CN116755350A - House safety monitoring and early warning system based on intelligent household internet of things technology - Google Patents
House safety monitoring and early warning system based on intelligent household internet of things technology Download PDFInfo
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Abstract
The invention relates to the field of data processing, and discloses a house safety monitoring and early warning system based on an intelligent household internet of things technology, wherein a data reading module is used for reading operation monitoring data of a sensor on an intelligent household in real time and sending the operation monitoring data to a data processing module through a wireless transmission technology; the data processing module is used for receiving the operation monitoring data, carrying out data processing on the operation monitoring data to obtain operation target data, and transmitting the operation target data to the security analysis module; the security analysis module is used for analyzing the house security containing the intelligent home based on the operation target data to obtain house security analysis information; the early warning sending module is used for judging whether the house is safe or not according to the house safety analysis information, if not, generating corresponding safety early warning information according to the house safety analysis information, and sending the safety early warning information to the user terminal; the invention can find out abnormal state in time, prevent safety problem, and meet user demand.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a house safety monitoring and early warning system based on an intelligent household internet of things technology.
Background
The intelligent home uses the house as a platform, integrates facilities related to home life by utilizing a comprehensive wiring technology, a network communication technology, a security protection technology, an automatic control technology and an audio-video technology, builds an efficient management system of home facilities and family schedule matters, improves the safety, convenience, comfort and artistry of the house, realizes environment-friendly and energy-saving living environment, has the traditional living function, integrates the functions of building, network communication, information home appliances and equipment automation, and provides an omnibearing information interaction function, so that the intelligent home can realize comprehensive real-time monitoring of the house, but the intelligent home is adopted at present to carry out intelligent monitoring in the house, so that the use requirement of a user cannot be met.
Disclosure of Invention
The invention aims to solve the problems, and designs a house safety monitoring and early warning system based on the intelligent home Internet of things technology.
The invention provides a house safety monitoring and early warning system based on an intelligent home Internet of things technology, wherein a plurality of intelligent home devices of the Internet of things are in communication connection with a user terminal through the Internet of things and are connected with the user terminal through a network;
the data processing module is used for receiving the operation monitoring data, carrying out data processing on the operation monitoring data to obtain operation target data, and transmitting the operation target data to the security analysis module;
the safety analysis module is used for analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information, and transmitting the house safety analysis information to the early warning sending module;
and the early warning sending module is used for judging whether the house is safe or not according to the house safety analysis information, if not, generating corresponding safety early warning information according to the house safety analysis information, and sending the safety early warning information to the user terminal.
Optionally, in a first implementation manner of the first aspect of the present invention, the data processing module includes a normalization processing sub-module, a first computing sub-module, a second computing sub-module, an updating sub-module, a third computing sub-module, a merging sub-module, and an analyzing sub-module, where the normalization processing sub-module is configured to perform normalization processing on the operation monitoring data to obtain an initial monitoring dataset, and set minimum sample data included in a class center of the cluster;
the first calculation sub-module is used for calculating the Euclidean distance of the initial monitoring data set relative to the minimum sample data and carrying out ascending arrangement on the obtained Euclidean distance;
the second calculation sub-module is used for taking k sample data farthest from each cluster as initial clustering center points of each cluster and calculating the distances between other sample data in the initial monitoring data set and the initial clustering center points of each cluster;
the updating sub-module is used for dividing other sample data in the initial monitoring data set into clusters with the minimum distance, and updating the initial clustering center of each cluster to obtain a first clustering result;
a third calculation sub-module, configured to calculate an average distance of sample data in a cluster in the first clustering result, and calculate a similarity degree between each category of the first clustering result as a dispersion degree of the cluster;
the merging submodule is used for combining the dispersion degree and the similarity degree, and merging similar sample data in clusters in the first clustering result to obtain a second clustering result;
and the analysis sub-module is used for analyzing the second aggregation result through a multivariate data analysis method to obtain operation target data.
