CN113919752A - Intelligent community platform construction method based on government big data - Google Patents

Intelligent community platform construction method based on government big data Download PDF

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Publication number
CN113919752A
CN113919752A CN202111347292.2A CN202111347292A CN113919752A CN 113919752 A CN113919752 A CN 113919752A CN 202111347292 A CN202111347292 A CN 202111347292A CN 113919752 A CN113919752 A CN 113919752A
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cloud
decision
community
state parameters
conclusion
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樊馨
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Shenzhen Chuangzhiyuan Intellectual Property Operation Co Ltd
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Shenzhen Chuangzhiyuan Intellectual Property Operation Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0631Resource planning, allocation or scheduling for a business operation
    • G06Q10/06315Needs-based resource requirements planning or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10Services
    • G06Q50/26Government or public services

Abstract

The application discloses a method for building a smart community platform based on government big data, which is applied to a smart community cloud platform and comprises the following steps: the intermediate cloud carries out data cleaning on the community state parameters and the user requirements, extracts effective user requirements and effective community state parameters, and sends the effective user requirements and the effective community state parameters to the decision cloud; the decision cloud analyzes the effective community state parameters and generates an analysis conclusion; the decision cloud generates an initial decision suggestion based on effective user requirements, generates a final decision suggestion based on an analysis conclusion, and sends the final decision suggestion to the government affair cloud; the government affair cloud receives the decision suggestions, generates decision conclusions based on the decision suggestions, and respectively sends the decision conclusions to the decision cloud; and the decision cloud receives the decision conclusion, carries out digital verification on the decision conclusion, and transmits the decision conclusion to the intermediate cloud after the verification is successful.

Description

Intelligent community platform construction method based on government big data
Technical Field
The application relates to the technical field of information, in particular to a method for building an intelligent community platform based on government big data.
Background
The intelligent community is characterized in that the intelligent community fully depends on the internet and the internet of things, relates to the fields of intelligent buildings, intelligent homes, road network monitoring, intelligent hospitals, city life line management, food and medicine management, ticket management, home care, personal health, digital life and the like, holds the important opportunities of a new technological innovation revolution and the wave of information industry, fully exerts the advantages of developed Information Communication (ICT) industry, advanced RFID related technologies, excellent telecommunication services and information-based infrastructure and the like, accelerates the key industrial technology attack and construction of the intelligent environment of community development by building ICT infrastructure, authentication, safety and other platforms and demonstration projects, forms a new life, industrial development, social management and other modes based on mass information and intelligent filtering processing, and is oriented to the construction of a brand new community form.
However, in the current intelligent community, the intelligent community platform based on government affairs does not really realize 'intelligence', the collection channel of information is single, the decision making or reference information making of government affairs is less, and a large amount of 'information isolated islands' and 'non-user pain points' government affair decisions appear.
Disclosure of Invention
The embodiment of the application provides a method for building a smart community platform based on government big data, which is used for solving the problems that in the prior art, a government affair-based smart community decision information channel is single and decision reference information is not sound.
The embodiment of the invention provides a method for building a smart community platform based on government big data, which is applied to a smart community cloud platform, wherein the smart community cloud platform comprises a government affair cloud, a decision cloud, a middle cloud, a backup cloud and a plurality of community clouds, and the method comprises the following steps:
the plurality of community clouds collect community state parameters and user requirements and send the community state parameters and the user requirements to the intermediate cloud;
the intermediate cloud carries out data cleaning on the community state parameters and the user requirements, extracts effective user requirements and effective community state parameters, and sends the effective user requirements and the effective community state parameters to the decision cloud;
the decision cloud analyzes the effective community state parameters and generates an analysis conclusion;
the decision cloud generates an initial decision suggestion based on the effective user demand, generates a final decision suggestion based on the analysis conclusion, and sends the final decision suggestion to the government affair cloud;
the government affair cloud receives the decision suggestion, generates a decision conclusion based on the decision suggestion, and respectively sends the decision conclusion to the decision cloud and the backup cloud, wherein the decision conclusion comprises a cell ID, a cell resource release decision and a cell special fund number;
the decision cloud receives the decision conclusion, carries out digital verification on the decision conclusion, and sends the decision conclusion to the intermediate cloud after successful verification;
and the intermediate cloud broadcasts the decision conclusion to a community cloud corresponding to the community ID according to the community ID so as to receive and display the information of the community cloud.
