and the serious satellite is also caused to the stability of the society and the urban safety. Therefore, how to realize effective management of municipal waste through the innovation of supervision and treatment means becomes a focus of attention and research.
Along with the development of urban modernization, urban garbage treatment and supervision are more and more complex, a new supervision platform is necessarily required, a new technology is provided for urban garbage information collection due to the arrival of a big data era, and based on the new technology, the urban garbage intelligent supervision platform based on big data is designed to solve the problems.
Disclosure of Invention
The invention aims to provide a smart urban garbage supervision platform based on big data to solve the problems.
In order to achieve the purpose, the invention provides the following technical scheme: the intelligent urban garbage supervision platform based on big data comprises a data exchange center subsystem and an application subsystem, wherein the data exchange center subsystem comprises a data acquisition module, a data organization module and a data analysis module and is used for completing the collection, organization and analysis of the big data and establishing a basic database; the application subsystem comprises a GIS application subsystem, an event tracking processing subsystem, an information management subsystem and a decision support subsystem.
Preferably, the data acquisition module specifically comprises
The urban garbage data acquisition module is used for acquiring urban garbage data by using intelligent data of Internet of things, GIS, computer network and image identification;
the dynamic information acquisition module is used for analyzing and acquiring the geographic space position information of the urban garbage disposal facility and the dynamic load information of the garbage disposal facility by utilizing a GIS space and a support vector machine;
the garbage dynamic data collection module is used for realizing dynamic data collection of garbage discharge by utilizing a GIS, a BP neural network and the Internet of things;
and the population dynamic data acquisition module is used for acquiring real-time data of urban population flow and dynamic data of urban population living environment by utilizing the GIS and the Internet.
Preferably, the data organization module specifically comprises
The preprocessing module is used for cleaning, redundancy elimination, association aggregation and feature extraction of data acquired in the early stage;
and the storage module is built based on Hadoop by adopting a mainstream distributed architecture.
Preferably, the data analysis module specifically comprises
The basic data analysis module carries out multi-dimensional and multi-level granularity deep analysis on the urban garbage data by using a tool, realizes the clustering, classification, inspection and weight setting of the data, mines the characteristics, attributes, values, associations and potential rules behind the data, and predicts the evolution process of the data.
The advanced data modeling module realizes modeling and simulation of garbage problems by utilizing machine learning and cloud computing, and establishes an intelligent analysis model.
Preferably, the GIS application subsystem includes
The data acquisition and storage module is used for acquiring ground data by using a satellite positioning system, and carrying out image segmentation, feature extraction, data cleaning and storage on the acquired data through big data preprocessing;
the space analysis module is used for determining whether the site selection meets environmental, social and political constraints or not by utilizing GIS space analysis, realizing information conversion from analog to digital by utilizing GIS and determining a primary site selection scheme; secondly, analyzing main influence factors of the site selection of the garbage facility by combining the collected multi-source data to form a site selection decision evaluation index system and related weights; finally, inputting the preliminary site selection scheme into a site selection model of the support vector machine, wherein the site selection model takes the least environmental cost and economic cost as a target function;
the data application module confirms the site selection of the garbage collection and treatment facility by using the GIS and the support vector machine technology and outputs a site selection map through a big data platform;
the detection and early warning module is used for collecting and storing pollutant emission garbage data, environment geographic data, meteorological data and remote sensing data by utilizing big data, establishing a garbage emission pollutant model library, establishing a monitoring and early warning model for dividing the emission type and the emission concentration of the garbage pollution emission according to the monitoring of the garbage pollution emission, combining a Gaussian diffusion model and a neural network, and realizing the visual output of the information of the monitoring and early warning model by utilizing the GIS technology.
Preferably, the event tracking processing subsystem collects subjective evaluation and complaint opinions of the public on urban garbage processing by using a web crawler acquisition method, acquires and distributively stores big data, intelligently identifies the data by using a K-Means clustering algorithm, establishes a gray early warning model by using a co-word analysis method and deep learning, establishes a neural network model by using satisfaction data, evaluation indexes and weights, and obtains dynamic and static values of service quality to form an early warning model; has a visual interface.
Preferably, the information management subsystem is used for managing the information of the supervision platform, and providing channels and platforms for information sharing feedback, decision negotiation and governing action cooperation for cooperation of a multi-element main body by utilizing big data.
