69 results about "Cloud computing big data" patented technology

The invention discloses an intelligent electrical equipment environment monitoring system based on cloud computing and big data analysis. The system comprises a cloud server, an intelligent master control device, monitoring devices and communication equipment communicating with the cloud server, wherein the monitoring devices are used for acquiring related data of an electrical equipment environment and transmitting the 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 of the electrical equipment environment; a user accesses the cloud server through a mobile phone or a computer and then controls the master control device and the monitoring devices remotely. The system depends on cloud computing to perform big data analysis on online meteorological information, real-time data and historical data, intelligently monitors the monitoring devices of all nodes, evaluates the monitoring effectiveness, analyzes potential risks effectively and solves problems by which people are puzzled for many years about outdoor electrical equipment microenvironments, online micrometeorology monitoring, real-time intelligent control and the like.

The invention provides an assembly type concrete whole-process monitoring system based on the Internet of Things. An Internet of Things model conforming to assembly type concrete development is established, a perceiving structure in the assembly type concrete producing and constructing process is constructed, a low-cost and environmental-friendly transmission network is built and a cloud calculation big data service platform of the assembly type concrete and an intelligent decision and information feedback system are built according to the whole production process of pre-production, during-production, post-production and operation of the assembly type concrete based on the technologies of sensors, radio frequency, wireless communication and the like for the problems of quality safety and logistics tracing in the links of manufacturing, transporting and installing of the assembly type concrete. Quality monitoring and controlling over the production process, logistics tracing on members and dynamic monitoring and controlling over the hoisting installation process are achieved, and the whole process from manufacturing to completing of the assembly type concrete is monitored, controlled and traced.

The invention provides a smart city management system based on a cloud platform, and the system comprises: an infrastructure layer which is used for providing a system data access service and city resource data collection, and storing the city resource data in a data sharing layer in real time; a basic service layer which is used for developing and operating a platform as a service to be providedfor a user; adata sharing layer which is used for gathering various basic service system data to form massive traffic data, forming a comprehensive information sharing database by utilizing a cloud computing big data processing technology, breaking through information island limitation and realizing data gathering and sharing; an application integration layer which comprises application managementand application configuration management; and a cloud service platform which is used for performing security analysis through an application program interface and a communication network according tothe acquired data of the infrastructure layer. Data in all fields of city management are analyzed and interacted through the cloud technology, modular integrated management of the smart city is achieved, all modules are clear in function, management is more reasonable and perfect, multiple services needed by residents in the smart city can be provided, the life quality of the residents can be improved, and construction of the smart city is facilitated.

The invention discloses a semantics-based music retrieval method, belongs to the field of cloud computing big data, and solves the problem of lack of effective automatic semantic tagging and interactive retrieval in a Chinese song data set. According to the technical key points, starting from original audio bottom features, audio contents are mapped to a tag-based semantic feature space by utilizing a semantic tagging model. The effects are that a system can obtain a user retrieval intention more naturally and accurately, so that a user can obtain better retrieval experience and conveniently find and discover wanted songs.

The invention discloses an automatic nosql cluster configuration system and method based on cloud computing. The automatic configuration system comprises a decision analysis module, a cloud communication module, an nosql management module, a cluster monitoring module and a cloud platform, wherein the cluster monitoring module acquires motion state parameters of an nosql cluster in real time, sends the parameters to the decision analysis module for decision analysis and sends a command for adjusting the nosql cluster to the nosql management module according to the analysis result, and the nosql management module configures the adjusted nosql cluster. With the adoption of the system and the method, high concurrency, extendibility and dynamic scalability required by storage and management of cloud computing big data in the prior art are realized, load condition changes can be responded dynamically, burdens of management staff can be reduced, and the utilization rate of system resources can be increased.

