CN113985747B - Intelligent home management system - Google Patents

Intelligent home management system Download PDF

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CN113985747B
CN113985747B CN202111325898.6A CN202111325898A CN113985747B CN 113985747 B CN113985747 B CN 113985747B CN 202111325898 A CN202111325898 A CN 202111325898A CN 113985747 B CN113985747 B CN 113985747B
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data
wireless sensor
wsn
environment
sensor node
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CN113985747A (en
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王炳坤
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De Rucci Healthy Sleep Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2642—Domotique, domestic, home control, automation, smart house
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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Abstract

The invention provides an intelligent home management system, which comprises a wireless sensor node, an Internet of things gateway, a wireless communication network, a data processing device and an environment adjusting device, wherein the wireless sensor node is connected with the Internet of things gateway; the wireless sensor node is used for acquiring environmental data of the position of the wireless sensor node; the Internet of things gateway is used for judging the correctness of the environmental data and transmitting the environmental data judged by the correctness to the wireless communication network; the wireless communication network is used for transmitting the environment data to the data processing device; the data processing device is used for formulating an indoor environment adjusting instruction based on the environment data and transmitting the indoor environment adjusting instruction to the environment adjusting device; the environment adjusting device is used for executing the indoor environment adjusting instruction. The invention finishes the judgment of the environment data striving at the edge acquisition end, and is beneficial to saving the computing resource of the data processing device, thereby leading the data processing device to be capable of correctly processing the effective environment data and being beneficial to timely adjusting the indoor environment.

Description

Intelligent home management system
Technical Field
The invention relates to the field of intelligent home, in particular to an intelligent home management system.
Background
With the development of the internet of things technology, more and more internet of things devices are used for realizing various functions related to home life in the field of home management. In buildings with large living spaces, such as villas, the existing indoor environment regulation and control mode generally only acquires data such as real-time temperature, humidity and the like in a wired mode, or acquires data such as real-time temperature, humidity and the like in a wireless sensor node mode. The wired collection mode needs to set up a large amount of cables, and the operation and maintenance cost of these cables is high in the later stage. The wireless sensor acquisition mode lacks the judgment on the correctness of the data when acquiring the data, so that some wrong data are transmitted to the data processing center, the computing resources of the data processing center are wasted, and the indoor environment is not convenient to adjust in time.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide an intelligent home management system, which includes a wireless sensor node, an internet of things gateway, a wireless communication network, a data processing device, and an environment adjusting device;
the wireless sensor node is used for acquiring environmental data of the position of the wireless sensor node and transmitting the environmental data to the gateway of the Internet of things;
the Internet of things gateway is used for judging the correctness of the environment data and transmitting the environment data judged by the correctness to the wireless communication network;
the wireless communication network is used for transmitting the environment data to the data processing device;
the data processing device is used for formulating an indoor environment adjusting instruction based on the environment data and transmitting the indoor environment adjusting instruction to the environment adjusting device;
the environment adjusting device is used for executing the indoor environment adjusting instruction;
the judging the correctness of the environment data comprises the following steps:
for wireless sensor node
Figure 134549DEST_PATH_IMAGE001
Obtained environmental data
Figure 529759DEST_PATH_IMAGE002
Is judged by
Figure 16235DEST_PATH_IMAGE003
Whether the correctness is passed or not is judged;
computing
Figure 104277DEST_PATH_IMAGE003
The degree of deviation index of (2):
Figure 558261DEST_PATH_IMAGE004
wherein
Figure 491581DEST_PATH_IMAGE005
To represent
Figure 98143DEST_PATH_IMAGE003
S represents the acquisition time of the environmental data,
Figure 357086DEST_PATH_IMAGE006
is shown and
Figure 32787DEST_PATH_IMAGE007
a set of wireless sensor nodes having a communication delay therebetween less than a preset communication delay threshold,
Figure 35378DEST_PATH_IMAGE008
representing environmental data obtained by the wireless sensor node k,
Figure 496447DEST_PATH_IMAGE009
a reference scale value representing a wireless sensor node k;
Figure 660712DEST_PATH_IMAGE010
representing wireless sensor nodes
Figure 89288DEST_PATH_IMAGE011
The accumulated length of time of operation of (c),
Figure 629991DEST_PATH_IMAGE012
expressing a unit time length error value;
and judging whether the deviation degree index is larger than a preset deviation degree index judgment threshold value, if so, indicating that the environmental data does not pass the correctness judgment, and if not, indicating that the environmental data passes the correctness judgment.
