124 results about "Big data cloud computing" patented technology

The invention discloses a hybrid cloud computing system based on a cloud bus and a realization method of the hybrid cloud computing system. The system is based on a local private cloud, one or more public clouds are integrated, the internal constitution of the local private cloud is consistent with that of the public cloud, both the internal constitution of the local private cloud and the internal constitution of the public cloud comprise an infrastructure, a virtualization layer, a cloud platform layer, a cloud bus layer, a cloud application layer, a management center and a storage center, wherein the hardware resources on a bottom layer are grouped into a virtual cluster through the infrastructure and the virtualization layer so as to provide different virtual resources to the superior layer; the cloud platform is used for operating a web application program or a service and utilizing an open interface to carry out the secondary development and application integration; and the cloud bus layer is used for managing and monitoring various services on the cloud platform layer and is a hub for connecting the cloud application layer and the cloud platform layer, and the cloud bus layer is established on the basis of SOA (service oriented architecture) concept and comprises a control bus, a plurality of node buses and an adapter. Due to the adoption of the hybrid cloud computing system, the migration of the existing IT (internet) environment of an enterprise to a cloud computing environment can be accelerated, the investment can be reduced, and the resource can be adequately utilized.

The present invention discloses a regional complex distribution network dispatch control management system based on a virtual power plant, and belongs to the technical field of dispatch control management. Aiming at the problem that distribution network control becomes increasingly complex due to increasing complexity of the structure in a distribution network, sharply increased number of dispersed and distributed power supplies, increasingly growing capacity / power ratio and complex and varied regional distribution networks, the regional complex distribution network dispatch control managementsystem based on a virtual power plant is developed. The system mainly includes the construction of different types of virtual power plants and a big data cloud computing platform at a regional leveldistribution network dispatch center. By developing the dispatch control management system for a regional power grid, a complex distribution network can be connected in the form of a virtual power plant for unified coordination and optimization management, and the system is a new type of complex distribution network management mode. The regional complex distribution network dispatch control management system can be widely applied to distributed new energy-rich areas, and is of practical significance for developing virtual power plants, developing renewable green energy and achieving energy transformation.

The invention relates to the technical field of agricultural monitoring, in particular to an intelligent agricultural monitoring system based on NB-IoT, comprising an environment monitoring sensor, amainboard unit, an Internet of Things platform, a webpage monitoring platform, a mobile phone APP and a power supply unit, wherein the environment monitoring sensor is connected with a central processing unit by virtue of an I2C bus, the central processing unit is connected with the Internet of Things platform by virtue of an NB-IoT communication module, the central processing unit is respectivelyconnected with a Beidou positioning module and a debugging interface module, the Internet of Things platform is respectively connected with the webpage monitoring platform and a mobile terminal, andthe mainboard unit is connected with the power supply unit. On basis of NB-IoT communication, power consumption is extremely low, installation is easy, and energy conservation and environment protection are realized, and matched electric power installation investment is eliminated; a low-delay and high-reliability information transmission technology is beneficial to large-scale investment; manufacturing cost and service cost are extremely low, and cost performance is high; various sensors are flexibly expanded, and customizable expansion is realized; and by virtue of big data and cloud computing, functional agricultural data operation is realized.

The invention provides an electronic commerce goods recommendation method based on large data multiple labels. The method comprises the steps of (1) collecting user data, (2) constructing a purchase behavior model, (3) analyzing the purchase tendency of the user through data, (4) pushing goods, (5) carrying out secondary collection of user data, through a large data cloud calculating platform, recording the click and purchase information of a user after pushing and the browse time information of different goods pages, and carrying out characteristic acquisition and data acquisition of the data, and (6) carrying out the secondary pushing of the goods, and pushing corresponding goods to the user according to the click and purchase information of the user after pushing and the browse time information of different goods pages. Compared with the prior art, the method has the advantages of user shopping can be guided, a user shopping experience is satisfied, and the method has an important effect in improving the clicking rate and popularity of an electronic commerce website.