Optionally, in a second implementation manner of the first aspect of the present invention, the security analysis module includes a data determination submodule, a data calculation submodule and a data analysis submodule, where the data determination submodule is configured to obtain historical monitoring data of the smart home, and determine a security index of the smart home according to the historical monitoring data;
the data computing sub-module is used for outputting probability density of the safety indexes through Gaussian mixture, computing weight of the safety indexes through an entropy weight computing method and computing total safety indexes of the intelligent home;
and the data analysis sub-module is used for calculating the house security score containing the intelligent house so as to analyze the house security according to the house security score and obtain house security analysis information.
Optionally, in a third implementation manner of the first aspect of the present invention, the data calculation submodule includes a first construction unit, a second construction unit, a third construction unit and a fourth construction unit, where the first construction unit is configured to construct a first matrix according to a security index of the smart home, and perform gaussian mixture fitting on the first matrix to obtain a probability density corresponding to the security index;
the second construction unit is used for calculating an entropy value corresponding to the safety index of the intelligent home by adopting the shannon entropy theory and constructing a second matrix according to the entropy value corresponding to the safety index;
the third construction unit is used for calculating the entropy weight of the safety index based on the second matrix and constructing an entropy weight matrix to obtain the weight of the safety index;
and the fourth construction unit is used for sequencing the safety indexes of the intelligent home according to the importance, and constructing a safety total index matrix of the intelligent home to obtain a safety total index.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the data analysis submodule includes a determining unit, a normalizing unit and a scoring unit, where the determining unit is configured to calculate an average total safety index according to a plurality of total safety indexes of the smart home, and determine a safety area according to the average total safety index;
the normalization unit is used for normalizing the safety area to obtain a safety score threshold value, wherein the safety score threshold value is obtained according to the maximum and minimum average safety total indexes;
and the scoring unit is used for scoring the house safety containing the intelligent house based on the operation target data to obtain a house safety score, and analyzing the house safety based on the house safety score and the safety score threshold to obtain house safety analysis information.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the scoring unit includes a building unit, a calculating unit and an analyzing unit, where the building unit is configured to build a multiple linear regression model based on probability density, weight and total safety index of the smart home;
the calculating unit is used for calculating a theoretical regression correction coefficient through the multiple linear regression model, wherein the theoretical regression correction coefficient is a theoretical correction weight value;
and the analysis unit is used for analyzing and scoring the result of the operation target data according to the theoretical regression correction coefficient to obtain the house security score.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the early warning sending module includes an information obtaining sub-module, a first judging sub-module and a second judging sub-module, where the information obtaining sub-module is configured to determine early warning level information according to the house security analysis information, and obtain early warning measure information of a corresponding level;
the first judging submodule is used for judging whether to respond to the early warning measure information, and if the early warning measure information is the response, the early warning level information and the early warning measure information are updated;
and the second judging sub-module is used for evaluating the early warning measure behavior if the early warning measure information responds and judging whether the early warning measure behavior reaches a safe state or not, and if the early warning measure behavior reaches the safe state, the early warning is released.
Optionally, in a seventh implementation manner of the first aspect of the present invention, the security early warning information includes at least early warning category information, early warning level information and early warning measure information of the smart home.
Optionally, in an eighth implementation manner of the first aspect of the present invention, the operation method of the system includes the following steps:
the method comprises the steps of reading operation monitoring data of the sensor to the intelligent home in real time;
receiving the operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data;
analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information;
judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information.
Optionally, in a ninth implementation manner of the first aspect of the present invention, the receiving the operation monitoring data and performing data processing on the operation monitoring data to obtain operation target data includes:
performing standardized processing on the operation monitoring data to obtain an initial monitoring data set, and setting minimum sample data included in a clustered class center;
calculating the Euclidean distance of the initial monitoring data set relative to the minimum sample data, and carrying out ascending arrangement on the obtained Euclidean distance;
taking k sample data with the farthest distance as initial clustering center points of each cluster, and calculating the distances between other sample data in the initial monitoring data set and the initial clustering center points of each cluster;
dividing other sample data in the initial monitoring data set into clusters with the minimum distance, and updating the initial clustering centers of the clusters to obtain a first clustering result;
calculating the average distance of sample data in a cluster in the first clustering result, and calculating the similarity degree among all the categories of the first clustering result as the dispersion degree of the cluster;
combining the dispersion degree and the similarity degree, and combining similar sample data in clusters in the first clustering result to obtain a second clustering result;
and analyzing the second aggregation result by a multivariate data analysis method to obtain operation target data.