Preferably, the reference ratio value is calculated by:
Figure 945565DEST_PATH_IMAGE013
wherein,
Figure 546311DEST_PATH_IMAGE014
respectively represents the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node k in a space rectangular coordinate system,
Figure 211253DEST_PATH_IMAGE015
respectively represents the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node wsn in a space rectangular coordinate system,
Figure 555646DEST_PATH_IMAGE016
，
Figure 991307DEST_PATH_IMAGE017
，
Figure 497374DEST_PATH_IMAGE018
to represent
Figure 900543DEST_PATH_IMAGE019
The total number of wireless sensor nodes contained in it,
Figure 783048DEST_PATH_IMAGE020
representing the distance between wireless sensor node k and wireless sensor node wsn,
Figure 73215DEST_PATH_IMAGE021
representing wireless sensor nodes wsn and
Figure 750184DEST_PATH_IMAGE022
a variance of distances between wireless sensor nodes contained in (a);
Figure 375069DEST_PATH_IMAGE023
and ctr represents a preset control parameter,
Figure 61266DEST_PATH_IMAGE024
representing wireless sensor nodes wsn and
Figure 205939DEST_PATH_IMAGE025
the variance of the environmental data collected between the wireless sensor nodes contained in (a).
Preferably, the environmental data includes temperature data, humidity data and PM10 data.
Preferably, the wireless communication network comprises a cellular mobile communication network or a WiFi communication network.
Preferably, the formulating the indoor environment adjustment instruction based on the environment data includes:
determining a data type of the environmental data;
and comparing the environment data with a working value interval corresponding to the data type of the environment data to determine an environment adjusting instruction.
Preferably, the determining the environment adjustment instruction comprises:
if the environmental data is larger than the working value interval, generating an environmental regulation instruction for reducing the monitoring value of the data type of the environmental data;
and if the environmental data is smaller than the working value interval, generating an environmental regulation instruction for improving the monitoring value of the data type of the environmental data.
Preferably, the environment conditioning device comprises a temperature conditioning device, a humidity conditioning device and a PM10 conditioning device.
The invention combines the environmental data obtained by the wireless sensor nodes wsn with the environmental data obtained by the wireless sensor nodes wsn at the data acquisition end
Figure 319389DEST_PATH_IMAGE026
The difference between the environmental data obtained by the wireless sensor nodes and the accumulated working time of the wireless sensor nodes wsn are considered, an accurate deviation degree index is determined, and then whether the environmental data passes the correctness judgment is judged according to the deviation degree index. This kind of mode of setting up has accomplished the judgement of striving for nature to the environmental data at the edge acquisition end to do not need to judge the exactness of environmental data again in data processing device department, be favorable to practicing thrift data processing device's computational resource, thereby make data processing device can carry out accurate processing to effectual environmental data, be favorable to in time adjusting indoor environment. In addition, the present invention does not directly compare environment data obtained by the wireless sensor node wsn with a certain fixed threshold value to determine accuracy. Since the data error of the wireless sensor node increases with the increase of the operating time, it is obvious that such a determination manner will eventually obtain an erroneous determination result as the operating time of the wireless sensor node increases. But the invention passes through
Figure 431570DEST_PATH_IMAGE006
The environment data obtained by the wireless sensor nodes in the method is accumulated according to the reference proportional value, and the accumulated error of the wireless sensor nodes wsn is also considered when the deviation degree index value is calculated, so that the judgment mode of the method can be adaptively changed according to the time lapse, and the accuracy of the judgment of the environment data is maintained.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of an intelligent home management system according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, in an embodiment, the present invention provides an intelligent home management system, including a wireless sensor node, an internet of things gateway, a wireless communication network, a data processing device, and an environment adjusting device;