The invention discloses an intelligent fresh-air control system based on big data cloud computing. The intelligent fresh-air control system comprises a cloud server, an intelligent master control device and a plurality of monitoring devices installed in a fresh air device. The monitoring devices are used for collecting related data of the installation environment of the fresh air device and transmitting the related data to the intelligent master control device. The intelligent master control device is used for controlling the monitoring devices and transmitting the data received from the monitoring devices to the cloud server. The cloud server is used for receiving and storing the related data collected by the monitoring devices. The intelligent fresh-air control system further comprises a communication device in communication with the cloud server. A user checks the data stored in the cloud server through the communication device. According to the intelligent fresh-air control system, all-around online monitoring and early warning can be carried out on the data such as temperature values, humidity values, methanal values, PM2.5 values and carbon dioxide values of the fresh air device, and meanwhile real intelligent online monitoring is achieved in cooperation with cloud computing and big data analysis.

The invention provides a robot cloud platform based on big data cloud computing support and a working method, and the platform comprises a resource layer used for collecting robot data and uploading the robot data to a platform layer through an edge computing layer; a platform layer which is used for processing and storing the data, comprises a big data storage service module, a big data analysis service module, an algorithm engine module and a basic management service module, and is used for providing big data storage service, big data analysis service, an algorithm engine and basic management service; and an application layer comprising a cloud service platform and a mobile application side, and a user provides various analysis application functions and remote monitoring based on the robot for the user by calling various services of the platform layer. The invention has the advantages that an equipment layer supports data access of various robots at home and abroad, the edge computing layer can perform equipment authentication to prevent malicious connection, data preprocessing reduces cloud processing pressure, and data encryption and breakpoint resume guarantee data transmission safety and transmission stability.

The invention discloses a cloud computing system with a data cube storage index structure, which includes one or more management nodes and one or more computing and storage nodes (data nodes). A data cube index structure is established and applied in the system in a distributed manner during data creation and inquiry; one or more keyword fields are set for standardized data during data creation and storage; indexes for the different keyword fields are respectively created; an independent B+ tree structure is generated from each index; and all the B+ tree structures are stacked and form the complete data cube structure with a global data table. Through the data cube storage index structure, accurate retrieval of positioning data in a mass data cloud computing system can be conveniently and rapidly achieved.

The present invention discloses a method for rapidly configuring virtual machine resources in a cloud computing data center. The method comprises: a resource controller receives a virtual machine job request from a first application server and responds to the request: if the request is received, a physical server cluster which is optimal in queue is selected according to a job type of the request and a virtual machine job is issued to the physical server cluster, and if the request is rejected, reject information is returned; the physical server cluster receivs the virtual machine job from the resource controller and enqueues the job according to tolerable latest job completion time; and when a dispatching cycle of the physical server cluster is reached, a resource optimization strategy of sequentially dispatching in a non-preemptive queue is adopted to dispatch the virtual machine job. One single virtual machine job is sequentially subjected to the steps; and virtual machine jobs in different steps can be processed simultaneously. According to the method for rapidly configuring the virtual machine resources in the cloud computing data center, which is provided by the present invention, the configuration speed of the virtual machine resources is improved, so that the data center can meet service quality requirements of big data cloud computing.

The invention provides a big data cloud computing service-based steering wheel-free intelligent network reservation car system and an operation method. An intelligent driving system and an automatic navigation system which are connected with big data cloud computing services are arranged in an intelligent network reservation car; an intelligent robot composed of a touch screen, a mobile phone data interface or bank card interface, a camera and a voice interactive system is installed at the front of each seat; a luggage cargo monitoring camera which is connected with the intelligent robot and is used for monitoring luggage and cargo in real time is arranged in the trunk of the car; when monitoring information indicates that the trunk is opened or a passenger or a cargo owner gets off, the intelligent robot carries out real-time display or voice prompting; the intelligent driving system and the intelligent robot transmit the car use information of the passenger or cargo owner to a transport management center in real time through the Internet; the transport management center controls the intelligent driving system through the Internet to make the intelligent driving system automatically drive the intelligent network reservation car according to starting and termination paths required by the passenger or cargo owner; and the intelligent robot is connected with the transport management center in real time through the Internet and transmits the information of the interaction between the passenger or cargo owner and the intelligent robot and transportation expense settlement to the transport management center.

The invention belongs to the technical field of big data cloud computing, and discloses a distributed flow acquisition system and an edge calculation method. The method comprises the following steps:firstly, planning nodes of a distributed data acquisition system, dividing the nodes into acquisition nodes, edge nodes and cloud center nodes, and respectively installing Apache MiNiFi or Apache NiFiaccording to the hardware performance of equipment, secondly, configuring flow templates on the acquisition nodes, the edge nodes and the cloud center nodes, connecting the front and rear nodes to complete functions of data acquisition, data transmission, edge calculation and the like, and organizing all the nodes into a multi-level tree structure taking a cloud center as a root. According to themethod, an edge computing mode in an Internet of Things application scene is used for reference, a machine learning model is deployed to perform distributed parallel processing on data at a place asclose as possible to a data source, and the resource utilization rate and the data processing efficiency are improved.

