CN118035222A - Internet of things data analysis method and system based on intelligent platform - Google Patents
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Abstract
The invention relates to an internet of things data analysis method, system and device based on an intelligent platform, wherein the method comprises the following steps: the intelligent platform acquires multi-mode data acquired in real time by acquisition equipment deployed on Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data; carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data; analyzing the original ecological data in real time through an intelligent analysis engine to obtain standard data, and sending the standard data to a real-time monitoring system; and carrying out feedback analysis on the standard data through a real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy. The method can analyze and process the multi-mode data, effectively process large-scale and complex internet of things data and provide various data for external energy.
Description
Technical Field
The invention relates to the technical field of data analysis of the Internet of things, in particular to an Internet of things data analysis method, system and device based on an intelligent platform.
Background
In modern industry and life, the application of internet of things devices is becoming more and more widespread, and the devices can collect various environment and device data to realize real-time monitoring and intelligent analysis. However, the existing internet of things system has some problems and challenges, the traditional data analysis method can only process certain data, cannot analyze and process multi-mode data with various data, and the traditional data analysis method cannot effectively process large-scale and complex internet of things data, so that real-time analysis and accurate prediction cannot be realized. In addition, when data is externally transmitted, only specific data can be transmitted.
Disclosure of Invention
The invention mainly aims to provide an Internet of things data analysis method, system and device based on an intelligent platform, which can analyze and process multi-mode data, effectively process large-scale and complex Internet of things data and provide various data for external energy.
In order to achieve the above object, the present invention provides an internet of things data analysis method based on an intelligent platform, comprising: the intelligent platform acquires multi-mode data acquired in real time by acquisition equipment deployed on Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data;
carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data;
Analyzing the original ecological data in real time through an intelligent analysis engine to obtain standard data, and sending the standard data to a real-time monitoring system;
And carrying out feedback analysis on the standard data through a real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy.
Further, the data preprocessing is performed on the multi-mode data through an intelligent algorithm to obtain original ecological data, including:
And extracting the data feature codes of the multi-mode data by the intelligent algorithm, judging whether the data feature codes meet the requirements according to a preset feature code table, when the data feature codes meet the requirements of the feature code table, carrying out data arrangement on the multi-mode data by the intelligent algorithm according to the data feature codes, and sequentially carrying out data cleaning, noise elimination and processing missing values on the obtained arrangement data to obtain original ecological data, wherein the intelligent algorithm carries out algorithm data updating according to the original ecological data.
Further, after the step of performing data preprocessing on the multi-modal data through the intelligent algorithm to obtain the original-ecology data, the method further includes:
The original ecological data are sent to a third party system through a first interface on the intelligent platform;
The sending the original ecological data to a third party system through a first interface on the intelligent platform comprises:
detecting the data transmission specification of the standard interface of the third party system when the first interface on the intelligent platform is connected with the standard interface of the third party system, and when the data transmission specification of the standard interface of the third party system is consistent with the data transmission specification of the first interface, sending a permission code to the third party system by the intelligent platform, carrying out matching processing on the permission code by the third party system, and carrying out combined packaging on the permission instruction obtained by the matching processing and the third party system information;
The intelligent platform judges whether the authority instruction meets the requirement of an instruction table according to a preset instruction table, and detects whether the login database records the third-party system information or not after the authority instruction meets the requirement, and when the intelligent platform does not record, the intelligent platform acquires the third-party system information according to the authority instruction, records the third-party system information into the login database and transmits the original ecological data to the third-party system.
Further, the real-time analysis of the original ecological data by the intelligent analysis engine to obtain standard data includes:
Extracting data feature codes of the original ecological data through the intelligent analysis engine, performing type matching on the data feature codes of the original ecological data according to sound types, picture types, audio and video types, position types and sensor types, and performing data identification on the sound data, the picture data, the audio and video data, the position data and the sensor data which are obtained through matching through the intelligent analysis engine;
Detecting abnormal information of the Internet of things equipment according to the equipment information of the Internet of things equipment obtained through identification by the intelligent analysis engine, when the abnormal information of the Internet of things equipment is detected, processing the abnormal information to obtain abnormal data, combining sound data, picture data, audio and video data, position data and sensor data based on the intelligent analysis engine to obtain comprehensive data, and carrying out trend prediction on the Internet of things equipment by the intelligent analysis engine by combining the equipment information and the comprehensive data to obtain a prediction result;
And carrying out three-time overlapped encryption on the abnormal information, the comprehensive data and the prediction result through the intelligent analysis engine to sequentially obtain first encrypted data, second encrypted data and third encrypted data, carrying out packaging processing on the third encrypted data, storing the packaged standard data in a corresponding standard database, and carrying out data updating on parameters of the intelligent analysis engine according to the abnormal information, the comprehensive data and the prediction result.