Preferably, the decision support subsystem is configured to analyze dynamic data provided by the data exchange center to obtain a suggestion for optimizing a garbage disposal route, a suggestion for optimizing a site of a garbage disposal site, and a suggestion for optimally placing a garbage facility, and the decision support subsystem implements, by means of an Agent and a genetic algorithm, garbage disposal market competition and garbage policy making and optimal selection.
Compared with the prior art, the invention has the beneficial effects that: the intelligent urban garbage supervision platform based on big data is designed according to the requirements of determined scientific purpose, scale and technical index to build a uniform, shared, high-technical-level, high-stability system meeting the requirements of intelligent urban garbage management business,
the advancement is as follows: the advanced development technology and architecture (component-based, plug-in or service-oriented architecture) are adopted to ensure the advancement and expandability of the platform and prolong the life cycle of the platform.
Configurability and manageability. The method is configurable, provides a convenient and friendly operation mode and a visual operation interface, and is easy to deploy, operate and manage the platform.
And (3) expandability: the product not only can be integrated with the existing system, but also has strong expansion capability and can support future application integration. And a clear secondary development environment and interface are provided.
Standardization: the system is constructed strictly according to relevant national, local and industrial standards and specifications, and open technologies and international mainstream products are adopted as far as possible so as to ensure that the system conforms to various international open standards.
High performance and stability: when the system is designed, developed and applied, the system structure, technical measures, software and hardware platforms, technical service, maintenance response capability and the like are comprehensively considered, and the higher performance of the system is ensured.
Safety and confidentiality: the safety of data under the network environment is ensured, and a complete data protection and backup mechanism is adopted. In order to prevent illegal intrusion of unauthorized users and unauthorized use of authorized users, the system should perform authority control of various levels, and has an auditing function, and automatically records the access condition and operation process of users for later inquiry.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a block diagram of a data acquisition module according to the present invention;
FIG. 3 is a block diagram of a data organization module according to the present invention;
FIG. 4 is a block diagram of a data analysis module according to the present invention;
FIG. 5 is a block diagram of a GIS application subsystem architecture of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-5, the present invention provides a technical solution: the intelligent urban garbage supervision platform based on big data comprises a data exchange center subsystem and an application subsystem, wherein the data exchange center subsystem comprises a data acquisition module, a data organization module and a data analysis module and is used for completing the collection, organization and analysis of the big data and establishing a basic database; the application subsystem comprises a GIS application subsystem, an event tracking processing subsystem, an information management subsystem and a decision support subsystem.
The data is the most critical raw material for big data analysis activities and is the basis for big data application. The data sources comprise management department data sources, social organization data sources, internet data sources, intelligent mobile terminal data sources and the like. The data center adopts intelligent data acquisition technologies such as Internet of things, GIS, computer network and image recognition to acquire urban garbage data.
Wherein the data acquisition module specifically comprises
The urban garbage data acquisition module is used for acquiring urban garbage data by using intelligent data of Internet of things, GIS, computer network and image identification;
the dynamic information acquisition module is used for analyzing and acquiring the geographic space position information of the urban garbage disposal facility and the dynamic load information of the garbage disposal facility by utilizing a GIS space and a support vector machine;
the garbage dynamic data collection module is used for realizing dynamic data collection of garbage discharge by utilizing a GIS, a BP neural network and the Internet of things;
and the population dynamic data acquisition module is used for acquiring real-time data of urban population flow and dynamic data of urban population living environment by utilizing the GIS and the Internet.
Wherein the data organization module specifically comprises
The preprocessing module is used for cleaning, redundancy elimination, association aggregation and feature extraction of data acquired in the early stage;
and the storage module is built based on Hadoop by adopting a mainstream distributed architecture.
The data center needs to preprocess and store the acquired mass data. The data content collected in the early stage is various and messy, and the data analysis can be carried out only after the preprocessing such as data cleaning, redundancy elimination, association aggregation, feature extraction and the like is carried out on the data.
Wherein the data analysis module specifically comprises
The basic data analysis module carries out multi-dimensional and multi-level granularity deep analysis on the urban garbage data by using a tool, realizes the clustering, classification, inspection and weight setting of the data, mines the characteristics, attributes, values, associations and potential rules behind the data, and predicts the evolution process of the data.