The invention belongs to the technical field of intelligent management, and relates to a cloud platform management system for a smart community. The system comprises a public security cloud service subsystem, a street cloud service subsystem, a property cloud service subsystem, a resident cloud service subsystem and a house renting cloud service subsystem which are in network connection to form the cloud platform management system. Cloud computing, big data and Internet of Things technologies are adopted, so that integration and analysis of community front-end management system data and modular management of multiple subsystems are achieved; artificial intelligence, deep learning and other technologies are adopted, convenience and resident-benefiting services are provided for community residents, a comfortable ecological environment is created, and a sustainable smart community is created; and meanwhile, accurate service is provided for the residents, and management is carried out in the service; through information sharing and resource integration, transformation and upgrading of community management are realized.

The invention is applicable to the technical field of data structures in cloud computing, and provides a data structure based on a cloud computing database system. The data structure comprises a primary key and a data sheet, wherein the primary key is used for storing data information with the unique identification in a binary code form and serves as a retrieval index; the data structure further comprises a primary key control module which is used for transforming data containing the time attribute in data information of the primary key into binary codes and storing the binary codes into the primary key in a hash distribution way. According to the design method and the system of the data structure, the primary key structure of transaction data and statistical data is the core of the data structure, and storage and retrieval efficiencies of a big data system during cloud computing can be greatly improved.

The invention relates to a method for protecting the privacy of cloud computed big data. The method comprises the following specific steps of: firstly, blocking big data of a cloud tenant according to a logic sequence number; then encrypting part of key privacy data blocks; next, encrypting path mapping formed after data storage in the second step; and finally, encrypting cloud data storage path mapping in the third step by a data owner. Compared with the prior art, the method is more suitable for protecting the privacy of the cloud big data, and data blocking processing can greatly improve processing efficiency; validity of data safety processing is improved, and the problems of low efficiency and even unavailability, which are generated due to encryption and decryption aiming at the big data are avoided; blocked and distributed storage of privacy data solves the problem that an illegal service provider threatens the tenant due to the case of owning complete data; and blocked storage and data backup improve usability, safety and robustness of the big data in the cloud computing process.

The invention provides cloud computing big data privacy protection method. The method comprises the following steps: deploying a plurality of authentication servers in a cloud storage platform, and performing graded key distribution and feature authentication affair; and maintaining a global user feature list, and setting an authorization reading strategy and a constraint control strategy by the authentication servers. By adoption of the cloud computing big data privacy protection method, the secure strategy reading control of the environment and the strategy constraint is enhanced, the computing cost of a writing user is reduced on the premise of ensuring the security, and the application demands of cross-cloud and cross-grade data strategies of all types are satisfied.

The invention discloses a characteristic collection and analysis system based on a wearable device. The system comprises the wearable device, a wireless networking module and a cloud computing big data service module. The wearable device is used for collecting data information of a target object. The wireless networking module is used for sending data information collected by the wearable device to the cloud computing big data service module and sends a decision obtained after the cloud computing big data service module processes the data information to the wearable device. The cloud computingbig data service module stores various data, analyzes and processes the received data information collected by the wearable device, makes a decision result and sends the decision result to the wearable device. A target object is collected actively by the wearable device and the cloud computing big data service module can identify the target rapidly and accurately, so the system is reliable in performance, many in application scene and high in intelligence degree.

The embodiment of the invention provides a virus defense system for uploading cloud computing big data, virus defense for uploading data of large-scale cloud computing cluster server is achieved, and safety and efficiency of the system are ensured. The virus defense system for uploading the cloud computing big data comprises at least one cloud computing server and at least one PC and further comprises a virus scanning server which is arranged on the connecting access point of the at least one PC and the at least one cloud computing server, the virus scanning server scans received data files and judges whether the data files come from the PC which has uploaded data files within a period of time, if not the data files are scanned, the data files carrying viruses are abandoned, and the data files without the viruses are uploaded; if yes, the data files are uploaded and then scanned, moreover, the data files carrying the viruses are deleted, and the data files without the viruses are kept.