Further, after the step of obtaining the standard data, the step of analyzing the original ecological data in real time by the intelligent analysis engine further includes:
the standard data is sent to a third party system through a second interface of the intelligent platform;
the sending the standard data to a third party system through a second interface of the intelligent platform comprises the following steps:
When the intelligent platform is connected with the interface of the third party system through the second interface, detecting the data transmission specification of the interface of the third party system, adjusting the data transmission specification of the second interface to be consistent with the data transmission specification of the interface of the third party system, receiving the login password of the third party system by the intelligent platform, and judging whether the login password meets the requirement according to a preset password library;
When the login password does not meet the requirement, the third party system is guided to perform authority registration, and after the third party system completes the authority registration and obtains the corresponding authority level, the intelligent platform opens the corresponding standard database according to the authority level of the third party system, and provides standard data for the third party system through the second interface according to the standard database of the corresponding authority level; when the login password meets the requirement, the third-party system information is obtained, a standard database corresponding to the authority level is opened according to the third-party system information, and the intelligent platform provides standard data for the third-party system through the second interface according to the standard database corresponding to the authority level.
Further, the real-time monitoring system performs feedback analysis on the standard data to obtain a corresponding coping strategy, including:
After the real-time monitoring system receives the standard data, the standard data is unpacked to obtain the abnormal information, the comprehensive data and the prediction result, the abnormal information is subjected to abnormal analysis according to a preset countermeasure database through an analysis model to obtain an abnormal processing countermeasure, the comprehensive processing analysis is performed through the combination of the comprehensive data and the prediction result through the analysis model to obtain a comprehensive analysis result, the analysis result is subjected to equipment operation simulation through the analysis model to obtain an operation decision of the Internet of things equipment, and the operation decision of the Internet of things equipment and the abnormal processing countermeasure are combined and packaged to obtain the corresponding coping strategy.
Further, after the real-time monitoring system receives the standard data, the standard data is unpacked, which includes:
After the real-time monitoring system receives the standard data, the real-time monitoring system unpacks the standard data to obtain the third encrypted data, and decrypts the third encrypted data according to a preset reverse decryption table to obtain the abnormal information and the second encrypted data; extracting abnormal characteristic data of the abnormal information, judging whether the second encrypted data meets the requirement of a reverse decryption table, and when the second encrypted data meets the requirement of the reverse decryption table, performing reverse decryption on the second encrypted data by the real-time monitoring system according to the abnormal characteristic data and the reverse decryption table to obtain the comprehensive data and the first encrypted data; and extracting comprehensive characteristic data of the comprehensive data, judging whether the first encrypted data meets the requirement of a reverse decryption table, and when the first encrypted data meets the requirement of the reverse decryption table, performing reverse decryption on the first encrypted data by the real-time monitoring system according to the comprehensive characteristic data and the reverse decryption table to obtain the prediction result.
The invention also provides an internet of things data analysis system based on the intelligent platform, which comprises the following steps:
The acquisition module is used for acquiring multi-mode data acquired in real time by acquisition equipment deployed on the Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data;
The processing module is used for carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data, and providing the original ecological data for a third party system through a first interface of the intelligent platform;
The analysis module is used for analyzing the original ecological data in real time through the intelligent analysis engine to obtain standard data, providing the standard data for a third party system through a second interface of the intelligent platform, and sending the standard data to the real-time monitoring system;
And the control module is used for carrying out feedback analysis on the standard data through the real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy through the intelligent platform.
The invention also provides an internet of things data analysis device based on the intelligent platform, which comprises:
A memory for storing a program;
and the processor is used for executing the program and realizing the steps of the intelligent platform-based data analysis method of the Internet of things.
The protection circuit for detecting the load when the battery protection chip is used in cascade connection has the following beneficial effects:
the intelligent platform acquires multi-modal data acquired by the Internet of things equipment in real time, wherein the multi-modal data comprises sound, pictures, audios and videos, positions and sensor data, performs data preprocessing on the multi-modal data through an intelligent algorithm, extracts useful information, cleans, eliminates noise and processes missing values, so that original ecological data is obtained, and the original ecological data can be provided for a third party system through a first interface on the premise of ensuring the quality and accuracy of the data. The original ecological data is analyzed in real time through the intelligent analysis engine, the feature codes of the data are extracted, the type matching and the recognition are carried out, the sound data, the picture data, the audio and video data, the position data and the sensor data are analyzed, the abnormal information of the Internet of things equipment is detected, and therefore standard data are obtained and can be transmitted to a third party system through a second interface. The invention can provide two data of original ecological data and standard data for a third party system, and simultaneously can carry out exception analysis and comprehensive processing analysis by a real-time monitoring system through an analysis model and a preset countermeasure database, and rapidly identify the state and the behavior of equipment to obtain a corresponding coping strategy, thereby providing decision support. The real-time monitoring system is helped to take corresponding measures to cope with abnormal conditions, equipment operation and resource utilization can be optimized, production efficiency is improved, cost is saved, and coping strategies are displayed to related personnel so that the related personnel can take necessary actions.
Drawings
FIG. 1 is a flow chart of an Internet of things data analysis method based on an intelligent platform;
FIG. 2 is a block diagram of an Internet of things data analysis system based on an intelligent platform;
fig. 3 is a block diagram of an internet of things data analysis device based on an intelligent platform.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The invention will be further described with reference to the drawings and detailed description.
