CN116170770A - Automatic sensing method and device for realizing sensor based on Internet of things - Google Patents

Automatic sensing method and device for realizing sensor based on Internet of things Download PDF

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CN116170770A
CN116170770A CN202310452414.7A CN202310452414A CN116170770A CN 116170770 A CN116170770 A CN 116170770A CN 202310452414 A CN202310452414 A CN 202310452414A CN 116170770 A CN116170770 A CN 116170770A
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sensing
sensor
center
centers
transmission frequency
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CN116170770B (en
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李康
接佳乐
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Hangzhou Radium Lake Technology Co ltd
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30Services specially adapted for particular environments, situations or purposes
    • H04W4/38Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W72/00Local resource management
    • H04W72/04Wireless resource allocation
    • H04W72/044Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453Resources in frequency domain, e.g. a carrier in FDMA
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W84/00Network topologies
    • H04W84/18Self-organising networks, e.g. ad-hoc networks or sensor networks
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02DCLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00Reducing energy consumption in communication networks
    • Y02D30/70Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention relates to the technical field of sensing data transmission, in particular to an automatic sensing method and device for realizing a sensor based on the Internet of things, comprising the following steps: determining all sensors responding to a collection instruction at present, wherein all sensors execute transmission of sensing data through a wireless sensor network, determining a plurality of sensing centers of the wireless sensor network, performing region division on all the sensors according to the plurality of sensing centers to obtain a plurality of groups of regional sensor sets, distributing data transmission frequency to each sensing center to obtain a central transmission frequency, distributing frequency to each regional sensor in the regional sensor sets according to the central transmission frequency to obtain sensing transmission frequency, receiving the sensing data generated by each regional sensor, and sequentially transmitting the generated sensing data to an initiator of the collection instruction on the premise of the sensing transmission frequency. The invention solves the problem that the feedback of the sensing data is jammed or untimely under the premise of not improving the communication signal of the environment where the sensor is located.

Description

Automatic sensing method and device for realizing sensor based on Internet of things
Technical Field
The present invention relates to the field of sensor data transmission technologies, and in particular, to an automatic sensing method, an apparatus, an electronic device, and a computer readable storage medium for implementing a sensor based on the internet of things.
Background
Along with the development of science and technology, various types of sensors in various industries, such as pressure sensors, position sensors, liquid level sensors, energy consumption sensors, speed sensors, acceleration sensors, radiation sensors, heat-sensitive sensors and the like, have been increasingly applied to various complex and severe scenes, such as glaciers, tunnels and the like.
It is conceivable that in a severe complex scene, because the communication signal is relatively poor, there is often a phenomenon that one channel transmits multiple types of sensing data simultaneously, so that the sensing data is blocked or untimely in feedback, and how to timely recover the sensing data is an urgent problem to be solved.
The current common method is to enhance the base station signal of the environment where the sensor is located, thereby improving the data transmission capacity of the channel.
Therefore, how to solve the phenomenon of congestion or untimely feedback of the sensing data on the premise of not improving the communication signal of the environment where the sensor is located is a technical problem which needs to be solved urgently.
Disclosure of Invention
The invention provides an automatic sensing method, an automatic sensing device and a computer readable storage medium for realizing a sensor based on the Internet of things, which mainly aim to solve the problem that sensing data is returned to be jammed or untimely on the premise of not improving communication signals of the environment where the sensor is located.
In order to achieve the above object, the present invention provides an automatic sensing method for implementing a sensor based on the internet of things, including:
receiving a collection instruction of sensing data, and determining all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network;
according to the number of the sensors, a plurality of sensing centers in the wireless sensor network are determined, wherein the method for determining the sensing centers comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure SMS_1
wherein ,
Figure SMS_3
representing the sensing center, +.>
Figure SMS_4
Representing a sensor->
Figure SMS_6
Representing the number of sensing centers, +.>
Figure SMS_7
Representing the number of sensors, +.>
Figure SMS_8
and
Figure SMS_9
Respectively representing the preset variance and the expected +.>
Figure SMS_10
Representing rounding symbols, ++>
Figure SMS_2
and
Figure SMS_5
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
Constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
performing area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
distributing data transmission frequency to each sensing center to obtain center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain sensing transmission frequency;
and receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
Optionally, the determining all sensors currently responding to the collection instruction includes:
acquiring IP addresses of all sensors prestored in a database;
triggering a sensor test program to generate a sensor test instruction, and sequentially sending the sensor test instruction to each sensor according to the IP address, wherein the sensor test instruction is sent to each sensor through a wireless sensor network;
and eliminating the sensors which do not return response instructions according to the sensor test instructions and the sensors with the return time of the response instructions being longer than the time threshold value, so as to obtain all the sensors.