The advanced data modeling module realizes modeling and simulation of garbage problems by utilizing machine learning and cloud computing, and establishes an intelligent analysis model.
The basic data analysis is to utilize tools such as the tool to deeply analyze urban garbage data in a data system in a multi-dimensional and multi-level granularity manner, realize clustering, classification, inspection and weight setting of the data, mine characteristics, attributes, values, association and potential rules behind the data, predict the evolution process of the data and the like, and obtain an analysis model for solving problems by comprehensively analyzing and researching the urban garbage treatment problems.
The advanced data modeling part mainly utilizes technologies such as machine learning, cloud computing and the like to realize modeling and simulation of garbage problems, establishes an intelligent analysis model, enables the intelligent analysis model to be capable of adapting to continuously changing garbage management requirements through continuous autonomous learning, monitoring and training, and can carry out deep mining analysis on related big data to obtain mathematical results such as data modes, rules, relations and the like.
Wherein the GIS application subsystem comprises
The system comprises a data acquisition and storage module, a garbage disposal facility site selection relates to a plurality of factors such as traffic, garbage, geography, humanity, economy and the like, high-resolution real-time ground data is acquired by means of a positioning system, and operations such as image segmentation, feature extraction, data cleaning and the like are carried out on the acquired data through a big data preprocessing technology.
The space analysis module is used for performing GIS space analysis to determine whether site selection meets the constraints of environment, society, politics and the like, and the geographic information technology is utilized to realize information conversion from analog to digital to determine a primary site selection scheme; secondly, analyzing main influence factors of the site selection of the garbage facility by combining the collected multi-source data to form a site selection decision evaluation index system and related weights; and finally, inputting the initial addressing scheme into an addressing model of the support vector machine, wherein the addressing model takes the least environmental cost and economic cost as a target function.
The data application module confirms the site selection of the garbage collection and treatment facility by using the GIS and the support vector machine technology and outputs a site selection map through a big data platform;
the detection and early warning module and the big data technology can quickly locate and identify pollution problems, and an intelligent monitoring and early warning technology is provided for secondary pollution. The method comprises the steps of collecting and storing pollution emission garbage data, environment geographic data, meteorological data and remote sensing data by utilizing big data, establishing a garbage emission pollutant model library, establishing a monitoring and early warning model for dividing the emission type and concentration of the garbage pollution emission according to the monitoring of the garbage pollution emission, combining a Gaussian diffusion model and a neural network, and realizing visual output of information of the monitoring and early warning model by utilizing a GIS technology.
Wherein the event tracking processing subsystem
The big data can enrich the dynamic supervision of the problem of low garbage treatment efficiency by a supervision mode, public can evaluate and supervise the level and quality of public services such as garbage classification, cleaning, recovery and the like of garbage management departments and garbage operation enterprises, and functional departments can provide rectification measures according to acquired data and track and supervise the event processing process, so that the urban garbage treatment level is improved. Collecting subjective evaluation and complaint opinions of public on urban garbage treatment by using a network crawler and other collection modes, acquiring and storing big data in a distributed mode, intelligently identifying the data by using big data preprocessing technologies such as a K-Means clustering algorithm and the like, establishing a gray early warning model by using a co-word analysis method and deep learning, establishing a neural network model by using satisfaction data, evaluation indexes and weights, obtaining dynamic and static values of service quality, and forming the early warning model. By utilizing a visualization technology, main problems and influencing factors focused by the public, garbage quality evaluation feedback results and information early warning are shown, and functional departments propose treatment measures and track execution results according to data analysis results to supervise and urge in time.
The information management subsystem is used for managing the information of the supervision platform, displaying the related big data resource information of the multi-element main body of the garbage disposal through various ways, and managing the system information in real time according to requirements. The big data technology can provide channels and platforms for information sharing feedback, decision negotiation and treatment action cooperation for cooperation of the multi-element main body, garbage related big data resources are integrated, and cooperation work of the multi-element garbage treatment main body is promoted.