Referring to fig. 1, the invention provides an internet of things data analysis method based on an intelligent platform, which comprises the following steps:
Step S1: the intelligent platform acquires multi-mode data acquired in real time by acquisition equipment deployed on the Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data, and the sensor data is other data which does not comprise the sound data, the picture data, the audio and video data and the position data;
step S2: carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data;
Step S3: real-time analysis is carried out on the original ecological data through an intelligent analysis engine to obtain standard data, and the standard data is sent to a real-time monitoring system;
step S4: and carrying out feedback analysis on the standard data through the real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy.
As shown in the above steps, specifically, the detailed steps include:
Step S1: the internet of things equipment comprises a sensor, a camera, a microphone and the like, and is used for collecting sound data, picture data, audio and video data, position data and sensor data in an environment in real time, wherein the sensor data can comprise temperature data, humidity data, pressure data and gas data. The internet of things equipment transmits the acquired multi-mode data to the intelligent platform through a wireless network, an Ethernet or other communication modes. The intelligent platform receives the multi-mode data from the Internet of things equipment, stores the multi-mode data in a proper database or a storage system, ensures the reliability and durability of the data, and provides a basis for subsequent data processing and analysis.
Step S2: the original multi-mode data is cleaned through an intelligent algorithm, noise, abnormal values and invalid data are removed, and the intelligent algorithm comprises various technologies such as filtering, interpolation, abnormal detection and the like. When there is a temporal or spatial misalignment in the cleaned multimodal data, a data alignment operation is performed, for example, time-aligning the audio data with the video data, spatial-aligning the position data with the image data, and matching and aligning by time stamp or position information. The multi-mode data after alignment processing is normalized, the value ranges of different data types are unified to the same scale, common normalization methods comprise minimum-maximum normalization, and finally original ecological data is obtained.
Step S3: the intelligent analysis engine performs real-time analysis on the received original ecological data, including application of various algorithms and models to extract useful information, discovery patterns, correlations and the like in the data, and the real-time analysis is performed based on techniques such as machine learning, deep learning, statistics and the like so as to realize intelligent interpretation and inference of the data. Through real-time analysis, the obtained result data needs to be subjected to standardized processing, the data is converted into a specific unit, range or format, and the consistency and comparability of the data are ensured so as to meet the requirements of a real-time monitoring system. And sending the standardized data to a real-time monitoring system through network connection or other communication means, wherein a data sending mode and protocol are selected according to actual conditions, and reliable transmission and instantaneity of the data are ensured.
Step S4: the real-time monitoring system monitors and analyzes the received standardized data in real time, and detects whether an abnormal condition exists or not by comparing the real-time data with a preset normal range or mode. For detected abnormal or important events, the real-time monitoring system can further analyze data, analyze reasons of abnormal data, predict trend and analyze relevance, and can help understand the back reasons of abnormal conditions through data analysis and provide basis for making coping strategies. Based on the result of the data analysis, the real-time monitoring system can generate corresponding coping strategies, including alarm notification, fault removal guidance, risk assessment report and the like, and the coping strategies can be generated based on various modes, such as rules, models and the like. The real-time monitoring system displays the generated coping strategies to the user in a visual mode such as a dashboard, a report, an alarm notification and the like, so that the user can know the abnormal situation in time, and takes corresponding measures according to the displayed coping strategies.
According to the intelligent platform-based data analysis method for the Internet of things, the intelligent platform is used for acquiring the multi-mode data acquired in real time by the acquisition equipment deployed on the Internet of things equipment, acquiring more comprehensive and diversified information, and providing more abundant environment and state information by different types of data (sound, picture, audio and video, position and sensor data), so that the situation of a monitored object can be comprehensively known. The multi-mode data is subjected to data preprocessing through an intelligent algorithm, noise is removed, deviation is corrected, key features are extracted, original ecological data is obtained, the data quality and accuracy are improved, and various types of data are provided. The intelligent analysis engine is used for carrying out real-time analysis on the original ecological data, rapidly extracting and calculating information such as key indexes, trends and anomalies to obtain standard data, timely knowing the state of a monitoring object or a system through real-time analysis, finding problems or anomalies, providing data support for subsequent coping strategy generation, and carrying out feedback analysis on the standard data through the real-time monitoring system to obtain corresponding coping strategies, thereby helping a user to rapidly take corresponding actions, solving problems, reducing risks or optimizing system operation.
In one embodiment, the data preprocessing is performed on the multi-modal data through an intelligent algorithm to obtain original ecological data, including:
The multi-mode data is extracted by an intelligent algorithm, and the feature code is a coding mode for representing the data features and can extract key feature information of the data. Judging whether the data feature codes meet the requirements according to a preset feature code table, wherein the feature code table defines a feature code range or mode meeting the requirements. When the data feature codes meet the requirements of the feature code table, the multi-mode data are arranged according to the data feature codes through an intelligent algorithm, and the operations including data rearrangement, conversion, normalization and the like are included, so that subsequent data processing and analysis can be facilitated. And cleaning the data after finishing to remove abnormal values, noise and inconsistent data, wherein the data cleaning can be realized by technologies such as a statistical method, a filtering algorithm, abnormal detection and the like. And the method adopts filtering, smoothing, noise reduction algorithm and other methods to eliminate noise on the cleaned data, so that the data quality is further improved. And processing missing values of the cleaned and noise-eliminated data by interpolation, filling, prediction and other methods. And obtaining original ecological data after data arrangement, cleaning and processing of the missing values.