The invention provides a public agency energy consumption monitoring method based on a cloud computing large data technology. The method is based on an energy consumption monitoring platform. The system comprises a number of energy resource consumption management subsystems and a cloud platform. Each superior subsystem delivers index data to a subordinate subsystem. Each subordinate subsystem sends the counted energy source consumption data of the unit and the subordinate subsystem of the unit to the superior subsystem, and simultaneously sends the same data to the cloud platform. The cloud platform stores the data. The data are downloaded by a needing user. The subsystem comprises a statistician module, a statistical manager module and a unit manager module. According to the invention, the method has the functions of alarm, error correction reminding, task reminding and the like; when filled data exceed a set threshold, the platform reminds the user to check; when the user does not complete reporting or other tasks in time, the platform gives reminding in time; and when the energy resource consumption suddenly changes, the platform gives an alarm to a relevant manager.

The invention belongs to the technical field of intelligent internet of things, and especially relates to a bioelectrical impedance detection terminal based internet of things smart beauty treatment system. The system includes a bioelectrical impedance detection terminal based on m sequence bioelectrical impedance and an all phase FFT response algorithm, an intelligent mobile equipment terminal and an internet platform based on cloud computing and big data; the bioelectrical impedance detection terminal is a wearable structure, and is in communication connection with the intelligent mobile equipment terminal; the bioelectrical impedance detection terminal has a sensitive metal probe and can accurately collect data; and an independent sensing system is arranged in the bioelectrical impedance detection terminal. The wearable bioelectrical impedance detection terminal based on the m sequence bioelectrical impedance and the all phase FFT response algorithm can obtain the distribution of skin electric characteristic parameters by applying excitation current or voltage through a surface electrode array and measuring boundary voltage or current signals, and therefore, skin function characteristic data models can be rebuilt.

The invention discloses an establishment method of a music retrieval data set based on semantics, and belongs to the fields of cloud computing and big data. The method is used to solve the problem ofestablishing the music retrieval data set based on the semantics. Technical key points are crawling of Chinese song data, selection of labels and generation of a semantic vector set. An effect is thatuser retrieval intention can be more naturally and accurately acquired by the data set.

The invention discloses an intelligent finance and taxation integrated service platform based on a multi-tenant SaaS technology. The service architecture of the platform comprises a service center module, a background service engine module, a data access module, a safety guarantee module and an external system docking module. The service center module is divided into an accounting service workbench, a service workbench, a financial workbench and a tax workbench; the background service engine module associates corresponding services through rule mapping corresponding relations, and supports are provided for automatic circulation of various services; the data access module provides a data access service; the safety guarantee module provides safety guarantee service; and the external system docking module provides external system docking service. According to the invention, an intelligent finance and taxation integrated service platform based on multi-tenant SaaS is constructed based on information technologies such as cloud calculation, big data analysis and artificial intelligence, ticket finance and taxation service management integrated service is carried out for small and micro enterprises and account agencies. The efficiency improvement and cost reduction in the enterprises can be realized.

The invention discloses a cloud computing big data technology-based public institution energy consumption monitoring platform, which comprises a plurality of energy resource consumption management subsystems of all levels of units and a cloud platform, wherein each superior subsystem transmits index data to the inferior subsystem and an organization directly subordinate to the administrative region within the jurisdiction, and each inferior subsystem transmits statistic energy resource consumption data of the unit and the inferior subsystem of the unit to the superior subsystem; the same data is transmitted to the cloud platform while each level of subsystem transmits data to the superior subsystem, the cloud platform stores the data and the data can be downloaded when a user needs the data. The cloud computing big data technology-based public institution energy consumption monitoring platform has alarming, error correction reminding and task reminding functions; when the reported data exceeds a set threshold value, the platform can remind the user to inspect; when the user does not finish report or other tasks in time, the platform can remind the user in time; when the energy resource consumption condition is suddenly changed, the platform can give an alarm to related responsible persons.

