CN111415098A - Intelligent endowment assessment system based on block chain technology - Google Patents
Intelligent endowment assessment system based on block chain technology Download PDFInfo
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- CN111415098A CN111415098A CN202010224103.1A CN202010224103A CN111415098A CN 111415098 A CN111415098 A CN 111415098A CN 202010224103 A CN202010224103 A CN 202010224103A CN 111415098 A CN111415098 A CN 111415098A
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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- G06F16/24—Querying
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- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G—PHYSICS
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- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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Abstract
The invention discloses an intelligent endowment evaluation system based on a block chain technology, which belongs to the technical field of intelligent endowment and comprises a user layer, an application layer and a data layer; the user layer is used for enabling a user to enter the application layer through a Web interactive interface to perform function interaction; the application layer comprises intelligent model evaluation, data statistics record, risk early warning management, node management, user management and system management, functional services are provided for the whole system by calling data of the data layer, wherein the intelligent model evaluation is used for intelligently evaluating various services in intelligent endowment, the data statistics record is used for counting evaluation results every time and drawing a chart, the risk early warning management is used for early warning the intelligent endowment services with lower evaluation, the node management is used for managing and accessing a database of the application layer, the user management is used for managing users, and the system management is used for configuring system parameters and managing system operation.
Description
Technical Field
The invention relates to the technical field of intelligent endowment, in particular to an intelligent endowment evaluation system based on a block chain technology.
Background
With the aging situation of the population in China becoming more and more severe, the advantage of the population's dividend becomes weaker and weaker. The traditional mode of relying on the old care of children has a plurality of problems which are mainly reflected in that: 1. most old people do not have the consciousness of checking bodies regularly and cannot find some fatal diseases in time at the early stage, so that the old people cannot be treated effectively and even endanger the lives of the old people; 2. the medical history and body index information of the old people are incomplete, or doctors do not know the medical history of the old people, and inaccurate judgment can be made on the body condition of the old people; 3. the psychological and mental requirements of the old can not be satisfied and the body can not be effectively exercised. The solitary old people are enabled to be more solitary, and the life of the solitary old people has no color; 4. the profession degree of the endowment service team is not high, a large number of professional maintenance personnel lack professional training or certification, many old people only satisfy the desire of satiety but neglect the needs of the body on the demand of three meals a day, the nutrition of the body is unbalanced, the mode of the internet plus a block chain is gradually mature, an intelligent endowment platform appears, the platform is a sensor network system and an information platform facing the old at home, communities and endowment institutions, and real-time, quick, efficient and low-cost endowment service is provided on the basis of the intelligent endowment service platform, and the purposes of internet of things, interconnection and intellectualization are achieved.
Traditional wisdom endowment contains each item service such as: medical treatment, shopping, amusement and food and beverage, because the project kind is different, inconvenient direct comparison, the quality of every service can not be guaranteed to the platform, consequently lack the evaluation system and assess every project, traditional aassessment can only follow the quality of service of single old man to the evaluation of service, lack the evaluation model of system, lead to the evaluation result unfair, and because the data bulk is more and the distribution is stored in each database, it is troublesome to call data collectively, influences the high efficiency of data evaluation.
Disclosure of Invention
The invention aims to solve the problems that the intelligent endowment platform cannot systematically evaluate the quality of each service item and data calling is inconvenient, and provides the intelligent endowment evaluation system based on the block chain technology.
The intelligent old-age care assessment system based on the block chain technology comprises a user layer, an application layer and a data layer;
the user layer is used for enabling a user to enter the application layer through a web interactive interface to perform function interaction;
the application layer comprises intelligent model evaluation, data statistics record, risk early warning management, node management, user management and system management, and functional services are provided for the whole system by calling data of the data layer, wherein the intelligent model evaluation is used for intelligently evaluating various services in intelligent endowment, the data statistics record is used for counting evaluation results each time and drawing a chart, the risk early warning management is used for early warning the intelligent endowment services with lower evaluation, the node management is used for managing a database accessed to the application layer, the user management is used for managing users, and the system management is used for configuring system parameters and managing system operation;
the data layer is used for providing service evaluation data to the application layer.
Preferably, the data layer comprises a medical evaluation database, an entertainment evaluation database, a shopping evaluation database, a catering evaluation database and a neural network call; medical evaluation data of intelligent old age is stored in the medical evaluation database; the entertainment evaluation database stores entertainment evaluation data of intelligent endowment; shopping evaluation data of intelligent endowment are stored in the shopping evaluation database; the catering evaluation database stores catering evaluation data of intelligent endowment, and the neural network can call the data in each database for the application layer to use.