Features are extracted from the raw ecological data by intelligent algorithms. Features can include statistical properties of the data, spectral features, image texture features, and the like. Based on the extracted features, intelligent algorithm performs adjustment of parameters, update of weights and update of model structure improvement. And evaluating the updated model, evaluating by using methods such as cross verification and test data set, and evaluating the accuracy and generalization capability of the algorithm by comparing the difference between the predicted result of the model and the real label. And further adjusting and optimizing according to the result of model evaluation through an intelligent algorithm to form a feedback loop process, and continuously and iteratively updating the model to improve the effects of data processing and analysis.
According to the embodiment, the multi-mode data is preprocessed through the intelligent algorithm, so that the original ecological data is obtained, the data quality and accuracy are improved, and a reliable basis is provided for subsequent real-time analysis and strategy generation. The intelligent algorithm is used for updating data according to the original ecological data, so that the algorithm model can be continuously improved and optimized, the data processing and analyzing effects are improved, and the subsequent analysis and coping strategies are more accurate and effective.
In one embodiment, after the step of performing data preprocessing on the multi-modal data by using the intelligent algorithm to obtain the original ecological data, the method further includes:
the method comprises the steps of sending original ecological data to a third party system through a first interface on an intelligent platform;
Sending the original ecological data to a third party system through a first interface on the smart platform, comprising:
detecting the data transmission specification of the standard interface of the third party system when the first interface on the intelligent platform is connected with the standard interface of the third party system, and when the data transmission specification of the standard interface of the third party system is consistent with the data transmission specification of the first interface, sending a permission code to the third party system by the intelligent platform, carrying out matching processing on the permission code by the third party system, and carrying out combined packaging on the permission instruction obtained by the matching processing and the third party system information;
The intelligent platform judges whether the authority instruction meets the requirement of an instruction table according to a preset instruction table, and detects whether the login database records the third-party system information or not after the authority instruction meets the requirement, and when the intelligent platform does not record, the intelligent platform acquires the third-party system information according to the authority instruction, records the third-party system information into the login database and transmits the original ecological data to the third-party system.
In this embodiment, before the standard interface of the third party system is connected, the smart platform detects the data transmission specification of the standard interface of the third party system, which includes specifications of data format, protocol, coding mode, etc., and the smart platform needs to ensure that its first interface and the standard interface of the third party system keep consistent in the data transmission specification to ensure correct transmission and analysis of data. When the data transmission specification of the standard interface of the third party system is consistent with the first interface of the intelligent platform, the intelligent platform generates a permission code and sends the permission code to the third party system. After receiving the permission code sent by the intelligent platform, the third party system performs matching processing on the permission code, which generally includes decrypting, verifying and comparing the permission code to ensure the validity and effectiveness of the permission code. After the matching process is successful, the third party system can combine and package the authority instruction obtained by the matching process and the third party system information, and the related information comprises the contents such as system identification, user authority, data access rules and the like.
And the third party system sends the information instruction obtained by encapsulation to a first interface of the intelligent platform. After receiving the information instruction, the intelligent platform performs decryption operation to obtain the authority instruction and the third party system information contained in the information instruction. The intelligent platform judges the received permission instruction according to a preset instruction table, and the instruction table defines the allowable execution operation and the corresponding permission requirement. The intelligent platform compares the authority instruction with the instruction list to determine whether the authority instruction meets the requirement.
If the entitlement instruction meets the requirements, the intelligent platform will detect whether third party system information has been recorded in a login database, which is typically used to store authorized third party system information, including system identification, access rights, user information, etc. If the third party system information is not recorded in the login database, the intelligent platform can acquire the third party system information from the rights management system or other authorization mechanisms according to the related information in the rights instruction, such as the system identification. The intelligent platform inputs the acquired third-party system information into a login database so as to facilitate subsequent data transmission and management. Finally, the intelligent platform transmits the original ecological data to the authorized and verified third party system so as to meet the requirements and application scenes of the third party system.
According to the embodiment, through connection and data transmission flow of the intelligent platform and the third party system, safety and authority control of data transmission are guaranteed, the intelligent platform can detect data transmission specifications of a standard interface of the third party system and send the authority code for matching processing, so that only authorized systems can access and use data, and safety and confidentiality of the data are improved. Through the collaborative work of the intelligent platform and the third party system, the sharing of data and the intercommunication of resources are realized, the intelligent platform transmits the original ecological data to the third party system, the accurate and reliable data is provided for the third party system, and meanwhile, the third party system can transmit the processing result and the analysis feedback back to the intelligent platform, so that the interaction and sharing of the data are realized, and the overall efficiency and the value of the system are improved.