According to the technical scheme, the intelligent household intelligent monitoring system comprises a data reading module, a data processing module, a safety analysis module and an early warning sending module, wherein operation monitoring data of a sensor on an intelligent household are read in real time; receiving the operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data; analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information; judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information; according to the intelligent household safety monitoring and early warning system, communication is carried out through the Internet of things, the degree of automation is high, the safety monitoring and early warning of the house are realized through the data processing of the intelligent household, the abnormal state is found timely, the safety problem is prevented, and the user requirement is met.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
FIG. 1 is a schematic diagram of an embodiment of a house security monitoring and early warning system based on the intelligent home Internet of things technology according to the present invention;
fig. 2 is a schematic diagram of another embodiment of a house security monitoring and early warning system based on the intelligent home internet of things technology according to the embodiment of the present invention.
Detailed Description
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of the embodiment of the present invention is described below, referring to fig. 1, which is a schematic diagram of a first embodiment of a house safety monitoring and early warning system based on the intelligent home internet of things technology, where a plurality of internet of things intelligent home devices are connected in a communication manner through the internet of things and are connected with a user terminal through a network, and the system includes a data reading module, a data processing module, a security analysis module and an early warning sending module, where the data reading module 101 is configured to read operation monitoring data of a sensor on an intelligent home in real time, and send the operation monitoring data to the data processing module through a wireless transmission technology;
the data processing module 102 is configured to receive the operation monitoring data, perform data processing on the operation monitoring data to obtain operation target data, and transmit the operation target data to the security analysis module;
the security analysis module 103 is configured to analyze the security of the house including the smart home based on the operation target data, obtain house security analysis information, and transmit the house security analysis information to the early warning sending module;
and the early warning sending module 104 is used for judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information and sending the safety early warning information to the user terminal.
The operation method of the system comprises the following steps: the method comprises the steps of reading operation monitoring data of the sensor to the intelligent home in real time; receiving operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data; analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information; judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information.
In this embodiment, receiving operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data, including: performing standardized processing on the operation monitoring data to obtain an initial monitoring data set, and setting minimum sample data included in a clustered class center; calculating Euclidean distance of an initial monitoring data set relative to the minimum sample data, and carrying out ascending arrangement on the obtained Euclidean distance; taking k sample data with the farthest distance as initial clustering center points of each cluster, and calculating the distances between other sample data in an initial monitoring data set and the initial clustering center points of each cluster; dividing other sample data in the initial monitoring data set into clusters with the minimum distance, and updating the initial clustering centers of the clusters to obtain a first clustering result;
calculating the average distance of sample data in a cluster in a first clustering result, and calculating the similarity degree among all the categories of the first clustering result as the dispersion degree of the cluster; combining the dispersion degree and the similarity degree, and combining similar intra-cluster sample data in the first clustering result to obtain a second clustering result; and analyzing the second aggregation result by a multivariate data analysis method to obtain operation target data.
In the embodiment of the invention, the system comprises a data reading module, a data processing module, a security analysis module and an early warning sending module, wherein the operation monitoring data of the sensor to the intelligent home is read in real time; receiving operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data; analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information; judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information; according to the intelligent household safety monitoring and early warning system, communication is carried out through the Internet of things, the degree of automation is high, the safety monitoring and early warning of the house are realized through the data processing of the intelligent household, the abnormal state is found timely, the safety problem is prevented, and the user requirement is met.
Referring to fig. 2, another embodiment of a house security monitoring and early warning system based on the intelligent home internet of things technology provided by the present invention is shown in the schematic diagram, and the system includes:
the data reading module 101 is configured to read operation monitoring data of the sensor to the smart home in real time, and send the operation monitoring data to the data processing module through a wireless transmission technology;
the data processing module 102 is configured to receive the operation monitoring data, perform data processing on the operation monitoring data to obtain operation target data, and transmit the operation target data to the security analysis module;
the security analysis module 103 is configured to analyze the security of the house including the smart home based on the operation target data, obtain house security analysis information, and transmit the house security analysis information to the early warning sending module;
the early warning sending module 104 is configured to determine whether the house is safe according to the house security analysis information, if not, generate corresponding security early warning information according to the house security analysis information, and send the security early warning information to the user terminal, where the security early warning information at least includes early warning category information, early warning level information and early warning measure information of the smart home.