Optionally, the intermediate cloud performs data cleaning on the community state parameters and the user requirements, extracts effective user requirements and effective community state parameters, and includes:
the intermediate cloud sets different sampling times for the community state parameters according to different types, samples the community state parameters of different types according to different sampling times, and obtains the sampled community state parameters;
the intermediate cloud acquires two adjacent sampled community state parameters of the same type, and if the difference between the two sampled community state parameters is within a preset threshold value range, one of the two sampled community state parameters is removed;
the middle cloud compresses the community state parameters after the sampling and eliminating operation;
the intermediate cloud acquires abnormal community state parameters, wherein the abnormal community state parameters and the compressed community state parameters are effective community state parameters, and the community state parameters are one or more combinations of building energy consumption, noise, parking space states, gate states and monitoring equipment states;
the intermediate cloud carries out character recognition on the user requirements, extracts keywords, carries out keyword identification to carry out requirement classification, and forms structured user requirement data, wherein the structured user requirement data are effective user requirements.
Optionally, before forming the structured user demand data, the method further comprises:
and the intermediate cloud grades the user requirements according to the probability of the occurrence of the keywords, and allocates different priorities to the user requirements of different grades, so that the different user requirements are sequentially sent to the decision cloud according to the priority sequence.
Optionally, the decision cloud generates an initial decision suggestion based on the effective user demand, and generates a final decision suggestion based on the analysis conclusion, including:
the decision cloud sets a demand matching target based on the effective user demand, conducts feasibility analysis based on the demand matching target, and generates an initial decision suggestion after the feasibility analysis is passed;
the decision cloud adjusts the initial decision suggestion based on the analysis conclusion and generates a final decision suggestion.
Optionally, the government cloud generating a decision conclusion based on the decision suggestion, including:
and the government affair cloud acquires a historical record based on a government affair database, government affair requirements and a special fund support target, and generates a decision conclusion.
Optionally, the decision cloud digitally verifies the decision conclusion, including:
and the decision cloud carries out digital signature verification on the decision conclusion.
Optionally, the method further comprises:
the intermediate cloud estimates the number of the community state parameters and the number of user requirements in different time periods;
and when the number of the community state parameters and the number of the user demands exceed a preset range in a period of time, the intermediate cloud carries out resource scheduling, occupies idle resources in the one or more community clouds and the backup cloud to strengthen data processing, and releases redundant data processed by the intermediate cloud.
Optionally, the method further comprises:
the backup cloud is also used to backup the final decision suggestions and decision conclusions.
According to the method provided by the embodiment of the invention, the community cloud, the middle cloud, the decision cloud and the government affair cloud are matched with each other, information is obtained from the basic layer, the middle layer is cleaned, the decision layer provides decision suggestions by utilizing the information, final decision is finally realized through the government affair cloud, information channels of various communities are opened, different community decisions can be provided according to local conditions based on the states of different communities, the pain points of residents of the smart communities are fundamentally solved, the decision is flexibly made based on the current community state, the decision is more targeted, an information sharing channel of a smart community platform of an end-management-cloud is opened, and the information sharing channel and the effective information utilization rate are greatly improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below.