In one embodiment, the real-time analysis of the raw ecological data by the intelligent analysis engine to obtain standard data comprises:
The original ecological data is analyzed and processed through the intelligent analysis engine, and data feature codes are extracted, wherein the data feature codes can be different types of feature codes such as sound, pictures, audios and videos, positions and sensors. And performing type matching on the data feature codes of the extracted original ecological data according to the sound type, the picture type, the audio/video type, the position type and the sensor type by an intelligent analysis engine. The intelligent analysis engine performs data recognition on the matched sound data, picture data, audio and video data, position data and sensor data, and the intelligent analysis engine performs operations such as voice recognition on the sound, image recognition on the picture, content analysis on the audio and video, geographic position analysis on the position data, signal processing on the sensor data and the like, so that the data recognition is performed. Based on the device information of the internet of things device obtained through recognition, the intelligent analysis engine detects whether the internet of things device has abnormal information.
When the abnormal information of the Internet of things equipment is detected, the intelligent analysis engine processes the abnormal information to obtain abnormal data, wherein the abnormal data comprises operations such as classification of abnormal events, analysis of abnormal reasons, correction of the abnormal data and the like.
The intelligent analysis engine combines the sound data, the picture data, the audio and video data, the position data and the sensor data to generate comprehensive data, and the comprehensive data can provide more comprehensive and comprehensive information, thereby being beneficial to further analysis and decision. The intelligent analysis engine performs trend prediction on the Internet of things equipment by combining equipment information and comprehensive data to obtain a prediction result, and can predict the future state and behavior of the equipment and make corresponding decisions and adjustments in advance.
And the intelligent analysis engine performs three-time superposition encryption on the abnormal information, the comprehensive data and the prediction result to obtain first encrypted data, second encrypted data and third encrypted data, then performs encapsulation on the third encrypted data, and stores the encapsulated standard data in a corresponding standard database so as to ensure the safety and confidentiality of the data. According to the abnormal information, the comprehensive data and the prediction result, the intelligent analysis engine updates the data of the parameters of the intelligent analysis engine, so that the intelligent analysis engine is helped to continuously optimize and adjust the analysis algorithm, and the accuracy and effect of analysis are improved.
According to the method, the device and the system, the original ecological data are analyzed and processed in real time through the intelligent analysis engine, the analysis and prediction capability of the data can be improved, the engine can acquire the data feature codes from multiple dimensions such as sound, pictures, audio and video, positions and sensors, and comprehensive and accurate information can be obtained through data identification and comprehensive analysis, so that a more accurate prediction result is provided for a user. The intelligent analysis engine can detect the abnormal information of the equipment of the Internet of things, process the abnormal information correspondingly, discover the abnormal state of the equipment in time, and take measures in advance to repair or adjust so as to ensure the normal operation and performance of the equipment. The security and privacy protection of standard data are ensured through three superimposed encryption and encapsulation processes, unauthorized access and theft are prevented through encryption and encapsulation, and the confidentiality and integrity of the data are protected. The intelligent analysis engine updates the data of the parameters according to the abnormal information, the comprehensive data and the prediction result, so that the engine can continuously optimize and adjust the analysis algorithm, the analysis accuracy and the analysis effect are improved, and the engine can better adapt to different application scenes and requirements.
In one embodiment, the step of analyzing the original ecological data in real time by the intelligent analysis engine to obtain the standard data further comprises:
The standard data is sent to a third party system through a second interface of the intelligent platform;
Sending the standard data to a third party system through a second interface of the intelligent platform, comprising:
When the intelligent platform is connected with the interface of the third party system through the second interface, detecting the data transmission specification of the interface of the third party system, adjusting the data transmission specification of the second interface to be consistent with the data transmission specification of the interface of the third party system, receiving the login password of the third party system by the intelligent platform, and judging whether the login password meets the requirement according to a preset password library;
When the login password does not meet the requirement, the third party system is guided to perform authority registration, and after the third party system completes the authority registration and obtains the corresponding authority level, the intelligent platform opens the corresponding standard database according to the authority level of the third party system, and provides standard data for the third party system through the second interface according to the standard database of the corresponding authority level; when the login password meets the requirement, the third-party system information is obtained, a standard database corresponding to the authority level is opened according to the third-party system information, and the intelligent platform provides standard data for the third-party system through the second interface according to the standard database corresponding to the authority level.
In this embodiment, the intelligent platform is connected to the interface of the third party system through the second interface, where the second interface is a universal interface, and in the connection process, the intelligent platform detects the data transmission specification of the interface of the third party system and adjusts the data transmission specification of the second interface to be consistent with the interface of the third party system, so as to ensure compatibility and smoothness of data transmission.
The intelligent platform receives the login password of the third party system and judges whether the login password meets the requirements according to a preset password library:
When the login password does not meet the requirement, the intelligent platform guides the third party system to conduct authority registration, the third party system completes authority registration and obtains corresponding authority levels, and after the third party system completes authority registration and obtains the corresponding authority levels, the intelligent platform opens corresponding standard databases according to the authority levels of the third party system, and the intelligent platform provides standard data for the third party system through a second interface according to the standard databases of the corresponding authority levels;
when the login password meets the requirement, the intelligent platform acquires the third-party system information, opens a standard database corresponding to the authority level according to the third-party system information, and provides standard data for the third-party system through the second interface according to the standard database corresponding to the authority level.