In this embodiment, the data processing module 102 includes a normalization processing sub-module, a first computing sub-module, a second computing sub-module, an updating sub-module, a third computing sub-module, a merging sub-module and an analyzing sub-module, where the normalization processing sub-module 1021 is configured to perform normalization processing on operation monitoring data to obtain an initial monitoring dataset, and set minimum sample data included in a class center of a cluster;
a first calculation submodule 1022, configured to calculate euclidean distances of the initial monitoring data set relative to the minimum sample data, and perform ascending arrangement on the obtained euclidean distances;
the second calculation submodule 1023 is used for taking k sample data farthest from each cluster as initial clustering center points of each cluster and calculating the distances between other sample data in the initial monitoring data set and the initial clustering center points of each cluster;
an updating sub-module 1024, configured to divide other sample data in the initial monitoring data set into clusters with the smallest distance, and update the initial clustering center of each cluster to obtain a first clustering result;
the third calculation sub-module 1025 is configured to calculate an average distance of sample data in a cluster in the first clustering result, and calculate a similarity degree between each category of the first clustering result as a dispersion degree of the cluster;
a merging submodule 1026, configured to combine the dispersion degree and the similarity degree, and merge similar sample data in clusters in the first clustering result to obtain a second clustering result;
and the analysis submodule 1027 is used for analyzing the second aggregation result through a multivariate data analysis method to obtain operation target data.
In this embodiment, the security analysis module 103 includes a data determination submodule, a data calculation submodule and a data analysis submodule, where the data determination submodule 1031 is configured to obtain historical monitoring data of the smart home, and determine a security index of the smart home according to the historical monitoring data;
the data calculation submodule 1032 is used for outputting probability density of the safety indexes through Gaussian mixture, calculating weight of the safety indexes through an entropy weight calculation method and calculating total safety indexes of the intelligent home;
the data analysis submodule 1033 is used for calculating the house security score containing the smart home so as to analyze the house security according to the house security score and obtain house security analysis information.
In this embodiment, the data calculation submodule includes a first construction unit, a second construction unit, a third construction unit and a fourth construction unit, where the first construction unit is configured to construct a first matrix according to a security index of the smart home, and perform gaussian mixture fitting on the first matrix to obtain a probability density corresponding to the security index;
the second construction unit is used for calculating an entropy value corresponding to the safety index of the intelligent home by adopting the shannon entropy theory and constructing a second matrix according to the entropy value corresponding to the safety index;
the third construction unit is used for calculating the entropy weight of the safety index based on the second matrix and constructing an entropy weight matrix to obtain the weight of the safety index;
and the fourth construction unit is used for sequencing the safety indexes of the intelligent home according to the importance, and constructing a safety total index matrix of the intelligent home to obtain a safety total index.
In this embodiment, the data analysis submodule includes a determining unit, a normalizing unit and a scoring unit, where the determining unit is configured to calculate an average total safety index according to a plurality of total safety indexes of the smart home, and determine a safety area according to the average total safety index;
the normalization unit is used for normalizing the safety area to obtain a safety score threshold value, wherein the safety score threshold value is obtained according to the maximum and minimum average safety total indexes;
the scoring unit is used for scoring the house safety containing the intelligent home based on the operation target data to obtain house safety scores, and analyzing the house safety based on the house safety scores and the safety score threshold value to obtain house safety analysis information.
In this embodiment, the scoring unit includes a building unit, a calculating unit and an analyzing unit, where the building unit is configured to build a multiple linear regression model based on probability density, weight and total safety index of the smart home;
the calculating unit is used for calculating a theoretical regression correction coefficient through the multiple linear regression model, wherein the theoretical regression correction coefficient is a theoretical correction weight value;
and the analysis unit is used for analyzing and scoring the result of the operation target data according to the theoretical regression correction coefficient to obtain the house security score.
