CN115690600A - Forest fire monitoring method and forest fire monitoring system based on remote communication integration - Google Patents
Forest fire monitoring method and forest fire monitoring system based on remote communication integration Download PDFInfo
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- CN115690600A CN115690600A CN202211342946.7A CN202211342946A CN115690600A CN 115690600 A CN115690600 A CN 115690600A CN 202211342946 A CN202211342946 A CN 202211342946A CN 115690600 A CN115690600 A CN 115690600A
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Abstract
The application provides a forest fire monitoring method based on remote communication integration, which comprises the following steps: acquiring hot spot data downloaded on the satellite in real time and data generated by the integration of communication, conduction and remote, and storing the data into a relational database according to data types; cleaning and analyzing the data in the relational database, and outputting a standard data format; the method comprises the following steps of utilizing a fire identification data model to realize fire identification, wherein the fire identification data model comprises a satellite orbit visualization model, a fire danger level early warning model and a fire discrimination model; the user uses the mobile terminal to request various services from the server software through the Web front-end software, and the server software returns the services to the Web client and visually displays the services. The hot spot data downloaded in real time on the satellite and the data generated by the integration of conduction and remote control comprise: hotspot Beidou short message information, remote sensing images and satellite orbit data issued by the on-satellite sensors in real time comprise: latitude and longitude, area, shape, and discovery time of the hot spot.
Description
Technical Field
The application relates to the technical field of information system software architecture, in particular to a Web front-end development scheme of a forest fire monitoring system based on remote communication and remote control integration.
Background
Forest fires often cause civil economy to suffer serious harm, generally, forest fire early warning adopted in the market generally adopts a three-dimensional forest fire monitoring system combining multiple monitoring modes, such as artificial ground patrol, aviation patrol, lookout tower construction and the like, and simultaneously integrates technologies of satellite remote sensing, geographic Information System (GIS), unmanned aerial vehicle, global Positioning System (GPS) and the like, but the problems of poor information interaction real-time performance, low data visualization degree and the like exist in forest fire monitoring.
Satellite remote sensing image monitoring is a high and new technology developed in recent years and is widely applied, however, because hot spot image processing and fire spot positioning are usually carried out after a hot spot image is downloaded to the ground, the images are generally downloaded after a satellite passes through a fire disaster, and the images can be judged and notified to related personnel after forest fire identification through the ground image, and the optimal fire disaster extinguishing time is usually missed.
Disclosure of Invention
In order to solve the problems, the application provides a forest fire monitoring method based on remote communication integration, an on-orbit remote sensing satellite monitors surface forest fire in real time, and hot spot information is issued to a ground monitoring system through a Beidou short message, so that the ground forest fire can be monitored in real time. The invention can utilize the technology of 'communication and remote control integration' to open an information bridge among the satellite, navigation and geospatial elements, realize the interconnection, unified reference and space-time fusion of the heaven and earth, discover the fire in time and reduce the life and property damage of people.
The application provides a forest fire monitoring method based on remote communication integration, which comprises the following steps:
s101: acquiring hot spot data downloaded on the satellite in real time and data generated by the integration of communication, conduction and remote, and storing the data into a relational database according to data types;
s102: cleaning and analyzing the data in the relational database, and outputting a standard data format;
s103: the fire identification is realized by utilizing a fire identification data model, and the fire identification data model comprises a satellite orbit visualization model, a fire risk level early warning model and a fire discrimination model;
s104: the user uses the mobile terminal to request various services from the server software through the Web front-end software, the server software returns the services to the Web client and displays the services visually,
the satellite real-time downloaded hot spot data and data generated by the integration of communication and remote communication comprise: hotspot Beidou short message information, remote sensing images and satellite orbit data which are issued by the on-board sensor in real time,
the hot Beidou short message information comprises: latitude and longitude, area, shape, and discovery time of the hot spot.
According to an embodiment of the present application, in step S101, the collected data is stored in the relational database through the data interface framework in the form of key-value pairs.
According to an embodiment of the present application, the data generated by integrating the satellite real-time downloaded hot spot data and the remote communication further includes: ground sensor data, user feedback data, unmanned aerial vehicle monitoring data.
According to an embodiment of the present application, wherein the cleaning and analyzing the data in the relational database comprises: removing redundant forest fire data, deleting repeated values, abnormal values, filling missing values and sorting data; the required data is converted into a standard data format.
According to one embodiment of the present application, wherein,
the satellite orbit visualization model takes satellite ephemeris and sensor parameters as input and outputs the satellite infrasatellite point coordinates and the transit time of an interested area;
the fire danger level early warning model takes soil, meteorological data, local terrain and human factors as input and outputs the probability of fire occurrence for a period of time.