the wireless sensor node is used for acquiring environmental data of the position of the wireless sensor node and transmitting the environmental data to the gateway of the Internet of things;
the Internet of things gateway is used for judging the correctness of the environment data and transmitting the environment data judged by the correctness to the wireless communication network;
the wireless communication network is used for transmitting the environment data to the data processing device;
the data processing device is used for formulating an indoor environment adjusting instruction based on the environment data and transmitting the indoor environment adjusting instruction to the environment adjusting device;
the environment adjusting device is used for executing the indoor environment adjusting instruction;
the judging the correctness of the environment data comprises the following steps:
for wireless sensor node
Figure 655878DEST_PATH_IMAGE001
Obtained environmental data
Figure 920637DEST_PATH_IMAGE002
Is judged by
Figure 204988DEST_PATH_IMAGE027
Whether the correctness is passed or not is judged;
computing
Figure 541816DEST_PATH_IMAGE027
The degree of deviation index of (2):
Figure 569815DEST_PATH_IMAGE028
wherein
Figure 689081DEST_PATH_IMAGE029
To represent
Figure 331283DEST_PATH_IMAGE030
S represents the acquisition time of the environmental data,
Figure 965527DEST_PATH_IMAGE006
is shown and
Figure 734900DEST_PATH_IMAGE007
a set of wireless sensor nodes having a communication delay therebetween less than a preset communication delay threshold,
Figure 770989DEST_PATH_IMAGE031
representing wireless transmissionsThe environmental data obtained by the sensor node k,
Figure 584093DEST_PATH_IMAGE009
a reference scale value representing a wireless sensor node k;
Figure 705633DEST_PATH_IMAGE032
representing wireless sensor nodes
Figure 13118DEST_PATH_IMAGE011
The accumulated length of time of operation of (c),
Figure 169292DEST_PATH_IMAGE033
expressing a unit time length error value;
and judging whether the deviation degree index is larger than a preset deviation degree index judgment threshold value, if so, indicating that the environmental data does not pass the correctness judgment, and if not, indicating that the environmental data passes the correctness judgment.
The invention combines the environmental data obtained by the wireless sensor nodes wsn with the environmental data obtained by the wireless sensor nodes wsn at the data acquisition end
Figure 153298DEST_PATH_IMAGE026
The difference between the environmental data obtained by the wireless sensor nodes and the accumulated working time of the wireless sensor nodes wsn are considered, an accurate deviation degree index is determined, and then whether the environmental data passes the correctness judgment is judged according to the deviation degree index. This kind of mode of setting up has accomplished the judgement of striving for nature to the environmental data at the edge acquisition end to do not need to judge the exactness of environmental data again in data processing device department, be favorable to practicing thrift data processing device's computational resource, thereby make data processing device can carry out accurate processing to effectual environmental data, be favorable to in time adjusting indoor environment. In addition, the present invention does not directly compare environment data obtained by the wireless sensor node wsn with a certain fixed threshold value to determine accuracy. The data error of the wireless sensor node can increase along with the increase of the working time, so that the data error of the wireless sensor node can increase along with the increase of the working timeObviously, the judgment mode can finally obtain wrong judgment results as the working time of the wireless sensor node is prolonged. But the invention passes through
Figure 762134DEST_PATH_IMAGE006
The environment data obtained by the wireless sensor nodes in the method is accumulated according to the reference proportional value, and the accumulated error of the wireless sensor nodes wsn is also considered when the deviation degree index value is calculated, so that the judgment mode of the method can be adaptively changed according to the time lapse, and the accuracy of the judgment of the environment data is maintained.