FIG. 1 is an architecture diagram of a platform construction system for a smart community in one embodiment;
FIG. 2 is a flow diagram illustrating platform construction of a smart community in one embodiment.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. 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 application.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Fig. 1 is an architecture diagram of a platform construction system of a smart community in an embodiment of the present invention. As shown in fig. 1, in the embodiment of the present invention, the system architecture includes a plurality of community clouds 101, an intermediate cloud 102, a backup cloud 103, a decision cloud 104, and a government affairs cloud 105. The community cloud is located in different communities and used for collecting the requirements of different residents (users) in the community and data reported by all IoT equipment in the community, and the cloud server is accessed inside the community in a distributed mode (such as a property management center), so that various different data in the community can be efficiently and stably collected to perform cloud storage and cloud management in real time. The intermediate cloud is an intermediate cloud between a basic community cloud and an upper decision cloud, and is used for data acquisition, data processing (such as data cleaning and data classification), data distribution and data storage, the intermediate cloud is generally built in a geometric center of a plurality of communities, for example, an administrative management department of a community street, data acquisition and processing are conveniently performed on a plurality of communities of the street, the intermediate cloud is different from the community cloud and only acquires and summarizes data of one community, the intermediate cloud collects data of different communities in real time or regularly, unified management is conveniently performed on the communities, and no matter the administrative department of the street, the public security department and the traffic management department can acquire information of different communities in real time or regularly. The decision cloud is set up based on an administrative district or a city, the coverage range of the decision cloud is wider than that of the middle cloud, and administrative advices can be provided for administrative reference of policy makers in the administrative district or the city. Therefore, after the intermediate cloud performs data cleaning, the effective information is sent to the decision cloud, the decision cloud can evaluate according to different community state parameters and user requirements, and make the most appropriate decision suggestion to report. The government affair cloud is a government ERP system adopted by government departments, comprises three functions of data acquisition, data storage and data processing, and can also provide functions such as government affair disclosure, government affair release, government affair financial data collection and the like.
Fig. 2 is a flowchart of a method for building a smart community platform based on government big data according to an embodiment of the present invention, and the method is applied to the smart community cloud platform shown in fig. 1, and as shown in fig. 2, the method includes:
s101, collecting community state parameters and user requirements by the plurality of community clouds, and sending the community state parameters and the user requirements to the intermediate cloud;
the community state parameters can be parameter information reported by various detection devices in the community, and according to the types, the community devices can be classified into safety monitoring devices, amusement facility devices, environment protection devices, maintenance and maintenance devices and the like, the safety monitoring devices comprise cameras, fire alarm early warning devices, gates, access control devices and the like, the amusement facility devices comprise sound boxes, loudspeakers, large amusement equipment and the like, the environment protection devices comprise noise acquisition devices, air quality (PM2.5) acquisition devices, energy consumption (electric energy, natural gas and water energy) monitoring devices and the like, and the maintenance and maintenance devices comprise maintenance warning lamps, seals, banners, ice cream cones, maintenance tools and the like. The types of parameter information collected by each type of equipment are different, the sizes of data are different, and reporting periods are also different, so that the community cloud is required to have a multi-source heterogeneous data fusion function, perform deep fusion on different data of different data sources, and feed back the data to the middle cloud in a real-time or timing manner.
The user demand can be put forward through the property aspect, also can report through the application on the user terminal, and the user demand is various, for example parking management, month card are recharged, and construction is noisy etc. the user demand possesses specific purpose, consequently, can follow the expression of characters in the user demand and extract the keyword, assesses according to the keyword, and the mode of accessible machine learning carries out user demand purpose aassessment.
S102, the intermediate cloud carries out data cleaning on the community state parameters and the user requirements, effective user requirements and effective community state parameters are extracted, and the effective user requirements and the effective community state parameters are sent to the decision cloud;
the community state parameters and the user requirements are generated and recorded at every moment, and most of the parameters and the user requirements have no practical significance for government affair planning, so that the intermediate cloud needs to clean the community state parameters and the user requirements reported by each community cloud and extract key information (effective information) in the community state parameters and the user requirements for decision making.