Wherein the decision support subsystem
And intelligent decision suggestion can be realized through big data analysis results. The system can obtain suggestions for optimizing garbage clearing lines, suggestions for optimizing site selection of garbage disposal places and suggestions for optimally placing garbage facilities by analyzing dynamic data provided by the data center. Meanwhile, the subsystem realizes the garbage disposal market competition and the garbage policy making and optimal selection by means of the Agent and the genetic algorithm.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. Municipal rubbish wisdom supervision platform based on big data, its characterized in that: the system comprises a data exchange center subsystem and an application subsystem, wherein the data exchange center subsystem comprises a data acquisition module, a data organization module and a data analysis module and is used for completing the collection, organization and analysis of big data and establishing a basic database; the application subsystem comprises a GIS application subsystem, an event tracking processing subsystem, an information management subsystem and a decision support subsystem.
2. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the data acquisition module specifically comprises
The urban garbage data acquisition module is used for acquiring urban garbage data by using intelligent data of Internet of things, GIS, computer network and image identification;
the dynamic information acquisition module is used for analyzing and acquiring the geographic space position information of the urban garbage disposal facility and the dynamic load information of the garbage disposal facility by utilizing a GIS space and a support vector machine;
the garbage dynamic data collection module is used for realizing dynamic data collection of garbage discharge by utilizing a GIS, a BP neural network and the Internet of things;
and the population dynamic data acquisition module is used for acquiring real-time data of urban population flow and dynamic data of urban population living environment by utilizing the GIS and the Internet.
3. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the data organization module specifically comprises
The preprocessing module is used for cleaning, redundancy elimination, association aggregation and feature extraction of data acquired in the early stage;
and the storage module is built based on Hadoop by adopting a mainstream distributed architecture.
4. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the data analysis module specifically comprises
The basic data analysis module carries out multi-dimensional and multi-level granularity deep analysis on the urban garbage data by using a tool, realizes the clustering, classification, inspection and weight setting of the data, mines the characteristics, attributes, values, associations and potential rules behind the data, and predicts the evolution process of the data.
The advanced data modeling module realizes modeling and simulation of garbage problems by utilizing machine learning and cloud computing, and establishes an intelligent analysis model.
5. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the GIS application subsystem comprises
The data acquisition and storage module is used for acquiring ground data by using a satellite positioning system, and carrying out image segmentation, feature extraction, data cleaning and storage on the acquired data through big data preprocessing;
the space analysis module is used for determining whether the site selection meets environmental, social and political constraints or not by utilizing GIS space analysis, realizing information conversion from analog to digital by utilizing GIS and determining a primary site selection scheme; secondly, analyzing main influence factors of the site selection of the garbage facility by combining the collected multi-source data to form a site selection decision evaluation index system and related weights; finally, inputting the preliminary site selection scheme into a site selection model of the support vector machine, wherein the site selection model takes the least environmental cost and economic cost as a target function;
the data application module confirms the site selection of the garbage collection and treatment facility by using the GIS and the support vector machine technology and outputs a site selection map through a big data platform;
the detection and early warning module is used for collecting and storing pollutant emission garbage data, environment geographic data, meteorological data and remote sensing data by utilizing big data, establishing a garbage emission pollutant model library, establishing a monitoring and early warning model for dividing the emission type and the emission concentration of the garbage pollution emission according to the monitoring of the garbage pollution emission, combining a Gaussian diffusion model and a neural network, and realizing the visual output of the information of the monitoring and early warning model by utilizing the GIS technology.
6. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the event tracking processing subsystem collects subjective evaluation and complaint opinions of the public on urban garbage processing by using a web crawler acquisition method, acquires and stores big data in a distributed mode, intelligently identifies the data by using a K-Means clustering algorithm, establishes a gray early warning model by using a co-word analysis method and deep learning, establishes a neural network model by using satisfaction data, evaluation indexes and weights, and obtains dynamic and static values of service quality to form an early warning model; has a visual interface.
7. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the information management subsystem is used for completing management of the information of the supervision platform, and providing channels and platforms for information sharing feedback, decision negotiation and governing action cooperation for cooperation of a multi-element main body by utilizing big data.
8. The intelligent administration platform of municipal waste based on big data according to claim 1, wherein: the decision support subsystem is used for analyzing dynamic data provided by the data exchange center to obtain suggestions for optimizing a garbage clearing line, suggestions for optimizing site selection of a garbage disposal place and suggestions for optimally placing garbage facilities, and meanwhile, the decision support subsystem realizes garbage disposal market competition and the formulation and optimal selection of garbage policies by means of an Agent and a genetic algorithm.
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