Disclosure of Invention
In order to solve the problems, the invention provides an internet of things platform monitoring system based on cloud computing and a method thereof.
The purpose of the invention is realized by adopting the following technical scheme:
the invention provides an Internet of things platform monitoring system based on cloud computing, which comprises an environment monitoring sensing layer, a cloud computing layer and an application layer, wherein the environment monitoring sensing layer is connected with the cloud computing layer, and the cloud computing layer is in signal connection with the application layer; the application layer comprises a mobile terminal and a control terminal used for controlling the household equipment to work, and the mobile terminal is in wireless connection with the control terminal through an APP terminal; the environment monitoring sensing layer collects environment data of a monitored area and sends the environment data to the cloud computing layer; and the cloud computing layer is provided with a processor to store, manage and analyze the environment data and transmit the environment data to the mobile terminal.
Wherein, household equipment includes air purifier and new trend switch.
According to the first aspect of the invention, the mobile terminal sends an instruction to the control terminal through the APP terminal so as to control the household equipment corresponding to the instruction to work.
According to a first aspect of the invention, a cloud computing-based platform monitoring system for the internet of things is provided, wherein environment data comprises environment perception data and corresponding geographic position data, and the environment data is visually displayed by a mobile terminal through an APP terminal.
The environmental perception data may include indoor formaldehyde concentration, PM2.5 concentration, smoke concentration, temperature and humidity, and the like.
According to a first aspect of the present invention, there is provided a cloud computing-based internet of things platform monitoring system, where the visual display includes:
defining a data grid and determining the display scale of an X axis;
configuring, scanning and reading a data source according to the environment perception data and the geographic position data;
analyzing the stored data and correcting the X-axis display scale, and further calculating the quartile of the data in each data grid of each scale level;
and performing data display by adopting the quartering bitmap, wherein the displayed data comprises environment perception data and corresponding geographic position data.
According to the embodiment, the visual display of the complex home environment is realized through the visual method.
The invention provides a cloud computing-based Internet of things platform monitoring method, which comprises the following steps:
the cloud computing layer receives environmental data collected by the environmental monitoring sensing layer;
the cloud computing layer stores, manages and analyzes the environment data to obtain the environment data corresponding to each time node and geographic position;
and the cloud computing layer sends the environment data corresponding to each time node and the geographic position to the mobile terminal.
According to a second aspect of the present invention, there is provided a cloud computing-based internet of things platform monitoring method, where the environmental data includes environmental awareness data and corresponding geographic location data, the method further including:
and the cloud computing layer performs threshold analysis on the environment perception data, and sends alarm information to the mobile terminal when the environment perception data exceeds a standard environment perception data threshold range.
According to the embodiment of the invention, the sensing, the Internet of things and the cloud computing technology are combined, the household environment is collected and transmitted in real time, a system for all-weather real-time remote monitoring of the household environment is developed, the corresponding household equipment is controlled to be turned on and turned off, the household air quality is improved, and the alarm is realized; the method has the advantages that the strong processing capacity of cloud computing is utilized, massive household environment data are stored, managed and analyzed, and monitoring departments, enterprises or individuals and other users can easily acquire needed resources in a cloud mode.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1, an embodiment of the first aspect of the present invention provides a cloud computing-based platform monitoring system for internet of things, where the system includes an environment monitoring sensing layer 1, a cloud computing layer 2, and an application layer 3, where the environment monitoring sensing layer 1 is connected to the cloud computing layer 2, and the cloud computing layer 2 is in signal connection with the application layer 3; the application layer 3 comprises a mobile terminal and a control terminal for controlling the household equipment to work, and the mobile terminal is in wireless connection with the control terminal through an APP terminal; the environment monitoring perception layer 1 collects environment data of a monitored area and sends the environment data to the cloud computing layer 2; the cloud computing layer 2 is provided with a processor to store, manage and analyze the environment data and transmit the environment data to the mobile terminal.
Wherein, household equipment includes air purifier and new trend switch.
According to the first aspect of the invention, the mobile terminal sends an instruction to the control terminal through the APP terminal so as to control the household equipment corresponding to the instruction to work.
According to a first aspect of the invention, a cloud computing-based platform monitoring system for the internet of things is provided, wherein environment data comprises environment perception data and corresponding geographic position data, and the environment data is visually displayed by a mobile terminal through an APP terminal.
The environmental perception data may include indoor formaldehyde concentration, PM2.5 concentration, smoke concentration, temperature and humidity, and the like.
According to a first aspect of the present invention, there is provided a cloud computing-based internet of things platform monitoring system, where the visual display includes:
defining a data grid and determining the display scale of an X axis;
configuring, scanning and reading a data source according to the environment perception data and the geographic position data;
analyzing the stored data and correcting the X-axis display scale, and further calculating the quartile of the data in each data grid of each scale level;
and performing data display by adopting the quartering bitmap, wherein the displayed data comprises environment perception data and corresponding geographic position data.
According to the embodiment, the visual display of the complex home environment is realized through the visual method.
As shown in fig. 2, a second aspect of the present invention provides a cloud computing-based internet of things platform monitoring method, including:
s01, the cloud computing layer receives environmental data collected by the environmental monitoring perception layer;
s02, the cloud computing layer stores, manages and analyzes the environment data to obtain the environment data corresponding to each time node and geographic position;
and S03, the cloud computing layer sends the environment data corresponding to each time node and geographic position to the mobile terminal.
According to a second aspect of the present invention, there is provided a cloud computing-based internet of things platform monitoring method, where the environmental data includes environmental awareness data and corresponding geographic location data, the method further including:
and the cloud computing layer performs threshold analysis on the environment perception data, and sends alarm information to the mobile terminal when the environment perception data exceeds a standard environment perception data threshold range.