Preferably, the data in each database of the data layer are provided by an intelligent endowment system, and the intelligent endowment system comprises a medical subsystem, an entertainment subsystem, a shopping subsystem and a catering subsystem.
Preferably, the medical subsystem comprises online medical treatment and customized medical treatment, and the old care personnel score medical conditions online and store the scores into a medical treatment database; the entertainment subsystem comprises entertainment equipment intelligent management and entertainment demand intelligent management, and old people score entertainment conditions on line and store the scores into an entertainment database; the shopping subsystem comprises intelligent shopping and customized shopping, and the old-aged people score shopping conditions on line and store the scores into a shopping database; the catering subsystem comprises intelligent catering customization, and the old people score the catering conditions on line and store the scores into a catering database.
Preferably, the step of evaluating the intelligent model comprises:
establishing an evaluation model, namely firstly carrying out system modeling and constructing a proper fuzzy neural network, wherein the network can call data from each database of a data layer;
the evaluation model training, namely firstly carrying out initialization processing on the fuzzy neural network and then training the fuzzy neural network;
and evaluating the evaluation model, calling data in the database through the trained neural network, and sending the data to the evaluation model for evaluation.
Preferably, the evaluation model establishes an evaluation grade according to the weight of each service item, and the grade to which the result belongs is obtained by inputting the data called by the database into a weight calculation formula.
Compared with the prior art, the invention has the beneficial effects that:
1. through the establishment of the online evaluation port, the senior citizen can grade each service subsystem in the intelligent senior citizen system, the grade result is stored in each database of the data layer, and the grade data in the database is called through the establishment of the intelligent evaluation model to carry out intelligent evaluation, so that each service in the intelligent senior citizen system is evaluated and is reflected in a chart form, and the user can visually see the quality of each service item conveniently.
2. The data in each database are called through the neural network, the calling is more real-time and rapid, and the intelligent evaluation model is established, trained and evaluated by means of the neural network, so that the accuracy and the efficiency of the intelligent evaluation model are guaranteed.
Drawings
FIG. 1 is a schematic diagram of the overall system framework of the present invention.
FIG. 2 is a diagram of a functional module of the intelligent endowment system according to the present invention.
FIG. 3 is a flow chart of the intelligent evaluation model building process 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. 1-3, the system for intelligent endowment assessment based on block chain technology includes a user layer, an application layer and a data layer; the user layer is used for enabling a user to enter the application layer through a web interactive interface to perform function interaction; the application layer comprises intelligent model evaluation, data statistics record, risk early warning management, node management, user management and system management, and functional services are provided for the whole system by calling data of the data layer, wherein the intelligent model evaluation is used for intelligently evaluating various services in intelligent endowment, the data statistics record is used for counting evaluation results each time and drawing a chart, the risk early warning management is used for early warning the intelligent endowment services with lower evaluation, the node management is used for managing a database accessed to the application layer, the user management is used for managing users, and the system management is used for configuring system parameters and managing system operation; the data layer is used for providing service evaluation data to the application layer.
The data layer comprises a medical evaluation database, an entertainment evaluation database, a shopping evaluation database, a catering evaluation database and a neural network call; medical evaluation data of intelligent old age is stored in the medical evaluation database; the entertainment evaluation database stores entertainment evaluation data of intelligent endowment; shopping evaluation data of intelligent endowment are stored in the shopping evaluation database; the catering evaluation database stores catering evaluation data of intelligent endowment, the neural network is called to call the data in each database for an application layer to use, the data in each database of the data layer is provided by an intelligent endowment system, the intelligent endowment system comprises a medical subsystem, an entertainment subsystem, a shopping subsystem and a catering subsystem, the medical subsystem comprises online medical treatment and customized medical treatment, and the endowment personnel score the medical condition online and store the score in the medical database; the entertainment subsystem comprises entertainment equipment intelligent management and entertainment demand intelligent management, and old people score entertainment conditions on line and store the scores into an entertainment database; the shopping subsystem comprises intelligent shopping and customized shopping, and the old-aged people score shopping conditions on line and store the scores into a shopping database; the catering subsystem comprises intelligent catering customization, and the old people scores the catering conditions on line and stores the scores into a catering database
The evaluation step of the intelligent model evaluation comprises the following steps:
establishing an evaluation model, namely firstly carrying out system modeling and constructing a proper fuzzy neural network, wherein the network can call data from each database of a data layer;
the evaluation model training, namely firstly carrying out initialization processing on the fuzzy neural network and then training the fuzzy neural network;
and evaluating the evaluation model, calling data in the database through the trained neural network, and sending the data to the evaluation model for evaluation.