Optionally, the sensor includes a pressure sensor, a position sensor, a liquid level sensor, an energy consumption sensor, a speed sensor, an acceleration sensor, a radiation sensor, a thermal sensor.
Optionally, the performing area division on all the sensors according to the plurality of sensing centers to obtain a plurality of groups of area sensor sets includes:
the following is performed for each sensor:
acquiring a sensor three-dimensional coordinate corresponding to a sensor and a sensing center three-dimensional coordinate corresponding to each sensing center;
calculating a distance value between the three-dimensional coordinates of the sensor and the three-dimensional coordinates of each sensing center; obtaining a distance value set, wherein the number of the distance values in the distance value set is the same as that of the sensing centers;
Selecting a minimum distance value from the distance value set, and determining a sensing center corresponding to the minimum distance value, namely, a sensing center with a corresponding relation with the sensor;
and executing area division according to the minimum distance value corresponding to the sensing center until all the sensors determine the corresponding sensing center, so as to obtain a plurality of groups of area sensor sets.
Optionally, the performing area division according to the minimum distance value corresponding to the sensing center to obtain a plurality of groups of area sensor sets includes:
acquiring the minimum distance value between all the sensors corresponding to each sensing center and the sensors;
screening out the maximum distance value from all the minimum distance values to obtain the radius of the region;
and constructing an area circle by taking the sensing center as an area center according to the area center and the area radius, wherein all sensors in the area circle are the area sensor set.
Optionally, the allocating a data transmission frequency to each sensing center to obtain a center transmission frequency includes:
determining all available channels of the wireless sensor network at the current time to obtain an available channel set;
receiving the lowest transmission frequency and frequency range input by a user;
and distributing data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency range to obtain center transmission frequency.
Optionally, the allocating a data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency band range to obtain a center transmission frequency includes:
screening channels conforming to the frequency range from the available channel sets to obtain one or more frequency range channels;
non-repeated extraction of each frequency band channel from one or more frequency band channels, and
the center transmission frequency is calculated according to the following formula:
Figure SMS_11
wherein ,
Figure SMS_12
representing the sensing center +.>
Figure SMS_13
Center transmission frequency of>
Figure SMS_14
Representing the lowest transmission frequency of the user input, +.>
Figure SMS_15
Indicate->
Figure SMS_16
Individual frequency band channels>
Figure SMS_17
Indicate->
Figure SMS_18
A unit frequency step factor of each frequency band channel.
Optionally, the allocating a frequency to each area sensor in the area sensor set according to the central transmission frequency to obtain a sensing transmission frequency includes:
the following calculation is performed for each area sensor to obtain the sensing transmission frequency:
calculating a distance value between each area sensor and a corresponding sensing center, and
acquiring the data generation amount of each area sensor in unit time;
and calculating to obtain the corresponding sensing transmission frequency according to the distance value and the data generation quantity.
Optionally, the calculating to obtain the corresponding sensing transmission frequency according to the distance value and the data generation amount includes:
Figure SMS_19
wherein ,
Figure SMS_20
representation area sensor->
Figure SMS_21
The assigned sensor transmission frequency, +.>
Figure SMS_22
The distribution factor representing the sensing transmission frequency is calculated by the following steps:
Figure SMS_23
wherein ,
Figure SMS_25
representation area sensor->
Figure SMS_27
Is>
Figure SMS_29
Distance value of>
Figure SMS_30
Representation area sensor->
Figure SMS_31
Data generation amount per unit time, +.>
Figure SMS_32
Representation area sensor->
Figure SMS_33
Is>
Figure SMS_24
Distance value of (2)Weight factor of->
Figure SMS_26
Representation area sensor->
Figure SMS_28
A weight factor for the amount of data generated by the system.
In order to solve the above problems, the present invention further provides an automatic sensing device for implementing a sensor based on the internet of things, the device comprising:
the system comprises a collection instruction receiving module, a wireless sensor network and a data processing module, wherein the collection instruction receiving module is used for receiving a collection instruction of sensing data and determining all sensors responding to the collection instruction at present, and all sensors execute transmission of the sensing data through the wireless sensor network;
the sensing center determining module is used for determining a plurality of sensing centers in the wireless sensor network according to the number of the sensors, wherein the sensing center determining method comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure SMS_34
wherein ,
Figure SMS_36
representing the sensing center, +.>
Figure SMS_38
Representing a sensor->
Figure SMS_39
Representing the number of sensing centers, +.>
Figure SMS_40
Representing the number of sensors, +.>
Figure SMS_41
and
Figure SMS_42
Respectively representing a preset variance and a desire,
Figure SMS_43
representing rounding symbols, ++>
Figure SMS_35
and
Figure SMS_37
A first weight factor and a second weight factor representing the number of calculated sensing centers; />
Acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
the area dividing module is used for carrying out area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
The sensing transmission frequency distribution module is used for distributing data transmission frequency to each sensing center to obtain a center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain a sensing transmission frequency;
the sensing data receiving module is used for receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so that automatic sensing acquisition of the sensing data is realized.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
a memory storing at least one instruction; and the processor executes the instructions stored in the memory to realize the automatic sensing method based on the Internet of things.