According to the embodiment of the invention, the sensing, the Internet of things and the cloud computing technology are combined, the household environment is collected and transmitted in real time, a system for all-weather real-time remote monitoring of the household environment is developed, the corresponding household equipment is controlled to be turned on and turned off, the household air quality is improved, and the alarm is realized; the method has the advantages that the strong processing capacity of cloud computing is utilized, massive household environment data are stored, managed and analyzed, and monitoring departments, enterprises or individuals and other users can easily acquire needed resources in a cloud mode.
In the above internet of things platform monitoring system and method based on cloud computing, the environment monitoring sensing layer 1 includes a wireless sensor network, the wireless sensor network includes a plurality of sensor nodes, a plurality of cluster heads and sink nodes communicating with the cloud computing layer 2, and each sensor node selects a cluster head closest to the sensor node to join a cluster; the sink node periodically broadcasts a hello message to each cluster head, wherein the hello message comprises the position information of the sink node and a direct communication threshold hmin,hmin<ymax,ymaxA maximum communication distance that can be adjusted for the cluster head; after the cluster head receives the hello message, if the distance from the cluster head to the sink node is not more than hminIf so, the cluster head selects to directly communicate with the sink node; if the distance from the cluster head to the sink node is greater than hminIf so, selecting one cluster head in the communication range of the cluster head as a next hop node, and directly communicating with the next hop node; the direct communication threshold is determined according to the following formula:
in the formula, y
minFor the minimum communication distance that the cluster head can adjust,
as a distance from the sink node
The average initial energy of cluster heads within the range,
as a distance from the sink node
Average current residual energy of cluster heads in the range, g is a preset distance increasing factor based on energy consumption, and the value of g satisfies the requirement
And when the frequency of broadcasting the hello message to each cluster head by the aggregation node reaches a set frequency threshold value, stopping the broadcasting operation of the hello message.
In this embodiment, each cluster head determines to communicate with the sink node in a direct or indirect manner according to the distance from the cluster head to the sink node, so that the flexibility of cluster head routing is improved. Determining a direct communication distance threshold h according to the actual deployment condition of the cluster headminSo that h isminThe setting of the wireless sensor network is closer to the actual situation, the routing mode of the cluster head can be determined more reasonably, the transmission energy consumption of the wireless sensor network is reduced on the premise of ensuring effective transmission of environmental data as much as possible, and the monitoring cost of the cloud computing-based Internet of things platform monitoring system is saved.
In one implementation, the cluster head periodically calculates its load level and broadcasts it to other cluster heads in the communication range, where the calculation formula of the load level is:
in the formula of UITo the degree of loading of the cluster head I, QIIs the current remaining energy of cluster head I, NI(hmin) Is not more than h away from the cluster head IminThe number of cluster heads; kIFor the number of sensor nodes in cluster head I cluster, QθThe method comprises the steps of setting unit energy consumption based on cluster management;
when the cluster head selects a next hop node in the cluster heads in the communication range, the following steps are specifically executed:
(1) at a distance from it not exceeding hminDetermining cluster heads which are closer to the sink node relative to the cluster heads, and classifying the cluster heads into an alternative node set;
(2) and selecting the cluster head with the minimum load degree in the candidate node set as the next hop node.
The embodiment innovatively provides a load degree index of the cluster head, which is used for measuring the current load condition of the cluster head, and the embodiment further provides a working mechanism for selecting a next hop node by the cluster head based on the load degree, in the mechanism, the cluster head with the minimum load degree in the alternative node set is selected by the cluster head as the next hop node, so that the load of each cluster head is balanced as much as possible on the premise of ensuring that the electric energy and the environmental parameter information are transmitted to the sink node in a unidirectional manner, the energy of the cluster head is balanced, and the performance of the wireless sensor network is improved.
In an implementation mode, a next hop node periodically calculates a capability reduction coefficient of the next hop node, and when the capability reduction coefficient reaches the upper limit of a preset capability reduction coefficient threshold, the next hop node sends feedback information to a cluster head of the previous hop so as to reselect the next hop node from the cluster head of the previous hop; the calculation formula of the capacity reduction coefficient is as follows:
in the formula, BJFor the capability reduction factor of the next hop node J, QJIs the current residual energy of the next hop node J, MJThe number of cluster heads, Q, for the next-hop node JτH (J, O) is the distance from the next hop node J to the sink node, KJThe number of sensor nodes in the next-hop node J cluster.
The embodiment innovatively provides a concept of the capacity reduction coefficient, and a calculation formula of the capacity reduction coefficient is designed by taking the energy of a next hop node, the number of sensor nodes in a cluster, the distance between the sensor nodes and a sink node and the number of cluster heads taking the sensor nodes as the next hop node as consideration factors. In this embodiment, when the capacity reduction coefficient reaches the upper limit of the preset capacity reduction coefficient threshold, the next-hop node sends feedback information to the cluster head of the previous hop, so that the cluster head of the previous hop reselects the next-hop node, which is beneficial to reducing the failure probability of the next-hop node, balancing the energy consumption of each cluster head, and ensuring the reliability of environmental data forwarding.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the system and the terminal described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an application specific integrated circuit, a digital signal processor, a digital signal processing system, a programmable logic device, a field programmable gate array, a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. The computer-readable medium can include, but is not limited to, random access memory, read only memory images, electrically erasable programmable read only memory or other optical disk storage, magnetic disk storage media or other magnetic storage systems, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.