Preferably, the internet of things gateway is further configured to divide the wireless sensor node into a primary node and a secondary node;
the primary node is used for acquiring environmental data of the position where the primary node is located and transmitting the environmental data to the secondary node;
and the secondary node is used for transmitting the environment data sent by the primary node to the gateway of the Internet of things.
When the area needing to monitor the environmental data is large, the single wireless sensor node cannot directly communicate with the gateway of the internet of things due to the limitation of power when the distance between the single wireless sensor node and the gateway of the internet of things is large, and therefore the single wireless sensor node needs to communicate with the gateway of the internet of things in a multi-hop communication mode. Therefore, the wireless sensor node is divided into the primary node and the secondary node, and the pyramid structure is adopted, so that the remote communication between the wireless sensor node and the gateway of the Internet of things is realized.
Preferably, the gateway of the internet of things acquires attribute data of the wireless sensor nodes at fixed time intervals, completes the division of the primary nodes and the secondary nodes according to the attribute data, and sends the divided nodes to each wireless sensor node.
The attribute data includes coordinates, remaining power, communication delay with other communication devices, and the like.
Preferably, the secondary node is further configured to obtain environment data of a location where the secondary node is located, and transmit the environment data to the internet of things gateway.
The secondary node has a data forwarding task and also needs to take a data acquisition task to acquire the environmental data of the position of the secondary node.
Preferably, the dividing the wireless sensor node into a primary node and a secondary node includes:
the reference coordinates are calculated as follows
Figure 607730DEST_PATH_IMAGE034
：
Figure 618411DEST_PATH_IMAGE035
Wherein,
Figure 776248DEST_PATH_IMAGE036
represents the set of all wireless sensor nodes,
Figure 872380DEST_PATH_IMAGE037
respectively represent the x-axis coordinate, the y-axis coordinate, the z-axis coordinate,
Figure 521667DEST_PATH_IMAGE038
represent
Figure 652434DEST_PATH_IMAGE036
The total number of wireless sensor nodes contained in;
calculate each one separately
Figure 978242DEST_PATH_IMAGE036
The transmission performance index of each wireless sensor node:
Figure 296091DEST_PATH_IMAGE039
wherein,
Figure 749069DEST_PATH_IMAGE040
to represent
Figure 734342DEST_PATH_IMAGE036
In a wireless sensor node
Figure 231052DEST_PATH_IMAGE041
The transmission performance index of (a) is,
Figure 36197DEST_PATH_IMAGE042
to represent
Figure 27286DEST_PATH_IMAGE043
Coordinate of (2) and
Figure 867066DEST_PATH_IMAGE044
is measured by the distance of a straight line between the coordinates of (c),
Figure 534677DEST_PATH_IMAGE045
，
Figure 92697DEST_PATH_IMAGE046
for a preset proportionality coefficient, U represents a wireless sensor node
Figure 356319DEST_PATH_IMAGE047
The total number of other wireless sensor nodes of communication range,
Figure 771645DEST_PATH_IMAGE048
representing wireless sensor nodes
Figure 423206DEST_PATH_IMAGE047
Of the communication range of
Figure 140626DEST_PATH_IMAGE044
The straight-line distance between the two,
Figure 535836DEST_PATH_IMAGE049
coordinates representing the vs-th wireless sensor node and
Figure 537158DEST_PATH_IMAGE044
the straight-line distance between the coordinates of (c),
Figure 359621DEST_PATH_IMAGE050
represent
Figure 564337DEST_PATH_IMAGE036
The total number of other wireless sensor nodes in the communication range of the vth wireless sensor node,
Figure 763237DEST_PATH_IMAGE051
is shown at
Figure 619067DEST_PATH_IMAGE036
Coordinate sum of all wireless sensor nodes in communication range of every vs wireless sensor node
Figure 612431DEST_PATH_IMAGE052
The linear distance therebetween;
will be provided with
Figure 304443DEST_PATH_IMAGE036
The wireless sensor node with the largest transmission performance index is used as the 1 st secondary node;
the v secondary node is obtained in the following mode, and v is greater than or equal to 2:
acquiring a set of wireless sensor nodes with communication distances smaller than R from the v-1 th secondary node
Figure 307034DEST_PATH_IMAGE053
；
Will be provided with
Figure 17370DEST_PATH_IMAGE053
The wireless sensor node with the largest transmission performance index and not belonging to the secondary node is used as the vth secondary node;
the maximum value of v is obtained as follows:
Figure 181635DEST_PATH_IMAGE054
wherein,
Figure 360944DEST_PATH_IMAGE055
the maximum value of v is represented by,
Figure 901647DEST_PATH_IMAGE056
representing the total area of the monitoring area for which the wireless sensor node is responsible,
Figure 457700DEST_PATH_IMAGE057
represents the average coverage area of each wireless sensor node,
Figure 58446DEST_PATH_IMAGE058
the redundant coverage coefficients are represented by a representation of,
Figure 459471DEST_PATH_IMAGE059
；
after the acquisition of the secondary node is completed,
Figure 803865DEST_PATH_IMAGE036
the rest wireless sensor nodes in the network are used as primary nodes.