The invention discloses a home intelligent elderly care service system. The system comprises an intelligent terminal, a user terminal, an emergency rescue service module, an active care service moduleand a comprehensive life care home service module, the intelligent terminal is bidirectionally and electrically connected with the user terminal, the emergency rescue service module, the active careservice module and the comprehensive life care home care service module, and the intelligent terminal comprises a server, a digital health archive library and a unit for recording the SOS alarm position of the elderly in real time. According to the system, the intelligent terminal, the user terminal, the emergency rescue service module, the active care service module and the comprehensive life care home service module are used cooperatively; by utilizing new-generation information technology products such as the Internet-of-things, cloud computing, big data and intelligent hardware, effectivedocking and optimal configuration of individuals, families, communities, institutions and health care resources can be realized, intelligent upgrading of health care services is promoted, and the quality and efficiency level of the health care services is improved.

The invention relates to a sewage processing control system and a sewage processing method. The control system comprises a data collection module, a PLC (Programmable Logic Controller), a cloud computing big data analysis platform and a communication module. The method comprises the following steps: obtaining the COD (Chemical Oxygen Demand) value of water before sewage processing, the COD value of the water in an aerobic tank and the COD value of the water after sewage processing; judging whether the COD value of the water before sewage processing is smaller than or equal to an incoming waterCOD reference value or not, whether the COD value of the water in the aerobic tank is smaller than or equal to the COD reference value in the aerobic tank or not, and whether the COD value of the water after sewage processing is smaller than or equal to an effluent COD reference value or not; if so, judging whether sewage processing is normal or not, otherwise, judging that sewage processing is abnormal, and in terms of the two abnormal situations, controlling the electrically operated valve of a medicine adding tank to be started or stopped through controlling a variable frequency fan or controlling the PLC. Through the control system, water quality can be monitored in real time so as to effectively improve the purification degree of the water quality. In addition, various pieces of monitoring data of sewage processing integration equipment can be collected so as to bring convenience for workers to carry out analysis and calling at any time.

The invention discloses fire extinguishing equipment for a cloud computing big data computer room. The fire extinguishing equipment comprises a shell, wherein a rotating cavity is formed in the shell,a storage cavity, a moving cavity and a stirring cavity are sequentially formed in the shell from top to bottom, the storage cavity, the moving cavity and the stirring cavity are all located on the right side of the rotating cavity, the storage cavity communicates with the stirring cavity through a discharging port, the moving cavity penetrates through the discharging port, and a heat conductioncavity is formed in the shell and located below the rotating cavity. According to the fire extinguishing equipment, when a fire occurs, heat is sensed through a heat conduction rod, sodium carbonate powder reacts with a ferric chloride solution to generate carbon dioxide, then the carbon dioxide is sprayed through multiple spray nozzles to extinguish the fire in time, and during fire extinguishing, the spray nozzles spraying the carbon dioxide are in a rotating state, so that the fire extinguishing range is enlarged, and the fire extinguishing effect is better.

The invention discloses a GPU resource elastic scheduling method based on a heterogeneous application platform. The method comprises the following steps: a) obtaining GPU resource utilization rate information; b) setting a trigger threshold value and the number of times; c) screening and sequencing the capacity-reducing platform queues; d) screening and sequencing the expansion platform queues; with the steps of 1) selecting a to-be-reduced platform; 2) establishing a GPU node list; 3) processing a locking state node; 4) offline the to-be-migrated node; 5) adding to a resource queue; and 6) judging whether the volume reduction is finished or not. According to the GPU resource elastic scheduling method, flexible adjustment can be conducted according to the GPU load condition of the whole platform, so that maximized utilization of platform GPU resources is achieved, scheduling of the platform is mainly achieved through an existing scheduling assembly of an adaptive platform on the lower layer, dynamic resource monitoring, information collection and execution operation issuing are achieved through interface calling. And rapid and flexible deployment and implementation of cloud computing, big data, artificial intelligence and high-performance computing scene platforms can be satisfied.