In this embodiment, the early warning sending module 104 includes an information obtaining sub-module, a first judging sub-module and a second judging sub-module, where the information obtaining sub-module 1041 is configured to determine early warning level information according to house security analysis information, and obtain early warning measure information of a corresponding level;
the first judging submodule 1042 is used for judging whether to respond to the early warning measure information, if the early warning measure information is response, the early warning level information and the early warning measure information are upgraded;
the second judging sub-module 1043 is configured to evaluate the early warning measure behavior if the early warning measure information responds, and judge whether the early warning measure behavior reaches the safe state, and release the early warning if the early warning measure behavior reaches the safe state.
Through implementation of the scheme, the system comprises a data reading module, a data processing module, a safety analysis module and an early warning sending module, adopts the Internet of things to communicate, has high automation degree, realizes monitoring and early warning of house safety through data processing of intelligent home, timely discovers abnormal states, prevents safety problems from happening, and meets user requirements.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present invention, and are not intended to limit the invention, and that various changes and modifications may be made therein without departing from the spirit and scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. The house safety monitoring and early warning system based on the intelligent home Internet of things technology is characterized in that the system comprises a data reading module, a data processing module, a safety analysis module and an early warning sending module, wherein the data reading module is used for reading running monitoring data of a sensor on an intelligent home in real time and sending the running monitoring data to the data processing module through a wireless transmission technology;
the data processing module is used for receiving the operation monitoring data, carrying out data processing on the operation monitoring data to obtain operation target data, and transmitting the operation target data to the security analysis module;
the safety analysis module is used for analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information, and transmitting the house safety analysis information to the early warning sending module;
and the early warning sending module is used for judging whether the house is safe or not according to the house safety analysis information, if not, generating corresponding safety early warning information according to the house safety analysis information, and sending the safety early warning information to the user terminal.
2. The house safety monitoring and early warning system based on the intelligent home internet of things technology according to claim 1, wherein the data processing module comprises a standardized processing sub-module, a first computing sub-module, a second computing sub-module, an updating sub-module, a third computing sub-module, a merging sub-module and an analyzing sub-module, wherein the standardized processing sub-module is used for carrying out standardized processing on the operation monitoring data to obtain an initial monitoring data set, and setting minimum sample data included in a clustered class center;
the first calculation sub-module is used for calculating the Euclidean distance of the initial monitoring data set relative to the minimum sample data and carrying out ascending arrangement on the obtained Euclidean distance;
the second calculation sub-module is used for taking k sample data farthest from each cluster as initial clustering center points of each cluster and calculating the distances between other sample data in the initial monitoring data set and the initial clustering center points of each cluster;
the updating sub-module is used for dividing other sample data in the initial monitoring data set into clusters with the minimum distance, and updating the initial clustering center of each cluster to obtain a first clustering result;
a third calculation sub-module, configured to calculate an average distance of sample data in a cluster in the first clustering result, and calculate a similarity degree between each category of the first clustering result as a dispersion degree of the cluster;
the merging submodule is used for combining the dispersion degree and the similarity degree, and merging similar sample data in clusters in the first clustering result to obtain a second clustering result;
and the analysis sub-module is used for analyzing the second aggregation result through a multivariate data analysis method to obtain operation target data.
3. The house safety monitoring and early warning system based on the intelligent home internet of things technology according to claim 1, wherein the safety analysis module comprises a data determination submodule, a data calculation submodule and a data analysis submodule, wherein the data determination submodule is used for acquiring historical monitoring data of the intelligent home and determining safety indexes of the intelligent home according to the historical monitoring data;
the data computing sub-module is used for outputting probability density of the safety indexes through Gaussian mixture, computing weight of the safety indexes through an entropy weight computing method and computing total safety indexes of the intelligent home;
and the data analysis sub-module is used for calculating the house security score containing the intelligent house so as to analyze the house security according to the house security score and obtain house security analysis information.
4. The house safety monitoring and early warning system based on the intelligent home internet of things technology according to claim 3, wherein the data computing sub-module comprises a first building unit, a second building unit, a third building unit and a fourth building unit, wherein the first building unit is used for building a first matrix according to safety indexes of intelligent home, and performing Gaussian mixture fitting on the first matrix to obtain probability densities corresponding to the safety indexes;
the second construction unit is used for calculating an entropy value corresponding to the safety index of the intelligent home by adopting the shannon entropy theory and constructing a second matrix according to the entropy value corresponding to the safety index;
the third construction unit is used for calculating the entropy weight of the safety index based on the second matrix and constructing an entropy weight matrix to obtain the weight of the safety index;
and the fourth construction unit is used for sequencing the safety indexes of the intelligent home according to the importance, and constructing a safety total index matrix of the intelligent home to obtain a safety total index.