In the process of acquiring the primary node and the secondary node, the secondary node is acquired by adopting a spreading type acquisition mode, namely, a first secondary node is selected, and then a wireless sensor node meeting the distance requirement is taken as a next secondary node from neighbor nodes of the secondary node. By the adoption of the acquisition mode, at least one neighbor two-sister node is arranged between every two secondary nodes, and therefore the pyramid structure is formed. Meanwhile, when the transmission performance index is calculated, the concept of a reference coordinate is introduced, wherein the reference coordinate is a virtual point in a space rectangular coordinate system and represents that the average distance between the reference coordinate and other wireless sensor nodes is the minimum in the point. Therefore, the larger the transmission performance index is, the smaller the average distance between the wireless sensor node and other wireless sensor nodes is, so that the primary node can communicate with the secondary node by adopting the lowest transmission power loss, and the transmission loss is reduced as much as possible while the secondary node is uniformly distributed.
Preferably, transmitting the environmental data to the secondary node comprises:
the primary node transmits the environment data to a secondary node with the minimum communication delay with the primary node.
In another embodiment, the primary node may also transmit the environmental data to the secondary node that is the smallest distance from itself.
Preferably, transmitting the environment data to the internet of things gateway includes:
if the distance between the Internet of things gateway and the secondary node is smaller than or equal to the communication radius of the secondary node, the secondary node directly sends the environment data to the Internet of things gateway;
and if the distance between the gateway of the Internet of things and the secondary node is greater than the communication radius of the secondary node, selecting a target node from other secondary nodes within the communication radius of the target node, and transmitting the environment data to the target node.
Preferably, the selecting a target node from other secondary nodes within a communication radius thereof includes:
storing other secondary nodes within its communication radius into the set
Figure 223214DEST_PATH_IMAGE060
Performing the following steps;
respectively calculate
Figure 994861DEST_PATH_IMAGE060
The transmission efficiency value of each secondary node in (1):
Figure 883182DEST_PATH_IMAGE061
wherein,
Figure 765687DEST_PATH_IMAGE062
to represent
Figure 305122DEST_PATH_IMAGE060
The transmission efficiency value of the secondary node seu contained in (1),
Figure 247670DEST_PATH_IMAGE063
which represents a pre-set weight parameter that is,
Figure 623288DEST_PATH_IMAGE064
indicating the current amount of power of the seu,
Figure 496435DEST_PATH_IMAGE065
indicating the full charge of seu,
Figure 703425DEST_PATH_IMAGE066
to represent
Figure 754558DEST_PATH_IMAGE067
The total number of secondary nodes contained in it,
Figure 679789DEST_PATH_IMAGE068
the average communication delay between the secondary node and the gateway of the Internet of things is represented,
Figure 93977DEST_PATH_IMAGE069
represents the total number of other secondary nodes contained within the communication radius of the seu;
will be provided with
Figure 421053DEST_PATH_IMAGE060
And taking the secondary node with the maximum transmission efficiency value as a target node.