According to the embodiment, the intelligent platform is connected with the interface of the third-party system, the intelligent platform adjusts the data transmission specification, transmission compatibility and smoothness of data between the two systems are guaranteed, the data are efficiently transmitted and shared between the systems, cooperation and collaboration between different systems are promoted, the integration and comprehensive analysis capability of the data are enhanced, and the utilization value and application effect of the data are improved. The intelligent platform ensures that only authorized third party systems can access and acquire standard data through password verification and authority registration, effectively controls the access authority of the data, and protects the safety and privacy of the data. The intelligent platform provides customized standard data according to different system requirements and authority levels by opening the corresponding standard database according to the authority levels of the third party system, so that the third party system can acquire data matched with the application requirements of the third party system, and the applicability and practicability of the data are improved.
In one embodiment, the real-time monitoring system performs feedback analysis on the standard data to obtain a corresponding coping strategy, including:
After the real-time monitoring system receives the standard data, the standard data is unpacked to obtain the abnormal information, the comprehensive data and the prediction result, the abnormal information is subjected to abnormal analysis according to a preset countermeasure database through an analysis model to obtain an abnormal processing countermeasure, the comprehensive processing analysis is performed through the combination of the comprehensive data and the prediction result through the analysis model to obtain a comprehensive analysis result, the analysis result is subjected to equipment operation simulation through the analysis model to obtain an operation decision of the Internet of things equipment, and the operation decision of the Internet of things equipment and the abnormal processing countermeasure are combined and packaged to obtain the corresponding coping strategy.
In this embodiment, the real-time monitoring system receives standard data, where the standard data includes real-time data collected by the sensor, device status information, and the like, and performs an unpacking operation on the received standard data, and extracts abnormal information, comprehensive data, and a prediction result therein. The real-time monitoring system analyzes the abnormality information by using an analysis model and a preset countermeasure database, and generates corresponding abnormality processing countermeasures according to the type, degree and possible reasons of the abnormality. The real-time monitoring system combines the comprehensive data and the prediction result with the analysis model to carry out comprehensive processing analysis, including technologies such as statistical analysis, trend prediction, pattern recognition and the like of the data, so as to acquire more comprehensive information and insight. The real-time monitoring system utilizes the analysis model to simulate the operation of the equipment, and can evaluate the influence of different decisions on the operation of the equipment by simulating different operation scenes and strategies and obtain the optimal operation decision of the equipment of the Internet of things. And carrying out combined encapsulation on the running decision and the abnormality processing countermeasure of the equipment of the Internet of things to generate corresponding coping strategies, wherein the coping strategies comprise adjustment parameters of the equipment, alarm notification, fault elimination guidelines and the like, and aim to cope with abnormal conditions in monitoring data and optimize the running effect of the equipment.
According to the method, the system and the device, the standard data are analyzed and processed through the real-time monitoring system, abnormal conditions in the running process of the device are timely detected and identified, the detection and response speed of faults is improved, the analysis model and the prediction result are utilized, comprehensive processing analysis is carried out by combining comprehensive data, the running decision of the Internet of things device is generated, the running decision is based on data driving and simulation evaluation, intelligent decision support can be provided, and the running efficiency and performance of the device are optimized. The coping strategies generated by the real-time monitoring system provide targeted processing countermeasures for the abnormal condition of the equipment, and the strategies can optimize the running state of the equipment and reduce the occurrence and influence of faults through simulation and evaluation. The real-time monitoring system analyzes and predicts the standard data, so that potential fault risks and trends of the equipment are found in advance, a basis is provided for maintenance planning and preventive measures, and the downtime and maintenance cost of the equipment are reduced.
In one embodiment, after the real-time monitoring system receives the standard data, the real-time monitoring system decapsulates the standard data, including:
the real-time monitoring system receives the standard data, performs unpacking operation on the standard data to obtain third encrypted data, and performs decryption operation on the third encrypted data according to a preset reverse decryption table to obtain abnormal information and second encrypted data.
And extracting abnormal characteristic data from the abnormal information through the real-time monitoring system for subsequent judgment and analysis, judging whether the second encrypted data meets the requirement of a reverse decryption table, and performing reverse decryption operation on the second encrypted data according to the abnormal characteristic data and the reverse decryption table when the second encrypted data meets the requirement to obtain comprehensive data and first encrypted data.
And extracting comprehensive characteristic data from the comprehensive data through the real-time monitoring system for subsequent judgment and analysis, judging whether the first encrypted data meets the requirement of a reverse decryption table, and when the first encrypted data meets the requirement, performing reverse decryption operation on the first encrypted data by the system according to the comprehensive characteristic data and the reverse decryption table to obtain a prediction result.
According to the embodiment, the original abnormal information, the comprehensive data and the prediction result are restored through the deblocking and decrypting operation of the real-time monitoring system on the standard data, so that the data can be further analyzed and processed.
The real-time monitoring system is used for extracting the abnormal characteristic data and the comprehensive characteristic data, so that the system can be helped to acquire more comprehensive information and insight, and meanwhile, the abnormal condition can be identified and processed, the accuracy and the efficiency of fault detection and response can be improved, and the system can be helped to optimize the operation and decision-making effect of equipment. Through encryption and reverse decryption, the security of the standard data is improved, unauthorized access and tampering are prevented, and the integrity and the credibility of the data are ensured.