The present invention discloses an intelligent parking lock system and an intelligent parking method. The intelligent parking method comprises the steps of: selecting a parking stall through application of a mobile terminal; after a positioning identification module identifies and confirms that a vehicle is in place, performing automatic locking of an intelligent parking lock; after parking in a designated space, recording parking time by a cloud management platform through the intelligent parking lock, and performing charging; after parking is end, performing vehicle movement confirmation through identification of the positioning identification module on the intelligent parking lock; and after the vehicle is moved, lifting the intelligent parking lock for standby. The intelligent parkinglock system and the intelligent parking method employ a bid data cloud calculation management platform, intelligently and remotely manage a parking lock device, monitor usage conditions of operation states of parking lock devices in real time, record and store all the related data of operation of a system, and provide sufficient data support for related activities such as manager decision, improvement of user experience by researchers; a mobile Internet and technologies related to an internet-of-things technology are employed to perform intelligent induction identification and automatic faultalarm; and moreover, the intelligent parking lock system and the intelligent parking method can achieve self-service parking and are convenient and rapid.

The invention discloses a wind power plant SCADA system based on a big data cloud computing platform and a running method of the wind power plant SCADA system. The system comprises a wind power plant side, the cloud computing platform and a centralized control center side; both the wind power plant side and the centralized control center side are connected with the cloud computing platform through the internet; the wind power plant side comprises a draught fan, a booster station, a box transformer substation, an anemometer tower, a watt hour meter, AGC, AVC, a message protection substation, fault wave recorder, a motion device, a front-arranged server, a firewall and an interchanger; the cloud computing platform comprises a big data server, an advanced application server and an interchanger; the centralized control center side comprises a network printer, a draught fan centralized control workstation, a booster station monitoring workstation, a reporting and alarming workstation and a maintenance workstation. According to the running method of the wind power plant SCADA system, a distributed data processing technology of Hadoop+MapReduce is adopted, the space for data storage is drastically increased, the cost for data storage is also lowered to the greatest extent, and the processing speed of the data is increased fundamentally at the same time.

The invention discloses a charging pile back-stage management system based on big data cloud computing. The system comprises a charging strategy initial unit, a charging information receiving unit, a vehicle information receiving unit, a charging strategy updating unit and a feedback unit, wherein the charging strategy initial unit is used for generating an initial charging strategy with battery charging curves, provided by chargeable car manufacturers, as original reference; the charging information receiving unit is used for receiving charging information uploaded by a user in real time and sending the charging information to the charging strategy updating unit; the vehicle information receiving unit is used for obtaining service life period and mileage information of licensed cars provided by the user after registering and sending the information to the charging strategy updating unit; the charging strategy updating unit is used for optimizing the initial charging strategy according to the charging information uploaded by the user in real time and the service life period and mileage information of the licensed cars to obtain an updated charging strategy; and the feedback unit is used for feeding the updated charging strategy back to the user, so that the user can conduct charging management according to the updated charging strategy. The invention further provides a charging pile back-stage management method based on big data cloud computing.

The present invention is generally directed to systems and methods of providing automatic scaling pure-spot clusters. Such dusters may be dynamically rebalanced for further costs savings. In accordance with some methods of the present invention may include a method of utilizing a cluster in a big data cloud computing environment where instances may include reserved on-demand instances for a set price and on-demand spot instances that may be bid on by a user, the method including: creating one or more stable nodes, comprising spot instances with a bid price above a price for an equivalent on-demand instance; creating one or more volatile nodes, comprising spot instances with a bid price below a price for an equivalent on-demand instance; using one or more of the stable nodes as a master node; and using the volatile nodes as slave nodes.