In the embodiment of the present invention, the core content of the effective user requirement and the effective community state parameter needs to be associated with the content of government affairs services, such as children learning, cell school distribution, peripheral noise complaints and noise thresholds, cell environment update, cell traffic improvement, and the like. For the government service, firstly, community state parameters in different time periods and abnormal community state parameters need to be periodically acquired, and secondly, keywords corresponding to the government service (for example, primary school, etc. are education keywords) need to be provided in effective user requirements.
For the first point, the intermediate cloud needs to sample different community state parameters to compress the data volume to the maximum extent and acquire abnormal community state parameters, wherein the abnormal community state parameters are compared with the same data acquired at the previous time, and the difference value of the abnormal community state parameters is significantly larger than or smaller than a preset threshold value. For example, if the noise index of a certain period of time is greater than the noise index of the previous period of time, the noise index is determined as an abnormal parameter, and the reason behind the abnormal parameter is usually due to an emergency such as construction around a cell, a car accident, and an organization business activity, and thus needs to be emphasized.
Therefore, the intermediate cloud sets different sampling times for the community state parameters according to different types, samples the community state parameters of different types according to different sampling times, and obtains the sampled community state parameters;
the method comprises the steps that an intermediate cloud obtains two adjacent sampled community state parameters of the same type, and one of the two sampled community state parameters is removed if the difference between the two sampled community state parameters is within a preset threshold range;
compressing the sampled and removed community state parameters by the intermediate cloud;
the method comprises the steps that an intermediate cloud obtains abnormal community state parameters, the abnormal community state parameters and compressed community state parameters are effective community state parameters, and the community state parameters are one or more combinations of building energy consumption, noise, parking space states, gate states and monitoring equipment states;
for the second point, the user needs to perform keyword/word matching, so that the intermediate cloud performs character recognition on the user needs, extracts keywords, performs keyword identification to perform requirement classification, and forms structured user demand data, wherein the structured user demand data is effective user demands.
In addition, optionally, before forming the structured user requirement data, the embodiment of the present invention further includes:
and the intermediate cloud grades the user requirements according to the probability of the occurrence of the keywords, and allocates different priorities to the user requirements of different grades so as to sequentially send the different user requirements to the decision cloud according to the priority sequence.
In addition, the intermediate cloud estimates the number of the community state parameters and the number of user requirements in different time periods;
and when the number of the community state parameters and the number of the user demands exceed a preset range in a period of time, the intermediate cloud carries out resource scheduling, occupies idle resources in the one or more community clouds and the backup cloud to strengthen data processing, and releases redundant data processed by the intermediate cloud.
S103, analyzing the effective community state parameters by the decision cloud, and generating an analysis conclusion;
the decision cloud is separated from the intermediate cloud, namely the decision cloud is separated from heavy data clear work, and the work of data analysis and decision suggestion making is focused.
The effective community state parameter is composed of the abnormal community state parameter and the compressed community state parameter as described above, and how to utilize the information is the most core function of the decision cloud. For decision cloud, various community state parameters need to be analyzed, analysis conclusions are obtained, different community state parameters are different, the analysis conclusions are also different, generally, through manual rule making, different numerical value intervals can be used for matching different analysis conclusions, for example, a noise parameter is defined as high noise when the noise parameter exceeds 70 decibels, the noise parameter presents obvious normal distribution conditions at different times, working days, early peak and late peak noise values are high, a flat peak noise value is low, if a monitored noise value is higher than a certain threshold value in the flat peak period and has long duration, an emergency is considered to occur, according to the defined rules, the analysis conclusions are multiple possible conclusions, for example, construction around a community, community decoration, square dance noise, vehicle horn noise and the like, further, the analysis conclusions need to be verified by other effective community parameters, for example, the conclusion of square dance noise is required to be met if a plurality of people dance in square dance are detected, and the conclusion can be said to be met if the noise is higher than a preset threshold value, otherwise, the conclusion is not met. Therefore, for the decision cloud, at least one verification mode needs to be established to verify the conclusion of the decision cloud on the single parameter analysis, the establishment of the verification mode can be specified in processing logic in advance, for example, square dance noise needs noise detection equipment to detect noise, monitoring equipment monitors whether people gather and dance on the square, and the decision cloud needs to specify the association relationship between the square dance noise and the noise in the internal analysis conclusion processing logic or program. The logic relationship is as follows: the decision cloud acquires a noise parameter- > judges that the noise parameter is too high- > acquires an effective monitoring image (belonging to one of monitoring safety parameters of a community) uploaded by the detection equipment- > judges that someone dances on a square- > the conclusion of the noise of the square dance is established.