In order to solve the above problems, the present invention further provides a computer readable storage medium, where at least one instruction is stored, where the at least one instruction is executed by a processor in an electronic device to implement the above-mentioned automatic sensing method based on the internet of things for implementing a sensor.
In order to solve the problems described in the background art, the embodiment of the invention firstly receives a collection instruction of sensing data, determines all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network, and the wireless sensor network is a distributed sensing network, the network terminal of the wireless sensor network is the sensor, the wireless sensor network can effectively improve the feedback effect of the sensing data of the sensors, compared with the traditional communication technology, the time can be saved, excessive waste of manpower resources can be prevented, further, a plurality of sensing centers of the wireless sensor network are determined according to the number of the sensors, the area division is performed on all the sensors according to the plurality of sensing centers, a plurality of area sensor sets are obtained, each sensing center corresponds to each area sensor set, and the main effect of the sensing center is to reasonably allocate the transmission efficiency of the sensing data of each sensor, so that the phenomenon that the channel is not timely in feedback of the sensing data is prevented, the data transmission frequency is allocated to each sensing center, the center frequency is obtained, the sensing frequency is allocated to each sensing center, the sensing frequency is automatically allocated to each sensing area, and the data is automatically generated according to the number of sensing area, and the data is automatically acquired according to the frequency allocation of the sensing frequency, and the data is sequentially generated. Therefore, the automatic sensing method, the device, the electronic equipment and the computer readable storage medium for realizing the sensor based on the Internet of things mainly aim to solve the phenomenon of congestion or untimely return of sensing data on the premise of not improving communication signals of the environment where the sensor is located.
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Fig. 1 is a schematic flow chart of an automatic sensing method for implementing a sensor based on the internet of things according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of an automatic sensing device for implementing a sensor based on the Internet of things according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the automatic sensing method for implementing a sensor based on the internet of things according to an embodiment of the present invention.
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
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 embodiment of the application provides an automatic sensing method for realizing a sensor based on the Internet of things. The execution main body of the automatic sensing method for realizing the sensor based on the internet of things comprises at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the automatic sensing method based on the internet of things for realizing the sensor can be executed by software or hardware installed in the terminal equipment or the server equipment, and the software can be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Referring to fig. 1, a flow chart of an automatic sensing method for implementing a sensor based on the internet of things according to an embodiment of the invention is shown. In this embodiment, the method for implementing automatic sensing of a sensor based on the internet of things includes:
s1, receiving a collection instruction of sensing data, and determining all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network.
In the embodiment of the invention, the initiator of the collection instruction of the sensing data is different according to the type of the sensor, the application scene and the like. For example, environmental monitoring personnel in a city of Zhang Zuowei now plan to collect environmental data of an industrial park, and thus initiate a collection instruction of sensing data, the purpose of which is to connect all sensors in the industrial park through a wireless sensor network, and acquire sensing data of each sensor.
In detail, the determining all sensors currently responding to the collection instruction includes:
acquiring IP addresses of all sensors prestored in a database;
triggering a sensor test program to generate a sensor test instruction, and sequentially sending the sensor test instruction to each sensor according to the IP address, wherein the sensor test instruction is sent to each sensor through a wireless sensor network;
And eliminating the sensors which do not return response instructions according to the sensor test instructions and the sensors with the return time of the response instructions being longer than the time threshold value, so as to obtain all the sensors.
Further, the sensors include, but are not limited to, pressure sensors, position sensors, level sensors, energy consumption sensors, speed sensors, acceleration sensors, radiation sensors, thermal sensors, and the like. For example, if the environmental class initiated by the sheetlet transmits a data collection instruction, the sensor should also include a PH measurement sensor, a heavy metal detection sensor, an air composition monitoring sensor, and the like.
In addition, the wireless sensor network (Wireless Sensor Networks, WSN) is a distributed sensor network, the terminals of the sensor network are all sensors in the embodiment of the invention, and the sensors communicate in a wireless mode, so that the network is flexible to set, and can be connected with the Internet in a wired or wireless mode. The effect of acquiring the sensing data of the sensor can be effectively improved through the WSN mode, time is saved, and excessive waste of human resources is prevented.
S2, determining a plurality of sensing centers in the wireless sensor network according to the number of the sensors.