And the evaluation model establishes evaluation grades according to the weights of all service items, and the grade to which the result belongs is obtained through a data input weight calculation formula called by the database.
The working principle of the invention is as follows: by arranging the online evaluation port, the senior citizen can grade each service subsystem in the intelligent senior citizen system, the grade result is stored in each database of the data layer, and the grade data in the database is called for intelligent evaluation by establishing an intelligent evaluation model, so that each service in the intelligent senior citizen system is evaluated and is reflected in a chart form, and the user can visually see the quality of each service item; the data in each database are called through the neural network, the calling is more real-time and rapid, and the intelligent evaluation model is established, trained and evaluated by means of the neural network, so that the accuracy and the efficiency of the intelligent evaluation model are guaranteed.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (6)
1. Wisdom endowment evaluation system based on block chain technique, its characterized in that: the system comprises a user layer, an application layer and a data layer;
the user layer is used for enabling a user to enter the application layer through a web interactive interface to perform function interaction;
the application layer comprises intelligent model evaluation, data statistics record, risk early warning management, node management, user management and system management, and functional services are provided for the whole system by calling data of the data layer, wherein the intelligent model evaluation is used for intelligently evaluating various services in intelligent endowment, the data statistics record is used for counting evaluation results each time and drawing a chart, the risk early warning management is used for early warning the intelligent endowment services with lower evaluation, the node management is used for managing a database accessed to the application layer, the user management is used for managing users, and the system management is used for configuring system parameters and managing system operation;
the data layer is used for providing service evaluation data to the application layer.
2. The system of claim 1, wherein the system comprises: the data layer comprises a medical evaluation database, an entertainment evaluation database, a shopping evaluation database, a catering evaluation database and a neural network call; medical evaluation data of intelligent old age is stored in the medical evaluation database; the entertainment evaluation database stores entertainment evaluation data of intelligent endowment; shopping evaluation data of intelligent endowment are stored in the shopping evaluation database; the catering evaluation database stores catering evaluation data of intelligent endowment, and the neural network can call the data in each database for the application layer to use.
3. The system of claim 2, wherein the system comprises: data in each database of the data layer are provided by an intelligent endowment system, and the intelligent endowment system comprises a medical subsystem, an entertainment subsystem, a shopping subsystem and a catering subsystem.
4. The system of claim 3, wherein the system comprises: the medical subsystem comprises online medical treatment and customized medical treatment, and the old care personnel score medical conditions online and store the scores into a medical treatment database; the entertainment subsystem comprises entertainment equipment intelligent management and entertainment demand intelligent management, and old people score entertainment conditions on line and store the scores into an entertainment database; the shopping subsystem comprises intelligent shopping and customized shopping, and the old-aged people score shopping conditions on line and store the scores into a shopping database; the catering subsystem comprises intelligent catering customization, and the old people score the catering conditions on line and store the scores into a catering database.
5. The system of claim 1, wherein the system comprises: the evaluation step of the intelligent model evaluation comprises the following steps:
establishing an evaluation model, namely firstly carrying out system modeling and constructing a proper fuzzy neural network, wherein the network can call data from each database of a data layer;
the evaluation model training, namely firstly carrying out initialization processing on the fuzzy neural network and then training the fuzzy neural network;
and evaluating the evaluation model, calling data in the database through the trained neural network, and sending the data to the evaluation model for evaluation.
6. The system of claim 5, wherein the system comprises: and the evaluation model establishes evaluation grades according to the weights of all service items, and the grade to which the result belongs is obtained through a data input weight calculation formula called by the database.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040059628A1 (en) * | 2002-05-27 | 2004-03-25 | Stephen Parker | Service assessment system |
| CN109147924A (en) * | 2017-06-16 | 2019-01-04 | 四川科技职工大学 | One kind being based on the endowment comprehensive service platform of " data framework " |
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- 2020-03-26 CN CN202010224103.1A patent/CN111415098A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040059628A1 (en) * | 2002-05-27 | 2004-03-25 | Stephen Parker | Service assessment system |
| CN109147924A (en) * | 2017-06-16 | 2019-01-04 | 四川科技职工大学 | One kind being based on the endowment comprehensive service platform of " data framework " |
Non-Patent Citations (3)
| Title |
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| 屈巍;矫培艳;李晖;: "基于物联网的智慧养老社区系统" * |
| 谢晓珊: "颐老会智慧养老护理管理系统的研究与实现" * |
| 高承芳;: "基于模糊神经网络的信息系统客户服务感知评价研究" * |
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