Different analysis conclusions are different for different parameter performance characteristics, so that the decision cloud sets different analysis conclusion obtaining rules which are set based on community service experience and aim to automate artificial community processing.
S104, the decision cloud generates an initial decision suggestion based on the effective user demand, generates a final decision suggestion based on the analysis conclusion, and sends the final decision suggestion to the government affair cloud;
the effective user requirements are suggestions which are proposed based on the requirements of the user, the suggestion starts from the point of being based on individuals, and the decision mechanism is to convert the requirements of individuals into the requirements of commonalities and realize the requirements based on some means. Therefore, the decision cloud needs to react the analysis conclusion to the initial decision suggestion, so that rational data is provided for individual needs, and the decision cloud has both subjective will and objective facts, and is beneficial for decision makers to make final decisions.
Therefore, the decision cloud sets a demand matching target based on the effective user demand, conducts feasibility analysis based on the demand matching target, and generates an initial decision suggestion after the feasibility analysis is passed; for example, the effective user requirements are: prohibiting a square dance after 21 pm, then the demand matching objective is: release forbids square dancing at 21 o' clock and later, the initial decision proposal is the demand matching target.
The decision cloud adjusts the initial decision suggestion based on the analysis conclusion and generates a final decision suggestion. For example, if the analysis result is that the square dance noise is low, the initial decision suggestion is passed, and the final decision suggestion is consistent with the initial decision suggestion, and if the analysis result is that the square dance noise is low, and people cannot be disturbed, the initial decision suggestion is not passed, and the final decision suggestion and the initial decision suggestion are opposite.
S105, the government affair cloud receives the decision suggestion, generates a decision conclusion based on the decision suggestion, and sends the decision conclusion to the decision cloud and the backup cloud respectively, wherein the decision conclusion comprises a cell ID, a cell resource release decision and a cell special fund number;
the government affair cloud is a cloud adopted by government departments, and after decision suggestions are received, comprehensive analysis needs to be carried out by combining historical policy data, special fund data and the like in the government affair cloud so that decision-makers can provide decision-making conclusions. The decision conclusions may include cell-specific policies or guidelines such as primary school assignment policies, road improvement policies, decisions to increase security monitoring, etc.
Optionally, the government cloud generating a decision conclusion based on the decision suggestion, including: and acquiring historical records based on a government affair database, government affair requirements and special fund support targets, and generating a decision conclusion.
S106, the decision cloud receives the decision conclusion, carries out digital verification on the decision conclusion, and sends the decision conclusion to the intermediate cloud after the verification is successful;
and the decision cloud carries out digital signature verification on the decision conclusion. Digital signature verification is prior art, and the comparison of the embodiments of the present invention is not repeated.
S107, the intermediate cloud broadcasts the decision conclusion to the community cloud corresponding to the community ID according to the community ID, so that the community cloud receives and displays messages.
It should be noted that the backup cloud is also used for backing up the final decision suggestion and decision conclusion.
According to the method provided by the embodiment of the invention, the community cloud, the middle cloud, the decision cloud and the government affair cloud are matched with each other, information is obtained from the basic layer, the middle layer is cleaned, the decision layer provides decision suggestions by utilizing the information, final decision is finally realized through the government affair cloud, information channels of various communities are opened, different community decisions can be provided according to local conditions based on the states of different communities, the pain points of residents of the smart communities are fundamentally solved, the decision is flexibly made based on the current community state, the decision is more targeted, an information sharing channel of a smart community platform of an end-management-cloud is opened, and the information sharing channel and the effective information utilization rate are greatly improved.