It should be explained that there are huge numbers of sensors in the application scenario, if the sensing data of each sensor is obtained in sequence directly through the wireless sensor network, the phenomenon of sensor data collection blocking or delay is very easy to be caused, and the main effect of the sensing center is to divide the sensors in a regional manner, so that orderly and coordinated collection of the sensor data is ensured.
Further, the determining a plurality of sensing centers in the wireless sensor network according to the number of the sensors includes:
the number of sensing centers is calculated according to the following formula:
Figure SMS_44
wherein ,
Figure SMS_46
representing the sensing center, +.>
Figure SMS_48
Representing a sensor->
Figure SMS_49
Representing the number of sensing centers, +.>
Figure SMS_50
Representing the number of sensors, +.>
Figure SMS_51
and
Figure SMS_52
Respectively representing the preset variance and the expected +.>
Figure SMS_53
Representing rounding symbols, ++>
Figure SMS_45
and
Figure SMS_47
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
And according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain the three-dimensional coordinates of the sensing center.
It should be explained that, in the calculation formula of the number of the sensing centers, the variance and the expectation can be set in a manually preset manner, and the variance and the expectation value can be determined according to the fitting result of the historical data. For example, the small sheet needs to detect the environmental data of the industrial park a, but in the history detection record, the detection data of the industrial park B, the industrial park C and other areas are acquired, the variance and the expected value are determined to be a certain value through experimental fitting, and the calculated number of the sensing centers is optimal, so that the variance and the expected value can be determined based on the history fitting result.
In addition, the embodiment of the invention continuously adjusts the original coordinates of the sensing center through a clustering algorithm such as K-means and the like. For example, the industrial park A has 500 sensors in total, the number of the sensing centers is calculated to be 10 through a number calculation formula of the sensing centers, then the original coordinates of the sensing centers of the 10 sensing centers are randomly generated, and the original coordinates of the sensing centers of the 10 sensing centers are continuously adjusted through a clustering algorithm such as K-means and the like to obtain the three-dimensional coordinates of the sensing centers.
S3, performing area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets.
In detail, the performing area division on all the sensors according to the plurality of sensing centers to obtain a plurality of groups of area sensor sets includes:
the following is performed for each sensor:
acquiring a sensor three-dimensional coordinate corresponding to a sensor and a sensing center three-dimensional coordinate corresponding to each sensing center;
calculating a distance value between the three-dimensional coordinates of the sensor and the three-dimensional coordinates of each sensing center; obtaining a distance value set, wherein the number of the distance values in the distance value set is the same as that of the sensing centers;
selecting a minimum distance value from the distance value set, and determining a sensing center corresponding to the minimum distance value, namely, a sensing center with a corresponding relation with the sensor;
and executing area division according to the minimum distance value corresponding to the sensing center until all the sensors determine the corresponding sensing center, so as to obtain a plurality of groups of area sensor sets.
For example, the industrial park a has 500 sensors in total, the number of corresponding sensing centers is 10, and how to divide the regional sensor set by using the 10 sensing centers is a main technical problem to be solved in the step. Therefore, each sensor of 500 sensors is calculated with 10 sensing centers, and for example, the distance values of the sensor I and the 10 sensing centers are calculated when the 500 sensors include the sensor I, the minimum distance value is obtained from the 10 distance values, and the sensing center corresponding to the minimum distance value is assumed to be P, so that the sensor I belongs to the sensing center P.
Further, the performing area division according to the minimum distance value corresponding to the sensing center to obtain a plurality of groups of area sensor sets includes:
acquiring the minimum distance value between all the sensors corresponding to each sensing center and the sensors;
screening out the maximum distance value from all the minimum distance values to obtain the radius of the region;
and constructing an area circle by taking the sensing center as an area center according to the area center and the area radius, wherein all sensors in the area circle are the area sensor set.
By way of example, by the above calculation method, it is sequentially calculated that the sensor I belongs to the sensor center P, and 30 sensors among 500 sensors also belong to the sensor center P, so that the sensor center P corresponds to 31 sensors, and similarly, 31 minimum distance values correspond to each other. Therefore, further, the largest distance value is selected from 31 minimum distance values, and if 60 is assumed, the other 30 minimum distance values are smaller than or equal to 60, namely 60 is also the area radius, so that according to the area radius+the area center, an area circle can be determined, and the area circle can circle 31 sensors, and the 31 sensors are the area sensor set belonging to the sensing center P.
And S4, distributing data transmission frequency for each sensing center to obtain a center transmission frequency, distributing frequency for each area sensor in the area sensor set according to the center transmission frequency, and obtaining a sensing transmission frequency.