The invention discloses an urban expressway traffic information acquisition system, which comprises a data acquisition unit, a data management unit, an information processing unit, an integrated interface unit, a user application unit and a decision management unit, wherein the data acquisition unit is used for acquiring, gathering and disposing widely distributed multi-source heterogeneous mass traffic data, and the data management unit is used for distributed storage, inquiry, backup and cleansing of the data; the information processing unit is used for cleaning, analyzing and filtering the heterogeneous data to form an information item meeting the standard, and an integrated interface is used for providing standard information to a requester; the user application unit is used for publishing or acquiring the standard information through the relevant interface on a web page, deciding past paired data, disposing, analyzing and providing decision; through cloud computing, the data exchange of the national intelligent transportation system, and system interworking, interconnection and interoperability are realized by big data processing.

The invention discloses a service system for ideological education, which comprises a processor, a teacher user side, a student user side and a parent user side, and is characterized in that the processor comprises a central processing unit and a teaching management module; the teaching management module comprises an information input module, a learning guidance module, a teacher evaluation module, a student practice module, an extracurricular major counseling module, a psychological counseling module and a life care module. The information input module comprises a voice input module, a voicerecognition module, a matching module and a display module; each of the teacher user side, the student user side and the parent user side comprises an APP and a WeChat front end. The system provides related module operations for teachers, students and parents through an APP and a WeChat front-end tool, and the system analyzes student portraits through cloud computing and big data to comprehensively analyze student ideological education conditions. According to the invention, the mastering condition of theoretical knowledge of students can be known in time, the students can participate in the course process in time, and interaction among the students, teachers and parents is facilitated.

The invention discloses an image processing method, a device, equipment and a storage medium, belongs to the technical field of artificial intelligence, and particularly relates to cloud computing, big data or databases and the like in the technical field of cloud. According to the embodiment of the invention, one processing mode can be randomly selected to carry out degradation processing on the first sample image with the high resolution to obtain the second sample image with the low resolution, so that the second sample image with the low resolution can be obtained without manual processing, the labor cost can be greatly reduced, and the obtaining efficiency of the low resolution is improved. In the training process, one processing mode can be selected for degradation processing each time, so that the target image processing model obtained through training can perform good image processing on the images obtained through processing of the multiple processing modes, the method can adapt to more image processing scenes, and therefore the target image processing model is good in applicability.

The invention discloses a cloud server real-time monitoring device based on cloud computing and a method thereof, belongs to the technical field of cloud servers, and aims to solve the problems that an existing cloud server depends on a firewall to perform virus defense, but the firewall cannot perform real-time abnormality monitoring on the cloud server and cannot provide help and give an alarm in time. The operation state and data of the cloud server are monitored in real time based on the monitoring module, the data processed by the data processing module are transmitted to the anomaly detection module and the virus detection module, the anomaly detection module and the virus detection module detect the monitored data in real time to check whether the cloud server has operation anomaly and virus invasion, and when the operation anomaly of the cloud server is detected, the cloud computing analysis module analyzes detailed data when the cloud server operates abnormally through cloud computing big data, judges and analyzes the reason of abnormal operation of the cloud server, and gives an alarm to remind a worker by putting and displaying the reason; according to the invention, the abnormity of the cloud server can be monitored in real time, workers can be helped to quickly adjust and maintain the cloud server, and the use is convenient.

The invention provides a cabinet for installing a cloud computing big data processor. The cabinet is characterized in that partition plates are arranged and installed in a cabinet body, the upper surface of the partition plate is slidably connected with a first supporting plate, first supporting columns are fixedly connected to the left side and the right side of the upper surface of the first supporting plate, second supporting columns are arranged at the positions, located on the inner sides of the first supporting columns, of the upper surface of the first supporting plate, limiting blocksare movably connected to the upper ends of the first supporting columns, rockers are fixedly connected to the upper surfaces of the limiting blocks, adjusting rods are slidably connected into the second supporting columns, and the surfaces of the adjusting rods are sleeved with connecting springs. According to the invention, with the cabinet, a processor can be rapidly fixed while the processor isconvenient to disassemble, and when the processor needs to be overhauled, the processor can be adjusted to a proper angle according to needs, so that the practicability is improved; and starting of acooling fan can be controlled according to the external temperature, so that waste of electric power is avoided, and the cabinet adapts to sustainable development.