The above is only a specific embodiment of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (6)

1. A method for building a smart community platform based on government big data is applied to the smart community cloud platform, the smart community cloud platform comprises a government affair cloud, a decision cloud, an intermediate cloud, a backup cloud and a plurality of community clouds, and the method comprises the following steps:
the plurality of community clouds collect community state parameters and user requirements and send the community state parameters and the user requirements to the intermediate cloud;
the intermediate cloud carries out data cleaning on the community state parameters and the user requirements, extracts effective user requirements and effective community state parameters, and sends the effective user requirements and the effective community state parameters to the decision cloud;
the decision cloud analyzes the effective community state parameters and generates an analysis conclusion;
the decision cloud generates an initial decision suggestion based on the effective user demand, generates a final decision suggestion based on the analysis conclusion, and sends the final decision suggestion to the government affair cloud;
the government affair cloud receives the decision suggestion, generates a decision conclusion based on the decision suggestion, and respectively sends the decision conclusion to the decision cloud and the backup cloud, wherein the decision conclusion comprises a cell ID, a cell resource release decision and a cell special fund number;
the decision cloud receives the decision conclusion, carries out digital signature verification on the decision conclusion, and sends the decision conclusion to the intermediate cloud after the verification is successful;
the intermediate cloud broadcasts the decision conclusion to a community cloud corresponding to the community ID according to the community ID so as to receive and display messages of the community cloud;
the intermediate cloud estimates the number of the community state parameters and the number of user requirements in different time periods;
and when the number of the community state parameters and the number of the user demands exceed a preset range in a period of time, the intermediate cloud carries out resource scheduling, occupies idle resources in the one or more community clouds and the backup cloud to strengthen data processing, and releases redundant data processed by the intermediate cloud.
2. The method according to claim 1, wherein the intermediate cloud performs data cleaning on the community state parameters and the user requirements to extract effective user requirements and effective community state parameters, and the method comprises the following steps:
the intermediate cloud sets different sampling times for the community state parameters according to different types, samples the community state parameters of different types according to different sampling times, and obtains the sampled community state parameters;
the intermediate cloud acquires two adjacent sampled community state parameters of the same type, and if the difference between the two sampled community state parameters is within a preset threshold value range, one of the two sampled community state parameters is removed;
the middle cloud compresses the community state parameters after the sampling and eliminating operation;
the intermediate cloud acquires abnormal community state parameters, wherein the abnormal community state parameters and the compressed community state parameters are effective community state parameters, and the community state parameters are one or more combinations of building energy consumption, noise, parking space states, gate states and monitoring equipment states;
the intermediate cloud carries out character recognition on the user requirements, extracts keywords, carries out keyword identification to carry out requirement classification, and forms structured user requirement data, wherein the structured user requirement data are effective user requirements.
3. The method of claim 2, wherein prior to forming structured user demand data, the method further comprises:
and the intermediate cloud grades the user requirements according to the probability of the occurrence of the keywords, and allocates different priorities to the user requirements of different grades, so that the different user requirements are sequentially sent to the decision cloud according to the priority sequence.
4. The method of claim 1, wherein the decision cloud generates an initial decision suggestion based on the effective user demand and a final decision suggestion based on the analysis conclusion, comprising:
the decision cloud sets a demand matching target based on the effective user demand, conducts feasibility analysis based on the demand matching target, and generates an initial decision suggestion after the feasibility analysis is passed;
the decision cloud adjusts the initial decision suggestion based on the analysis conclusion and generates a final decision suggestion.
5. The method of claim 1, wherein the government cloud generating a decision conclusion based on the decision suggestion comprises:
and the government affair cloud acquires a historical record based on a government affair database, government affair requirements and a special fund support target, and generates a decision conclusion.
6. The method according to any one of claims 1-5, further comprising:
the backup cloud is also used to backup the final decision suggestions and decision conclusions.
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