It should be emphasized that the primary function of the sensing center is to determine the channel of data transmission, and the channels between the sensing center and the sensing center are generally different and not repeated, so that the difference between the channels can effectively prevent the problems of delay or blocking of the sensing data transmission caused by overload of the channels.
In detail, the allocating the data transmission frequency to each sensing center to obtain the center transmission frequency includes:
determining all available channels of the wireless sensor network at the current time to obtain an available channel set;
receiving the lowest transmission frequency and frequency range input by a user;
and distributing data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency range to obtain center transmission frequency.
In the wireless sensor network of the industrial park a, the number of available channels is assumed to be 30, and the currently calculated total 10 sensor centers are 10, which means that 10 available channels are selected from the 30 available channels to serve the 10 sensor centers.
Further, the allocating data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency range to obtain a center transmission frequency includes:
screening channels conforming to the frequency range from the available channel sets to obtain one or more frequency range channels;
non-repeated extraction of each frequency band channel from one or more frequency band channels, and
the center transmission frequency is calculated according to the following formula:
Figure SMS_54
wherein ,
Figure SMS_55
representing the sensing center +.>
Figure SMS_56
Center transmission frequency of>
Figure SMS_57
Representing the lowest transmission frequency of the user input, +.>
Figure SMS_58
Indicate->
Figure SMS_59
Individual frequency band channels>
Figure SMS_60
Indicate->
Figure SMS_61
A unit frequency step factor of each frequency band channel.
It should be explained that, in the embodiment of the present invention, the frequency band range is set to be [0.2 GHz,2.4 GHz ], and the unit frequency step factor corresponds to the frequency band channel, if the unit frequency step factor of the frequency band channel is 0.21 GHz.
Further, the allocating a frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain a sensing transmission frequency includes:
the following calculation is performed for each area sensor to obtain the sensing transmission frequency:
calculating a distance value between each area sensor and a corresponding sensing center, and
Acquiring the data generation amount of each area sensor in unit time;
and calculating to obtain the corresponding sensing transmission frequency according to the distance value and the data generation quantity.
For example, the industrial park A has a sensor I and a sensing center P with a one-to-one correspondence, and the distance between the sensor I and the sensing center P is calculated as
Figure SMS_62
Then according to the historical data transmission record of the sensor I, the data generation amount of the sensor I in 1 minute per unit is calculated to be 10M, and according to 10M and the distance
Figure SMS_63
The sensing transmission frequency of the sensor I can be calculated.
In detail, the calculating to obtain the corresponding sensing transmission frequency according to the distance value and the data generation amount includes:
Figure SMS_64
wherein ,
Figure SMS_65
representation area sensor->
Figure SMS_66
The assigned sensor transmission frequency, +.>
Figure SMS_67
The distribution factor representing the sensing transmission frequency is calculated by the following steps:
Figure SMS_68
wherein ,
Figure SMS_70
representation area sensor->
Figure SMS_72
Is>
Figure SMS_74
Distance value of>
Figure SMS_75
Representation area sensor->
Figure SMS_76
Data generation amount per unit time, +.>
Figure SMS_77
Representation area sensor->
Figure SMS_78
Is>
Figure SMS_69
Weight factor of distance value of ∈x->
Figure SMS_71
Representation area sensor->
Figure SMS_73
A weight factor for the amount of data generated by the system.
Summarizing, according to the above calculation method and calculation steps, the center transmission frequency of the sensing center may sequentially perform frequency allocation for each area sensor in the area sensor set, so that each area sensor has a corresponding sensing transmission frequency, and further, the sensing data generated by each area sensor may be transmitted according to the sensing transmission frequency.
And S5, receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
By way of example, the PH measuring sensor monitors the water quality of the industrial park at any time and generates a water quality PH measurement value, the air component monitoring sensor monitors the air component of the industrial park and generates an air component value, and since the water quality PH measurement value floats relatively little with respect to the change of the air component value and the number of the air component values is more, the sensing transmission frequency of the air component monitoring sensor can be calculated to be higher, so that the transmission efficiency of sensing data of the air component values is improved more quickly.
In order to solve the problems described in the background art, the embodiment of the invention firstly receives a collection instruction of sensing data, determines all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network, and the wireless sensor network is a distributed sensing network, the network terminal of the wireless sensor network is the sensor, the wireless sensor network can effectively improve the feedback effect of the sensing data of the sensors, compared with the traditional communication technology, the time can be saved, excessive waste of manpower resources can be prevented, further, a plurality of sensing centers of the wireless sensor network are determined according to the number of the sensors, the area division is performed on all the sensors according to the plurality of sensing centers, a plurality of area sensor sets are obtained, each sensing center corresponds to each area sensor set, and the main effect of the sensing center is to reasonably allocate the transmission efficiency of the sensing data of each sensor, so that the phenomenon that the channel is not timely in feedback of the sensing data is prevented, the data transmission frequency is allocated to each sensing center, the center frequency is obtained, the sensing frequency is allocated to each sensing center, the sensing frequency is automatically allocated to each sensing area, and the data is automatically generated according to the number of sensing area, and the data is automatically acquired according to the frequency allocation of the sensing frequency, and the data is sequentially generated. Therefore, the automatic sensing method, the device, the electronic equipment and the computer readable storage medium for realizing the sensor based on the Internet of things mainly aim to solve the phenomenon of congestion or untimely return of sensing data on the premise of not improving communication signals of the environment where the sensor is located.