The invention discloses a method, device and equipment for analyzing user operation behaviors and a storage medium, and relates to the technical field of computers, in particular to the fields of computer vision, intelligent search, big data and cloud computing. According to the specific implementation scheme, the method comprises the steps of obtaining an initial document object model tree snapshot of a front-end page, an operation log of a target user on the front-end page and an abnormal event log triggered by operation of the target user; restoring the operation of the target user on the front-end page and restoring an abnormal event triggered by the operation of the target user based on the initial document object model tree snapshot, the operation log and the abnormal event log; positioning an operation path of the abnormal event; and outputting an operating path. According to the implementation mode, behavior capture is carried out on the change of the front-end document objectmodel tree, and the operation path of the user can be simulated by restoring the captured change of the model tree, so that the operation behavior of the user can be visually analyzed, the use processof the user can be known, and quick response to a problem is achieved.

The invention discloses a catering food safety dynamic supervision method based on big data analysis.the method includes that data access is carried out, wherein the data access is used for accessingcatering industry data including government supervision department data, catering unit self-inspection data and social evaluation data; a big data cloud computing technology is applied to comprehensively evaluate catering units including data of AI video analysis non-standard behaviors, place environment and equipment operation Internet of Things sensing, electronic machine account data, personneltraining and self-checking implementation daily management in a certain period; and the food safety index risk factor statistics is used for performing risk classification and quantitative rating onthe accessed data according to the catering safety risk factor statistics and the established risk model to obtain a catering enterprise safety score.

The invention discloses a self-service tax registration method based on Ali cloud, which relates to an Ali cloud application technology. Industrial and commercial system data and relevant data and checking rules in a tax system are integrated in a self-service tax registration system. An Ali cloud development mode is used to extend large data cloud computing applications into tax and industry and commerce industries. A taxpayer carries out tax registration application through an external network. After industry and commerce and tax departments carry out intranet audit, the taxpayer can print a tax registration certificate and related documents on a self-service tax terminal. According to the invention, the processes of tax registration and industrial and commercial registration can be effectively reduced; the taxpayer who does not know a handling process and prepared information is prevented from repeatedly coming to a tax hall; the method has the advantages of simple operation and being fast and efficient; and more social resources are saved.

The invention discloses a safety socket for a big data cloud computing laboratory machine room. The safety socket comprises a housing, and two jacks are formed in the side wall of the housing. Placinggrooves are formed in the inner walls of the two jacks. Reeds are fixedly connected to the inner walls of the two placing grooves. A connector is fixedly embedded in the right side wall of the housing. A reinforcing mechanism is arranged in the housing. The reinforcing mechanism comprises two copper sheets, the two copper sheets are respectively positioned on the inner walls of the two placing grooves, and the side walls of the two copper sheets are jointly connected with a solenoid through wires. An inner cavity and a negative pressure cavity are formed in the housing, the solenoid is located in the inner cavity, the inner wall of the negative pressure cavity is elastically connected with a permanent magnet plate through a plurality of tension springs, and a negative pressure air channelis arranged in the side wall of the negative pressure cavity in a communicated mode. A control mechanism is arranged in the housing. A plug can be effectively prevented from loosening, and the temperature in the socket can be prevented from being too high to burn out an electric appliance.

The invention discloses a big data cloud calculating operation system and a method. A big data operation system and a cloud calculating server group are included. The operation system comprises a processing flow integration module, a historical data acquisition module, a real-time data acquisition module, a storage module and a data sharing module. The processing flow integration module is used for processing data in a centralized mode. The historical data acquisition module is used for collecting non-transaction data. The real-time data acquisition module is used for collecting instantaneously-generated service data in real time. The storage module is used for storing collected historical data and the service data. By using the big data system of the invention, a using threshold of the big data system is greatly reduced, and big data correlation resources in an organization can be conveniently shared so that the system is a set of sustainable and accumulated big data system; and the cloud calculating server group is used to guarantee correctness of a data transmission process and data privacy, and high reliability of normal work of the server group is ensured.

The invention discloses a cardiovascular disease early warning system. The system runs in a server, the server is connected with a hospital information system, and the hospital information system is connected with a monitoring system; the monitoring system transmits collected medical data to the hospital information system, and the cardiovascular disease early warning system comprises a data collection module, a data analysis module and a disease early warning module. According to the cardiovascular disease early warning system, by combining with the physical state, the vital sign and the self-condition of a patient based on an anxiety value, a data often model of an individual in each kind of states is built through big data cloud computing, the patient is monitored in the later period, obtained big data is subjected to contrastive analysis with the often model, symptoms of cardiovascular diseases can be effectively checked in advance, the health scheme guidance is provided, and risks caused by the cardiovascular diseases can be further reduced.