Referring to fig. 2, the invention further provides an internet of things data analysis system based on the intelligent platform, which comprises:
The acquisition module is used for acquiring multi-mode data acquired in real time by acquisition equipment deployed on the Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data;
The processing module is used for carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data, and providing the original ecological data for a third party system through a first interface of the intelligent platform;
the analysis module is used for analyzing the original ecological data in real time through the intelligent analysis engine to obtain standard data, providing the standard data for a third party system through a second interface of the intelligent platform, and sending the standard data to the real-time monitoring system;
and the control module is used for carrying out feedback analysis on the standard data through the real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy through the intelligent platform.
It should be noted that, for convenience and brevity of description, specific working processes of the above-described system and each module may refer to corresponding processes in the foregoing embodiment of the data analysis method of the internet of things based on the intelligent platform, which are not described herein again.
According to the intelligent platform-based internet of things data analysis system, the intelligent platform is used for acquiring the multi-mode data acquired in real time by the acquisition equipment deployed on the internet of things equipment, acquiring more comprehensive and diversified information, and providing more abundant environment and state information by different types of data (sound, picture, audio and video, position and sensor data), so that the situation of a monitored object can be comprehensively known. The multi-mode data is subjected to data preprocessing through an intelligent algorithm, noise is removed, deviation is corrected, key features are extracted, original ecological data is obtained, the data quality and accuracy are improved, and various types of data are provided. The intelligent analysis engine is used for carrying out real-time analysis on the original ecological data, rapidly extracting and calculating information such as key indexes, trends and anomalies to obtain standard data, timely knowing the state of a monitoring object or a system through real-time analysis, finding problems or anomalies, providing data support for subsequent coping strategy generation, and carrying out feedback analysis on the standard data through the real-time monitoring system to obtain corresponding coping strategies, thereby helping a user to rapidly take corresponding actions, solving problems, reducing risks or optimizing system operation.
Referring to fig. 3, the invention further provides an internet of things data analysis device based on the intelligent platform, which comprises:
A memory for storing a program;
and the processor is used for executing the program and realizing the steps of the intelligent platform-based data analysis method of the Internet of things.
In this embodiment, the processor and the memory may be connected by a bus or other means. The memory may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, a hard disk, or a solid state disk. The processor may be a general-purpose processor, such as a central processing unit, a digital signal processor, an application specific integrated circuit, or one or more integrated circuits configured to implement embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes using the descriptions and drawings of the present invention or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (9)
1. The Internet of things data analysis method based on the intelligent platform is characterized by comprising the following steps of:
The intelligent platform acquires multi-mode data acquired in real time by acquisition equipment deployed on Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data;
carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data;
Analyzing the original ecological data in real time through an intelligent analysis engine to obtain standard data, and sending the standard data to a real-time monitoring system;
And carrying out feedback analysis on the standard data through a real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy.
2. The internet of things data analysis method based on the intelligent platform according to claim 1, wherein the performing data preprocessing on the multi-modal data through the intelligent algorithm to obtain the original ecological data comprises:
And extracting the data feature codes of the multi-mode data by the intelligent algorithm, judging whether the data feature codes meet the requirements according to a preset feature code table, when the data feature codes meet the requirements of the feature code table, carrying out data arrangement on the multi-mode data by the intelligent algorithm according to the data feature codes, and sequentially carrying out data cleaning, noise elimination and processing missing values on the obtained arrangement data to obtain original ecological data, wherein the intelligent algorithm carries out algorithm data updating according to the original ecological data.
3. The internet of things data analysis method based on the intelligent platform according to claim 1, wherein after the step of performing data preprocessing on the multi-modal data by the intelligent algorithm to obtain the original-ecological data, the method further comprises:
The original ecological data are sent to a third party system through a first interface on the intelligent platform;
The sending the original ecological data to a third party system through a first interface on the intelligent platform comprises:
detecting the data transmission specification of the standard interface of the third party system when the first interface on the intelligent platform is connected with the standard interface of the third party system, and when the data transmission specification of the standard interface of the third party system is consistent with the data transmission specification of the first interface, sending a permission code to the third party system by the intelligent platform, carrying out matching processing on the permission code by the third party system, and carrying out combined packaging on the permission instruction obtained by the matching processing and the third party system information;
The intelligent platform judges whether the authority instruction meets the requirement of an instruction table according to a preset instruction table, and detects whether the login database records the third-party system information or not after the authority instruction meets the requirement, and when the intelligent platform does not record, the intelligent platform acquires the third-party system information according to the authority instruction, records the third-party system information into the login database and transmits the original ecological data to the third-party system.