The invention provides a privacy protection method for big data in cloud computing. The method includes the steps of setting a plurality of authentication servers in a cloud storage platform, and conducting secret key distribution and character authentication transaction processing by class; maintaining a global user character list, wherein the authentication servers set an authorization reading policy and a constraint control policy. The privacy protection method for the big data in the cloud computing enhances safe reading policy control of environment and policy constraints, reduces computing costs of writing users on the premise of ensuring safety, and meets application demands of various cross-cloud cross-class data policies.

The invention discloses a teaching system for big data based on computer cloud computing. The system comprises a teaching desk main body, a rotating groove, a display screen, a rotating assembly, a supporting plate, a lifting assembly, a limiting assembly, a login module, a control module, a cloud database module, a live broadcast teaching module, a knowledge training module, an investigation module, and a result feedback module. The rotating groove is formed in the outer wall of the top end of the teaching desk main body, the display screen is installed on the inner wall of one side of the rotating groove, and the login module, the control module, the cloud database module, the live broadcast teaching module, the knowledge training module, then investigation module and the result feedback module are installed on the inner wall of one side of the display screen. Through a computer cloud computing big data technology, audience surfaces of students can be expanded, so that more people can obtain knowledge, the teaching efficiency is improved, live broadcast and video storage can be carried out, the students can repeatedly watch and deepen knowledge impression, and the teaching effect is improved.

The invention discloses a mine personnel behavior management system and platform, and the system employs advanced technologies such as artificial intelligence, cloud computing, big data, and the Internet of Things, comprehensively masters human behaviors, environment states, key operation steps and operation processes in the mine production operation process, tracks and analyzes in real time, finds problems, prompts in time, gives an alarm to stop, locks safely, records in the background, intelligently identifies dangerous sources and updates a risk source knowledge base. Finally, static personnel behavior management systems, enterprise security governance policies and other rules and regulations files are implemented in place by adopting dynamic and objective informatization, digitization and intelligentization technical means, so that risks can be personally prevented in real time everywhere, piecemeal safety accidents can be avoided, precautions can be taken in the bud, and sustainable development of enterprises is facilitated.

The invention discloses a container resource limiting, fault monitoring and recovering method in the field of cloud computing big data, which comprises the following steps of: acquiring a starting process PID (Proportion Integration Differentiation) of a container, setting the starting process PID in a cgroup resource limiting group to which the container belongs, and setting a cgroup resource limiting value; a systemd resource restriction group of the container cgroup is specified as a non-system resource restriction group; executing a command of the container to start a first process of the container; if the first process of the container is successfully started, updating the state of the container to be in operation and recording the PID of the first process of the container; and destroying the container starting process, and taking over the first process of the container by the first process of the host machine so as to realize separated limitation of container resources. According to the method, the coupling between the components of the container management system is lower, the system is simpler and more reliable, the stability and maintainability of the container are higher, the self-recovery function is achieved, and when the local container breaks down, quick cross-host image file synchronization and container recovery are supported.

The invention discloses a traffic signal control system and method based on software definition. The system comprises a signal lamp, a roadside unit and a control unit, the roadside unit is used for sending a request signal to the control unit and receiving a response signal of the control unit, and the request signal comprises position information and identity information of the roadside unit; the control unit is used for receiving the request signal and sending the response signal to the road side unit, the response signal comprises control information, so that the road side unit can controlthe signal lamp according to the control information, and the control information is generated based on the position information and the identity information. Therefore, soft and hard decoupling, control and execution are separated, traffic signal control is intelligently realized by applying technologies such as cloud computing and big data, and dependence of control logics on specific hardwareis broken through.