Fig. 2 is a functional block diagram of an automatic sensing device for implementing a sensor based on the internet of things according to an embodiment of the present invention.
The automatic sensing device 100 for realizing the sensor based on the internet of things can be installed in electronic equipment. According to the implemented functions, the automatic sensing device 100 for implementing a sensor based on the internet of things may include a collection instruction receiving module 101, a sensing center determining module 102, a region dividing module 103, a sensing transmission frequency allocation module 104, and a sensing data receiving module 105. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
The collection instruction receiving module 101 is configured to receive a collection instruction of sensing data, determine all sensors currently responding to the collection instruction, where all sensors perform transmission of the sensing data through a wireless sensor network;
the sensing center determining module 102 is configured to determine a plurality of sensing centers in the wireless sensor network according to the number of sensors, where the determining method of the sensing centers includes:
The number of sensing centers is calculated according to the following formula:
Figure SMS_79
wherein ,
Figure SMS_81
representing the sensing center, +.>
Figure SMS_83
Representing a sensor->
Figure SMS_84
Representing the number of sensing centers, +.>
Figure SMS_85
Representing the number of sensors, +.>
Figure SMS_86
and
Figure SMS_87
Respectively representing the preset variance and the expected +.>
Figure SMS_88
Representing rounding symbols, ++>
Figure SMS_80
and
Figure SMS_82
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
the area dividing module 103 is configured to perform area division on all the sensors according to a plurality of sensing centers, so as to obtain a plurality of groups of area sensor sets, where each sensing center corresponds to each group of area sensor sets;
The sensing transmission frequency allocation module 104 is configured to allocate a data transmission frequency to each sensing center to obtain a center transmission frequency, allocate a frequency to each area sensor in the area sensor set according to the center transmission frequency, and obtain a sensing transmission frequency;
the sensing data receiving module 105 is configured to receive the sensing data generated by each area sensor, and send the generated sensing data to an initiator of the collection instruction in sequence on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
In detail, the modules in the automatic sensing device 100 for implementing a sensor based on the internet of things in the embodiment of the present invention use the same technical means as the above-mentioned blockchain-based product supply chain management method in fig. 1, and can produce the same technical effects, which are not described herein.
Fig. 3 is a schematic structural diagram of an electronic device for implementing an auto-sensing method for implementing a sensor based on the internet of things according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11 and a bus 12, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as an auto-sensing method program for implementing a sensor based on the internet of things.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used to store not only application software installed in the electronic device 1 and various data, such as code for implementing an auto-sensing method program of a sensor based on the internet of things, but also temporarily store data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects respective components of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, an auto-sensing method program for implementing a sensor based on the internet of things, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process the data.