According to one embodiment of the application, the fire situation screening model takes satellite hot spot data as input, screens the satellite hot spot data through the land use type data and the pseudo hot spot database, and outputs the screened hot spot data.
According to an embodiment of the present application, step S103 further includes: and forming two-dimensional or three-dimensional visual forest fire prediction and forecast and fire comprehensive query by depending on the relational database and the fire identification data model and using a map engine.
According to one embodiment of the application, the Web front-end software architecture comprises a database, a service framework, a Web data interface and a reverse proxy server,
the database is a relational database MySQL, the service framework is a node. Js Express framework and a Python flash framework,
the Web data interface is a RESTful API,
the reverse proxy server is NginX, the user sends out a request for accessing the Web server through the domain name, and the personal mobile terminal obtains system service.
The application also provides a forest fire monitoring system based on remote integration of leading, include: a data acquisition module, a real-time data analysis module, a fire behavior identification module and a user terminal, wherein,
the data acquisition module is used for acquiring hot spot data downloaded on the satellite in real time and data generated by the integration of communication and remote communication and storing the data into the relational database according to data categories;
the real-time data analysis module is used for cleaning and analyzing the data in the relational database and inputting data in a standard format to a forest fire monitoring system;
the fire recognition module is used for carrying out algorithm processing on the data, recognizing the fire and then transmitting the fire to each user side through the Internet.
The invention provides a forest fire monitoring method based on remote communication integration, which can perform data processing and visualization on fire point information issued by a sensor on a satellite in real time, realize real-time monitoring and quick response of forest fire, and avoid large-scale fire to a certain extent.
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The above features, technical features, advantages and modes of realisation of the present application will be further described in the following detailed description of preferred embodiments in a clearly understandable manner, in conjunction with the accompanying drawings. The drawings are only for purposes of illustrating and explaining the present application and are not to be construed as limiting the scope of the present application. Wherein:
fig. 1 shows a flow chart of a forest fire monitoring method based on the integration of communication, conduction and remote control, which is disclosed by the embodiment of the invention.
Detailed Description
In order to more clearly understand the technical features, objects, and effects of the present application, embodiments of the present application will now be described with reference to the accompanying drawings.
According to an embodiment of the invention, a forest fire monitoring method based on remote communication integration is provided, a flow of which is shown in fig. 1, and comprises the following steps:
s101: and hot spot data downloaded in real time on the satellite and data generated by the integration of communication, navigation and remote control are collected and stored in a relational database MySQL according to data types.
The satellite real-time downloaded hot spot data and data generated by integrating communication, conduction and remote control comprise: data collected by various ways such as hot Beidou short message information, remote sensing images, satellite orbit data, ground sensors (including temperature and humidity sensors and forest fire cameras), user feedback, unmanned aerial vehicle monitoring and the like issued by onboard sensors in real time can be divided into images, texts, videos and the like according to data types, and are stored in a MySQL database through a data interface framework (IOServer) according to key value pair forms.
The hot Beidou short message information comprises: latitude and longitude, area, shape, and discovery time of the hot spot.
S102: and cleaning and analyzing the data in the MySQL database, and inputting the required standard data format to each algorithm module.
Wherein the cleaning and analyzing of the data comprises: and (3) removing redundant forest fire data, and processing the forest fire data as follows: and deleting repeated values, abnormal values, missing value filling and data sorting to reduce unnecessary storage space of the server, converting the required data into a standard data format, and inputting the standard data format into each data model in the fire identification data models required in the next step, thereby providing service for the system.
S103: and the fire condition identification is realized by utilizing the fire condition identification data model.
The fire behavior recognition data model comprises: a satellite orbit visualization model, a fire danger level early warning model, a fire discrimination model and the like.
The satellite orbit visualization model takes data such as satellite ephemeris and sensor parameters as input and outputs the data as the coordinates of the satellite sub-satellite points and the transit time of the region of interest;
the fire danger level early warning model takes soil, meteorological data, local terrain, human factors and the like as input, and outputs the probability of fire occurrence for a period of time;
the fire situation discrimination model takes satellite hot spot data as input, screens the satellite hot spot data through the land use type data and the pseudo hot spot database, and outputs the screened hot spot data.
And forming various business application functions such as two-dimensional visualization, three-dimensional visualization, forest fire prediction and forecast, fire comprehensive query and the like by depending on the MySQL database and the fire identification data model and using a map engine.
S104: a user requests various services from server software through Web front-end software through mobile terminals such as a mobile phone, a personal computer and large-screen monitoring, and the server software returns the services to a Web client and visually displays the services.