5. The system for monitoring and early warning house safety based on the intelligent home internet of things according to claim 3, wherein the data analysis submodule comprises a determining unit, a normalizing unit and a scoring unit, wherein the determining unit is used for calculating an average total safety index according to a plurality of total safety indexes of the intelligent home and determining a safety area according to the average total safety index;
the normalization unit is used for normalizing the safety area to obtain a safety score threshold value, wherein the safety score threshold value is obtained according to the maximum and minimum average safety total indexes;
and the scoring unit is used for scoring the house safety containing the intelligent house based on the operation target data to obtain a house safety score, and analyzing the house safety based on the house safety score and the safety score threshold to obtain house safety analysis information.
6. The system for monitoring and early warning house safety based on the intelligent home internet of things according to claim 5, wherein the scoring unit comprises a building unit, a calculating unit and an analyzing unit, wherein the building unit is used for building a multiple linear regression model based on probability density, weight and total safety index of safety indexes of intelligent home;
the calculating unit is used for calculating a theoretical regression correction coefficient through the multiple linear regression model, wherein the theoretical regression correction coefficient is a theoretical correction weight value;
and the analysis unit is used for analyzing and scoring the result of the operation target data according to the theoretical regression correction coefficient to obtain the house security score.
7. The system for monitoring and early warning house safety based on the intelligent home internet of things technology according to claim 1, wherein the early warning sending module comprises an information acquisition sub-module, a first judging sub-module and a second judging sub-module, wherein the information acquisition sub-module is used for determining early warning level information according to the house safety analysis information and acquiring early warning measure information of corresponding levels;
the first judging submodule is used for judging whether to respond to the early warning measure information, and if the early warning measure information is the response, the early warning level information and the early warning measure information are updated;
and the second judging sub-module is used for evaluating the early warning measure behavior if the early warning measure information responds and judging whether the early warning measure behavior reaches a safe state or not, and if the early warning measure behavior reaches the safe state, the early warning is released.
8. The system for monitoring and early warning of house safety based on the internet of things technology of smart home as set forth in claim 1, wherein the safety early warning information includes at least early warning category information, early warning level information and early warning measure information of the smart home.
9. The house safety monitoring and early warning system based on the intelligent home internet of things technology as set forth in claim 1, wherein the operation method of the system comprises the following steps:
the method comprises the steps of reading operation monitoring data of the sensor to the intelligent home in real time;
receiving the operation monitoring data, and performing data processing on the operation monitoring data to obtain operation target data;
analyzing the house safety containing the intelligent home based on the operation target data to obtain house safety analysis information;
judging whether the house is safe or not according to the house safety analysis information, and if not, generating corresponding safety early warning information according to the house safety analysis information.
10. The system for monitoring and early warning of house safety based on the intelligent home internet of things technology according to claim 1, wherein the steps of receiving the operation monitoring data and performing data processing on the operation monitoring data to obtain operation target data include:
performing standardized processing on the operation monitoring data to obtain an initial monitoring data set, and setting minimum sample data included in a clustered class center;
calculating the Euclidean distance of the initial monitoring data set relative to the minimum sample data, and carrying out ascending arrangement on the obtained Euclidean distance;
taking k sample data with the farthest distance as initial clustering center points of each cluster, and calculating the distances between other sample data in the initial monitoring data set and the initial clustering center points of each cluster;
dividing other sample data in the initial monitoring data set into clusters with the minimum distance, and updating the initial clustering centers of the clusters to obtain a first clustering result;
calculating the average distance of sample data in a cluster in the first clustering result, and calculating the similarity degree among all the categories of the first clustering result as the dispersion degree of the cluster;
combining the dispersion degree and the similarity degree, and combining similar sample data in clusters in the first clustering result to obtain a second clustering result;
and analyzing the second aggregation result by a multivariate data analysis method to obtain operation target data.
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