The bus 12 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus 12 may be divided into an address bus, a data bus, a control bus, etc. The bus 12 is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
Further, the electronic device 1 may also comprise a network interface, optionally the network interface may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used for establishing a communication connection between the electronic device 1 and other electronic devices.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
The automatic sensing method program stored in the memory 11 of the electronic device 1 and based on the sensor implemented by the internet of things is a combination of a plurality of instructions, and when running in the processor 10, the method can be implemented:
Receiving a collection instruction of sensing data, and determining all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network;
according to the number of the sensors, a plurality of sensing centers in the wireless sensor network are determined, wherein the method for determining the sensing centers comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure SMS_89
wherein ,
Figure SMS_91
representing the sensing center, +.>
Figure SMS_93
Representing a sensor->
Figure SMS_94
Representing the number of sensing centers, +.>
Figure SMS_95
Representing the number of sensors, +.>
Figure SMS_96
and
Figure SMS_97
Respectively representing the preset variance and the expected +.>
Figure SMS_98
Representing rounding symbols, ++>
Figure SMS_90
and
Figure SMS_92
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
According to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
performing area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
distributing data transmission frequency to each sensing center to obtain center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain sensing transmission frequency;
and receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
Specifically, the specific implementation method of the above instructions by the processor 10 may refer to descriptions of related steps in the corresponding embodiments of fig. 1 to 3, which are not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
receiving a collection instruction of sensing data, and determining all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network;
according to the number of the sensors, a plurality of sensing centers in the wireless sensor network are determined, wherein the method for determining the sensing centers comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure SMS_99
wherein ,
Figure SMS_101
representing the sensing center, +.>
Figure SMS_102
Representing a sensor->
Figure SMS_104
Representing the number of sensing centers, +.>
Figure SMS_105
Representing the number of sensors, +.>
Figure SMS_106
and
Figure SMS_107
Respectively representing the preset variance and the expected +.>
Figure SMS_108
Representing rounding symbols, ++>
Figure SMS_100
and
Figure SMS_103
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
Randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
performing area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
distributing data transmission frequency to each sensing center to obtain center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain sensing transmission frequency;
and receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims (10)

1. An automatic sensing method for realizing a sensor based on the internet of things is characterized by comprising the following steps:
receiving a collection instruction of sensing data, and determining all sensors currently responding to the collection instruction, wherein all sensors execute transmission of the sensing data through a wireless sensor network;
according to the number of the sensors, a plurality of sensing centers in the wireless sensor network are determined, wherein the method for determining the sensing centers comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure QLYQS_1
wherein ,
Figure QLYQS_3
representing the sensing center, +.>
Figure QLYQS_4
Representing a sensor->
Figure QLYQS_6
Representing the number of sensing centers, +.>
Figure QLYQS_7
Indicating the number of sensors to be used,
Figure QLYQS_8
and
Figure QLYQS_9
Respectively representing the preset variance and the expected +.>
Figure QLYQS_10
Representing rounding symbols, ++>
Figure QLYQS_2
and
Figure QLYQS_5
Representing the number of calculated sensing centersA first weight factor and a second weight factor of the quantity;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
According to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
performing area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
distributing data transmission frequency to each sensing center to obtain center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain sensing transmission frequency;
and receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so as to realize automatic sensing acquisition of the sensing data.
2. The method for implementing automatic sensing of sensors based on internet of things according to claim 1, wherein said determining all sensors currently responding to said collection instruction comprises:
acquiring IP addresses of all sensors prestored in a database;
triggering a sensor test program to generate a sensor test instruction, and sequentially sending the sensor test instruction to each sensor according to the IP address, wherein the sensor test instruction is sent to each sensor through a wireless sensor network;
And eliminating the sensors which do not return response instructions according to the sensor test instructions and the sensors with the return time of the response instructions being longer than the time threshold value, so as to obtain all the sensors.
3. The automatic sensing method for realizing a sensor based on the internet of things according to claim 2, wherein the sensor comprises a pressure sensor, a position sensor, a liquid level sensor, an energy consumption sensor, a speed sensor, an acceleration sensor, a radiation sensor and a heat-sensitive sensor.
4. The method for implementing automatic sensing of sensors based on internet of things according to claim 1, wherein the performing area division on all the sensors according to the plurality of sensing centers to obtain a plurality of groups of area sensor sets comprises:
the following is performed for each sensor:
acquiring a sensor three-dimensional coordinate corresponding to a sensor and a sensing center three-dimensional coordinate corresponding to each sensing center;
calculating a distance value between the three-dimensional coordinates of the sensor and the three-dimensional coordinates of each sensing center; obtaining a distance value set, wherein the number of the distance values in the distance value set is the same as that of the sensing centers;
selecting a minimum distance value from the distance value set, and determining a sensing center corresponding to the minimum distance value, namely, a sensing center with a corresponding relation with the sensor;
And executing area division according to the minimum distance value corresponding to the sensing center until all the sensors determine the corresponding sensing center, so as to obtain a plurality of groups of area sensor sets.
5. The method for implementing automatic sensing of sensors based on internet of things according to claim 4, wherein the performing region division according to the minimum distance value corresponding to the sensing center to obtain a plurality of groups of region sensor sets comprises:
acquiring the minimum distance value between all the sensors corresponding to each sensing center and the sensors;
screening out the maximum distance value from all the minimum distance values to obtain the radius of the region;
and constructing an area circle by taking the sensing center as an area center according to the area center and the area radius, wherein all sensors in the area circle are the area sensor set.
6. The method for implementing automatic sensing of a sensor based on internet of things according to claim 5, wherein the allocating a data transmission frequency to each sensing center to obtain a center transmission frequency includes:
determining all available channels of the wireless sensor network at the current time to obtain an available channel set;
receiving the lowest transmission frequency and frequency range input by a user;
And distributing data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency range to obtain center transmission frequency.