If the communication with the gateway of the Internet of things cannot be directly carried out, multi-hop communication with the gateway of the Internet of things is required, in order to balance the transmission electric quantity loss of the multi-hop communication, the invention considers the aspects of electric quantity, average communication delay between the electric quantity and the gateway of the Internet of things, the total number of other secondary nodes contained in a communication radius and the like, so that the higher the proportion of the residual electric quantity is, the smaller the average communication delay between the electric quantity and the gateway of the Internet of things is, the higher the total number of other secondary nodes contained in the communication radius is, the higher the transmission efficiency value of the secondary nodes is, the transmission electric quantity loss is reduced, the electric quantity loss between the secondary nodes is balanced, and the average service life of the secondary nodes is effectively prolonged.
Preferably, the reference ratio value is calculated by:
Figure 377508DEST_PATH_IMAGE070
wherein,
Figure 790035DEST_PATH_IMAGE071
respectively represents the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node k in a space rectangular coordinate system,
Figure 4984DEST_PATH_IMAGE072
respectively represents the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node wsn in a space rectangular coordinate system,
Figure 186567DEST_PATH_IMAGE073
，
Figure 579502DEST_PATH_IMAGE074
，
Figure 213746DEST_PATH_IMAGE075
to represent
Figure 966807DEST_PATH_IMAGE019
The total number of wireless sensor nodes contained in it,
Figure 268475DEST_PATH_IMAGE076
representing the distance between wireless sensor node k and wireless sensor node wsn,
Figure 832312DEST_PATH_IMAGE021
representing wireless sensor nodes wsn and
Figure 953852DEST_PATH_IMAGE022
a variance of distances between wireless sensor nodes contained in (a);
Figure 510604DEST_PATH_IMAGE077
and ctr represents a preset control parameter,
Figure 666779DEST_PATH_IMAGE078
representing wireless sensor nodes wsn and
Figure 401516DEST_PATH_IMAGE025
the variance of the environmental data collected between the wireless sensor nodes contained in (a).
In the above embodiment, the present invention considers the spatial distance and the difference between the acquired environmental data, and improves the accuracy of the obtained reference ratio value. Specifically, the smaller the spatial distance, the smaller the difference in the environmental data, the larger the reference ratio value, that is, the larger the similarity to wsn, the larger the reference ratio value of the wireless sensor node, and the greater the importance.
Preferably, the environmental data includes temperature data, humidity data and PM10 data.
Specifically, the environmental data may further include air flow rate, harmful gas concentration, and the like.
Preferably, the wireless communication network comprises a cellular mobile communication network or a WiFi communication network.
The whole process adopts a wireless transmission mode, the laying of cables can be avoided, and the cost of follow-up operation and maintenance and the difficulty of the operation and maintenance are reduced. Especially, some cables adopting the concealed wire design have extremely high operation and maintenance difficulty if problems occur in the later period.
Preferably, the formulating the indoor environment adjustment instruction based on the environment data includes:
determining a data type of the environmental data;
and comparing the environment data with a working value interval corresponding to the data type of the environment data to determine an environment adjusting instruction.
The operating value range is a desired range of the data type, and for example, the operating value range of the data type, i.e., the temperature, is set to the range of [25.5 ℃, 26 ℃ ]. The data types of the environmental data include temperature, humidity, and the like.
Preferably, the determining the environmental adjustment instruction comprises:
if the environmental data is larger than the working value interval, generating an environmental regulation instruction for reducing the monitoring value of the data type of the environmental data;
and if the environmental data is smaller than the working value interval, generating an environmental regulation instruction for improving the monitoring value of the data type of the environmental data.
For example, when the monitored value of the temperature type environmental data is 27 ℃, the indoor temperature is lowered by the temperature adjusting device. When the monitored value of the temperature type environmental data is 25 ℃, the indoor temperature is increased by the temperature adjusting device. I.e. to adjust the working value intervals of various types of ambient data networks.