The present invention relates to a precise dynamic outburst prevention method based on the transparent space geophysics, and belongs to the field of mines. The method comprises: using the theoreticaltechnology of the transparent space geophysics to establish a spatial digital analysis model, combining with the modern high-precision geological prospecting technology and equipment to precisely identify and classify the regional geological structure of the mine, and determining the influence of coal and gas outburst key geological bodies on the gas occurrence; using a big data cloud computing technology to analyze the correlation between various factors, and precisely predicting the multi-indicator coupling of outburst risks in the coal seam area; and analyzing the correlation between data information, and establishing a scientific gas drainage model for mines according to specific procedures to achieve optimal scientific drainage of mines. According to the method provided by the presentinvention, parameters of each link in the outburst prevention process are dynamically managed in an online manner, comprehensive analysis is carried out in real time, the laws of coal and gas outburst are accurately grasped, and multiple precise measures are provided for dynamic outburst prevention, so that blindness of outburst prevention work is reduced, and the costs of outburst prevention engineering are saved.

The invention relates to a digitalization ultrasonic kinetocardiogram report automatic management method and a system. The system comprises five modules which are a photographing scanning assembly, an optical character recognition assembly, an electronic edition report reconstruction and presentation assembly, and a report filing management assembly; the method comprises a first processing of the ultrasonic kinetocardiogram and a second processing of the ultrasonic kinetocardiogram. The system and the method are advantageous in that the system and the method can be widely applied to the archiving, transmission, classification and comparison of various inspection reports (such as vascular ultrasound report, various inspection reports and the like) mainly based on objective indicators and long-term warning and disease management of large groups of large-scale data cloud, both to achieve the commonality of the results of various hospital tests, reduce medical costs, save medical resources, and to fulfill a network medical mode which integrates big data cloud calculation disease pre-warning and disease individual management.

The invention discloses a navigation system device based on a panoramic map. The navigation system device comprises a display terminal, a radar system navigation module, a rear panoramic camera, an automatic driving module, a front panoramic camera, a reflective mirror camera and a master control device. The navigation system device adopts the panoramic cameras, can check the surrounding road conditions at any time and record the road conditions in the system; the navigation system device is provided with a radar system which accurately judges the the surrounding vehicle distance, identifies vehicles with dangerous vehicle speed, and gives the driver a safest route to avoid vehicle collision through large data cloud computing; the navigation system device adopts the automatic driving module, so as to control the vehicle speed to accurately avoid a moving car; the navigation system device can automatically collect the routes which have newly appearing conditions that are likely to affect traffic, prevent accidents, record the traffic jam situation of the route and give a prompt. The navigation system device improves the accuracy of service through human-computer interaction and language communication, and is more humanized.

The invention provides a dynamic physical examination method and an automatic corporeity evaluation system. The dynamic physical examination method includes two modes: 1) measuring blood oxygen, blood pressure and heart rhythm by enabling a person to hold breath; 2) measuring the blood oxygen, the blood pressure and the heart rhythm by enabling the person to continuously squat. Normal value of a static examination is used as a reference base line of a dynamic physical examination performed by using the dynamic physical examination method, and therefore heart and lung functions and a circulatory system of the person under pressure are evaluated. A breath holding examination aims at examining high value of the blood pressure and heart rhythm changes under the circumstance of organ tissue ischemia, and a continuous squatting examination aims at examining high value of the heart rhythm and blood pressure changes under the circumstance of exercise. The automatic corporeity evaluation system analyzes corporeity and potential disease risk of the person by combining dynamic physical sign measurement value with static physical examination normal value and using front end embedded software and background big data cloud computing. Then, corresponding health advice and corresponding medical service recommendation are provided.

The invention discloses a big data cloud computing platform serving enterprise policy planning, and relates to the technical field of cloud computing platforms. The big data cloud computing platform comprises an enterprise development basic platform layer, an enterprise development analysis layer, a policy planning application layer, a policy planning presentation layer and a policy operation andmaintenance management layer, wherein the enterprise development basic platform layer comprises a cloud storage, a cloud host and enterprise planning network resources; the enterprise development analysis layer comprises a grouping statistics module, a comparative analysis module, a trend prediction module and a correlation analysis module; the policy planning application layer comprises a management staff application layer, a basic staff application layer and a client application layer; the policy planning presentation layer comprises a mobile terminal and a PC terminal; and the policy operation and maintenance management layer comprises a deployment configuration module and a polling control module. Business information of enterprises is subjected to statistical analysis by utilizing thegrouping statistics module and the comparative analysis module; and by utilizing intelligent cooperation of the management staff application layer, the basic staff application layer and the client application layer, stable development of the enterprises is ensured.