7. The method for implementing automatic sensing of a sensor based on internet of things according to claim 6, wherein the allocating a data transmission frequency to each sensing center according to the available channel set, the lowest transmission frequency and the frequency band range to obtain a center transmission frequency includes:
screening channels conforming to the frequency range from the available channel sets to obtain one or more frequency range channels;
non-repeated extraction of each frequency band channel from one or more frequency band channels, and
the center transmission frequency is calculated according to the following formula:
Figure QLYQS_11
wherein ,
Figure QLYQS_12
representing the sensing center +.>
Figure QLYQS_13
Center transmission frequency of>
Figure QLYQS_14
Representing the lowest transmission frequency of the user input, +.>
Figure QLYQS_15
Represent the first
Figure QLYQS_16
Individual frequency band channels>
Figure QLYQS_17
Indicate->
Figure QLYQS_18
A unit frequency step factor of each frequency band channel.
8. The method for implementing automatic sensing of sensors based on internet of things according to claim 7, wherein the allocating a frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain a sensing transmission frequency comprises:
The following calculation is performed for each area sensor to obtain the sensing transmission frequency:
calculating a distance value between each area sensor and a corresponding sensing center, and
acquiring the data generation amount of each area sensor in unit time;
and calculating to obtain the corresponding sensing transmission frequency according to the distance value and the data generation quantity.
9. The method for implementing automatic sensing of a sensor based on internet of things according to claim 8, wherein the calculating the corresponding sensing transmission frequency according to the distance value and the data generation amount comprises:
Figure QLYQS_19
wherein ,
Figure QLYQS_20
representation area sensor->
Figure QLYQS_21
The assigned sensor transmission frequency, +.>
Figure QLYQS_22
The distribution factor representing the sensing transmission frequency is calculated by the following steps: />
Figure QLYQS_23
wherein ,
Figure QLYQS_25
representation area sensor->
Figure QLYQS_27
Is>
Figure QLYQS_28
Distance value of>
Figure QLYQS_30
Representation area sensor->
Figure QLYQS_31
Data generation amount per unit time, +.>
Figure QLYQS_32
Representation area sensor->
Figure QLYQS_33
Is>
Figure QLYQS_24
Weight factor of distance value of ∈x->
Figure QLYQS_26
Representation area sensor->
Figure QLYQS_29
A weight factor for the amount of data generated by the system.
10. Automatic induction device for realizing a sensor based on the internet of things, which is characterized in that the device comprises:
the system comprises a collection instruction receiving module, a wireless sensor network and a data processing module, wherein the collection instruction receiving module is used for receiving a collection instruction of sensing data and determining all sensors responding to the collection instruction at present, and all sensors execute transmission of the sensing data through the wireless sensor network;
The sensing center determining module is used for determining a plurality of sensing centers in the wireless sensor network according to the number of the sensors, wherein the sensing center determining method comprises the following steps:
the number of sensing centers is calculated according to the following formula:
Figure QLYQS_34
wherein ,
Figure QLYQS_36
representing the sensing center, +.>
Figure QLYQS_37
Representing a sensor->
Figure QLYQS_39
Representing the number of sensing centers, +.>
Figure QLYQS_40
Indicating the number of sensors to be used,
Figure QLYQS_41
and
Figure QLYQS_42
Respectively representing the preset variance and the expected +.>
Figure QLYQS_43
Representing rounding symbols, ++>
Figure QLYQS_35
and
Figure QLYQS_38
A first weight factor and a second weight factor representing the number of calculated sensing centers;
acquiring a sensing position of each sensor to obtain a sensor position set;
constructing a three-dimensional coordinate system, and projecting the sensor position set to the three-dimensional coordinate system to obtain a sensor three-dimensional coordinate set, wherein the sensor three-dimensional coordinate has a one-to-one correspondence with the sensor;
randomly generating three-dimensional coordinates of the sensing centers in a three-dimensional coordinate system to obtain original coordinates of the sensing centers, wherein the number of the original coordinates of the sensing centers is the same as that of the sensing centers;
according to a clustering algorithm, adjusting the original coordinates of each sensing center to obtain three-dimensional coordinates of the sensing centers, wherein the sensing centers comprise the number of the sensing centers and the three-dimensional coordinates of the sensing centers;
The area dividing module is used for carrying out area division on all the sensors according to a plurality of sensing centers to obtain a plurality of groups of area sensor sets, wherein each sensing center corresponds to each group of area sensor sets;
the sensing transmission frequency distribution module is used for distributing data transmission frequency to each sensing center to obtain a center transmission frequency, distributing frequency to each area sensor in the area sensor set according to the center transmission frequency to obtain a sensing transmission frequency;
the sensing data receiving module is used for receiving the sensing data generated by each area sensor, and sequentially sending the generated sensing data to an initiator of the collection instruction on the premise of sensing transmission frequency, so that automatic sensing acquisition of the sensing data is realized.
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