Preferably, the environment conditioning device comprises a temperature conditioning device, a humidity conditioning device and a PM10 conditioning device.
Such as air conditioners, humidifiers, air purifiers, etc.
While embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (6)

1. An intelligent home management system is characterized by comprising wireless sensor nodes, an Internet of things gateway, a wireless communication network, a data processing device and an environment adjusting device;
the wireless sensor node is used for acquiring environmental data of the position of the wireless sensor node and transmitting the environmental data to the gateway of the Internet of things;
the Internet of things gateway is used for judging the correctness of the environment data and transmitting the environment data judged by the correctness to the wireless communication network;
the wireless communication network is used for transmitting the environment data to the data processing device;
the data processing device is used for formulating an indoor environment adjusting instruction based on the environment data and transmitting the indoor environment adjusting instruction to the environment adjusting device;
the environment adjusting device is used for executing the indoor environment adjusting instruction;
the judging the correctness of the environment data comprises the following steps:
for the environment data evdai (wsn, s) obtained by the wireless sensor node wsn, whether evdat (wsn, s) passes the correctness judgment is judged in the following way;
calculating the deviation degree index of evdat (wsn, s):
Figure FDA0003551540230000011
wherein devindex [ evdat (wsn, s)]Indicating an index of deviation of evdat (wsn, s), s indicating acquisition time of environmental data, wsnu，neiA set of wireless sensor nodes representing that communication delay with wsn is less than a preset communication delay threshold value, erdat (k, s) representing environment data obtained by the wireless sensor node k, weightskA reference scale value representing a wireless sensor node k; cunwkh (wsn) represents the accumulated working time of the wireless sensor node wsn, and unerval represents a unit time length error value;
judging whether the deviation degree index is larger than a preset deviation degree index judgment threshold value, if so, indicating that the environmental data does not pass the correctness judgment, and if not, indicating that the environmental data passes the correctness judgment;
the reference ratio value is calculated as follows:
Figure FDA0003551540230000021
wherein x isk、yk、zkRespectively representing the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node k in a space rectangular coordinate system, wherein x is the coordinate value of the wireless sensor node kwsn、ywsn、zwsnRespectively represents the coordinate values of an x axis, a y axis and a z axis of the wireless sensor node wsn in a space rectangular coordinate system,
Figure FDA0003551540230000022
Figure FDA0003551540230000023
numwsnu，neirepresentation wsnu，neiThe total number of wireless sensor nodes contained in (a), lodis (wsn, k) represents the distance between the wireless sensor node k and the wireless sensor node wsn, varianrf1Representing wireless sensor nodes wsn and wsnu，neiA variance of distances between wireless sensor nodes contained in (a);
Figure FDA0003551540230000031
ctr denotes a preset control parameter, varianrf2Representing wireless sensor nodes wsn and wsnu，neiThe variance of the environmental data collected between the wireless sensor nodes contained in (a).
2. A smart home management system as claimed in claim 1, wherein the environmental data comprises temperature data, humidity data and PM10 data.
3. The intelligent home management system of claim 1, wherein the wireless communication network comprises a cellular mobile communication network or a WiFi communication network.
4. The intelligent home management system of claim 1, wherein the formulating indoor environment adjustment instructions based on the environmental data comprises:
determining a data type of the environmental data;
and comparing the environment data with a working value interval corresponding to the data type of the environment data to determine an environment adjusting instruction.
5. The smart home management system of claim 4, wherein the determining environmental adjustment instructions comprises:
if the environmental data is larger than the working value interval, generating an environmental regulation instruction for reducing the monitoring value of the data type of the environmental data;
and if the environmental data is smaller than the working value interval, generating an environmental regulation instruction for improving the monitoring value of the data type of the environmental data.
6. A smart home management system as claimed in claim 2, wherein the environmental conditioning means comprises temperature conditioning means, humidity conditioning means and PM10 conditioning means.
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