The invention provides an unmanned body building analysis method based on artificial intelligence, and relates to the field of unmanned body building technology. The method comprises the following steps of S1, defining a motion index analysis rule based on human body key points, and generating a rule table; S2, acquiring a motion image of a sporter, and acquiring framework point information of thesporter; S3, inputting the acquired framework point information into a rule table; and S4, determining whether an error value between the generated framework point information and the data in the rule table is lower than a preset threshold, if yes, determining a fact that the action is qualified, and otherwise, outputting error framework point information. According to the unmanned body buildinganalysis method, by means of technologies such as artificial intelligence, big data, cloud computing and body feeling control, health intelligent body building guidance is generated for aiming at a household scene, thereby realizing identification, tracking and positioning of mass motion video image data for realizing management. Body building guidance such as motion exercise, body building guidance and sports rehabilitation is researched. Furthermore multifunctional and intelligent sports body building analysis and guidance are performed.

The invention provides an intelligent management method for urban parking space resources, and belongs to the technical field of automobile traffic management. The intelligent management method comprises the following steps of: superposing all public parking space resources in a control area on an electronic map by taking a city as a unit; installing car positioners on cars in the control area, and displaying the driving and parking states of each car on the special electronic map under the technical support of real-time centimeter-level positioning service provided by the cooperation of a Beidou III and a ground station network, and the Internet; calculating and recording the instant parking states of the cars through a GIS system and big data cloud computing; and automatically inputtingthe parking information of the cars into the mobile phones of car owners who pay money through mobile payment. According to the method of the invention, a physical world of an urban parking space resource entity is changed into a data world, foreground management is changed into background management, and timing charging of public parking spaces in an urban management and control area and automatic management of illegal parking are realized.

The invention relates to a traffic management and control service index evaluation method. The method comprises the following steps: step a, constructing a traffic management and control service indexsystem of an urban traffic system according to a selected traffic management service index and a traffic control service index; b, designing a regional traffic and urban traffic big data cloud computing platform; and c, based on a regional traffic and urban traffic big data cloud computing platform, modeling is carried out according to traffic management and control service index association andevaluation, and evaluation of the service level and the service capability of the traffic system is formed. According to the invention, rapid development of urban traffic and social economy can be accelerated, the urban traffic capacity and the living standard of residents are optimized and improved, an urban traffic system construction and development target is scientifically decided, and urban traffic development and countermeasures are more accurate and effective.

The invention relates to a network robot which is a robot network and is used for constructing the robot network, and belongs to the field of robots. The network robot is composed of an intelligent mobile phone, a three-axis tripod head stabilizer, a replaceable expansion cover plate, a network camera, an intelligent loudspeaker box, a display screen, a mechanical arm, a bearing shell, a walking mechanism, a driving motor, a speed reducer, a remote control and driving module, an expansion frame, a mechanical telescopic transmission mechanism, a control end intelligent mobile phone, a remote controller, a sensor, a ground gripping supporting mechanism, an automatic navigation and control module, a dual-mode router and the like; and social resources are fully utilized, and the robot network is established under the support of a 5G high-speed mobile network, artificial intelligence, big data, cloud computing and the Internet of Things technology, so that virtual avatar, virtual arrival, remote interaction and a home intelligent center of people are realized, thousands of novel applications are created, and the robot network is used for constructing an intelligent and digital society of social production and life and all-industry full-scene application.

The invention discloses an intelligent mouse capable of evaluating body health. The intelligent mouse capable of evaluating the body health comprises software algorithm design and appearance design. The intelligent mouse comprises two measuring modules for monitoring the situation changes of three kinds of physical sign data of the body at real time, and the situation changes are used for judging the health condition and the emotion of the body. The mouse operation frequency of the user is combined with the intelligent mouse to reinforce the analysis precision. The intelligent mouse capable of evaluating the body health analyzes the user body health trend through continuously sampling in long time and combining with background big data cloud computing and provides the corresponding health tips for the user. Because a drive program is mounted in a local machine connected with the mouse, the computing function and the data storage function can be set at the computer end, so that the hardware requirement for the intelligent mouse is lowered, the cost is low, and the price is low.