4. The internet of things data analysis method based on the intelligent platform according to claim 1, wherein the real-time analysis of the raw ecological data by the intelligent analysis engine to obtain standard data comprises:
Extracting data feature codes of the original ecological data through the intelligent analysis engine, performing type matching on the data feature codes of the original ecological data according to sound types, picture types, audio and video types, position types and sensor types, and performing data identification on the sound data, the picture data, the audio and video data, the position data and the sensor data which are obtained through matching through the intelligent analysis engine;
Detecting abnormal information of the Internet of things equipment according to the equipment information of the Internet of things equipment obtained through identification by the intelligent analysis engine, when the abnormal information of the Internet of things equipment is detected, processing the abnormal information to obtain abnormal data, combining sound data, picture data, audio and video data, position data and sensor data based on the intelligent analysis engine to obtain comprehensive data, and carrying out trend prediction on the Internet of things equipment by the intelligent analysis engine by combining the equipment information and the comprehensive data to obtain a prediction result;
And carrying out three-time overlapped encryption on the abnormal information, the comprehensive data and the prediction result through the intelligent analysis engine to sequentially obtain first encrypted data, second encrypted data and third encrypted data, carrying out packaging processing on the third encrypted data, storing the packaged standard data in a corresponding standard database, and carrying out data updating on parameters of the intelligent analysis engine according to the abnormal information, the comprehensive data and the prediction result.
5. The internet of things data analysis method based on the intelligent platform according to claim 4, wherein after the step of obtaining standard data by analyzing the original ecological data in real time by the intelligent analysis engine, further comprising:
the standard data is sent to a third party system through a second interface of the intelligent platform;
the sending the standard data to a third party system through a second interface of the intelligent platform comprises the following steps:
When the intelligent platform is connected with the interface of the third party system through the second interface, detecting the data transmission specification of the interface of the third party system, adjusting the data transmission specification of the second interface to be consistent with the data transmission specification of the interface of the third party system, receiving the login password of the third party system by the intelligent platform, and judging whether the login password meets the requirement according to a preset password library;
When the login password does not meet the requirement, the third party system is guided to perform authority registration, and after the third party system completes the authority registration and obtains the corresponding authority level, the intelligent platform opens the corresponding standard database according to the authority level of the third party system, and provides standard data for the third party system through the second interface according to the standard database of the corresponding authority level; when the login password meets the requirement, the third-party system information is obtained, a standard database corresponding to the authority level is opened according to the third-party system information, and the intelligent platform provides standard data for the third-party system through the second interface according to the standard database corresponding to the authority level.
6. The internet of things data analysis method based on the intelligent platform according to claim 4, wherein the real-time monitoring system performs feedback analysis on standard data to obtain a corresponding coping strategy, and the method comprises the steps of:
After the real-time monitoring system receives the standard data, the standard data is unpacked to obtain the abnormal information, the comprehensive data and the prediction result, the abnormal information is subjected to abnormal analysis according to a preset countermeasure database through an analysis model to obtain an abnormal processing countermeasure, the comprehensive processing analysis is performed by combining the comprehensive data and the prediction result through the analysis model to obtain a comprehensive analysis result, the analysis result is subjected to equipment operation simulation through the analysis model to obtain an operation decision of the equipment of the Internet of things,
And carrying out combined packaging on the running decision and the abnormality processing countermeasure of the equipment of the Internet of things to obtain the corresponding coping strategy.
7. The internet of things data analysis method based on the intelligent platform according to claim 6, wherein the real-time monitoring system, after receiving the standard data, unpacks the standard data, comprises:
After the real-time monitoring system receives the standard data, the real-time monitoring system unpacks the standard data to obtain the third encrypted data, and decrypts the third encrypted data according to a preset reverse decryption table to obtain the abnormal information and the second encrypted data; extracting abnormal characteristic data of the abnormal information, judging whether the second encrypted data meets the requirement of a reverse decryption table, and when the second encrypted data meets the requirement of the reverse decryption table, performing reverse decryption on the second encrypted data by the real-time monitoring system according to the abnormal characteristic data and the reverse decryption table to obtain the comprehensive data and the first encrypted data; and extracting comprehensive characteristic data of the comprehensive data, judging whether the first encrypted data meets the requirement of a reverse decryption table, and when the first encrypted data meets the requirement of the reverse decryption table, performing reverse decryption on the first encrypted data by the real-time monitoring system according to the comprehensive characteristic data and the reverse decryption table to obtain the prediction result.
8. An internet of things data analysis system based on an intelligent platform is characterized by comprising:
The acquisition module is used for acquiring multi-mode data acquired in real time by acquisition equipment deployed on the Internet of things equipment, wherein the multi-mode data comprises sound data, picture data, audio and video data, position data and sensor data;
The processing module is used for carrying out data preprocessing on the multi-mode data through an intelligent algorithm to obtain original ecological data, and providing the original ecological data for a third party system through a first interface of the intelligent platform;
The analysis module is used for analyzing the original ecological data in real time through the intelligent analysis engine to obtain standard data, providing the standard data for a third party system through a second interface of the intelligent platform, and sending the standard data to the real-time monitoring system;
And the control module is used for carrying out feedback analysis on the standard data through the real-time monitoring system to obtain a corresponding coping strategy, and displaying the coping strategy through the intelligent platform.
9. Internet of things data analysis device based on intelligent platform, which is characterized by comprising:
A memory for storing a program;
a processor for executing the program to implement the steps of the intelligent platform-based data analysis method for internet of things according to any one of claims 1 to 7.
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