The Web front-end software comprises a database, a service framework, a network interface, a reverse proxy server and the like. The database is a relational database MySQL, data are stored in different tables, and retrieval is carried out according to data storage paths when the database is used;
a server side builds a Web service by using a node.js Express framework and a Python flash framework, performs algorithm processing on related data in a database, encapsulates a service interface into a RESTful API, and returns JSON to a cloud; HTML5, CSS and JavaScript use AjaX and RESTful API to construct a front-end UI interface;
the reverse proxy server is NginX, the user sends out a request for accessing the Web server through a domain name, the domain name is analyzed as an IP address of the reverse proxy server by the DNS, when the client requests service to the system through the network, the NginX reverse proxy server receives a network connection request, searches the requested content in a local cache, directly sends the content to the user after finding, if the local cache does not have the information content requested by the user, the reverse proxy server can replace the user to request the same information content to the server, the server performs corresponding algorithm processing, then returns the result operated by the server to the client requesting connection on the Internet, and synchronously caches the information content.
According to the Web front-end development scheme of the forest fire monitoring system based on the communication and remote integration, short message information issued on the satellite in real time is visualized, local fire conditions of a user can be informed in time, the forest fire early warning and monitoring service capability of the industry is improved through application demonstration and scientific research result conversion, new technologies are fully exerted, meanwhile, data processing and visualization are carried out on fire point information issued on the satellite in real time by a sensor, so that a sensor product on the satellite and a forest fire early warning ground information system are integrated, real-time monitoring and quick response of forest fire are achieved, and large-scale fire is avoided to a certain extent.
The invention provides a Web front-end development scheme of a forest fire monitoring system based on remote communication integration, which aims at the problems of poor forest fire related information interaction real-time performance, low data visualization degree and the like of the current forest fire monitoring, the method receives Beidou short messages issued by onboard sensors in real time, decodes the Beidou short messages according to a fixed coding format, and the short message information comprises the longitude and latitude, the area, the shape, the occurrence time and the like of fire points, uses a relational database MySQL to store the decoded fire point information, and reads and returns the fire point information to an HTML5 front-end interface by using Nodejs for visualization display. The whole set of forest fire monitoring system comprises a data acquisition module, a real-time data analysis module, a fire condition identification module and a user side. The system comprises a data acquisition module, a real-time data analysis module, a fire behavior identification module and a user side, wherein the data acquisition module is responsible for collecting data generated by a communication, guide and remote integrated technology and respectively writing the data into a MySQL database according to data types, the real-time data analysis module is responsible for cleaning the data and inputting data in a standard format to a forest fire monitoring system, and the fire behavior identification module is responsible for performing algorithm processing on the data, identifying fire behavior and then transmitting the fire behavior to each user side through the Internet. According to the method, the fire information issued by the sensors on the satellite in real time, the fire condition captured by the ground forest fire cameras and the data fed back by the user terminal are subjected to algorithm processing and visualization, so that real-time monitoring and quick response of forest fire are realized, and large-scale fire is avoided to a certain extent.
It should be understood that although the present description has been described in terms of various embodiments, not every embodiment includes only a single embodiment, and such description is for clarity purposes only, and those skilled in the art will recognize that the embodiments described herein may be combined as suitable to form other embodiments, as will be appreciated by those skilled in the art.
The above description is only illustrative of the present invention and is not intended to limit the scope of the present invention. Any equivalent alterations, modifications and combinations that may be made by those skilled in the art without departing from the spirit and principles of this application shall fall within the scope of this application.
Claims (10)
1. A forest fire monitoring method based on remote communication integration comprises the following steps:
s101: acquiring hot spot data downloaded on the satellite in real time and data generated by the integration of communication, conduction and remote, and storing the data into a relational database according to data types;
s102: cleaning and analyzing the data in the relational database, and outputting a standard data format;
s103: the method comprises the following steps of utilizing a fire identification data model to realize fire identification, wherein the fire identification data model comprises a satellite orbit visualization model, a fire danger level early warning model and a fire discrimination model;
s104: the user uses the mobile terminal to request various services from the server software through the Web front-end software, the server software returns the services to the Web client and displays the services visually,
the hot spot data downloaded in real time on the satellite and the data generated by the remote communication integration comprise: hotspot Beidou short message information, remote sensing images and satellite orbit data which are issued by the on-board sensor in real time,
the hot Beidou short message information comprises: latitude and longitude, area, shape, and discovery time of the hot spot.
2. The method according to claim 1, wherein in step S101, the collected data is stored in the relational database in the form of key-value pairs through a data interface framework.
3. The method of claim 1, wherein the on-board real-time downloaded hot spot data and data generated by the integrated operations of communication, navigation and telemetry further comprise: ground sensor data, user feedback data, unmanned aerial vehicle monitoring data.
4. The method of claim 1, wherein cleansing and analyzing the data in the relational database comprises: and removing redundant forest fire data, deleting repeated values, abnormal values, filling missing values and sorting the data.
5. The method of claim 1, wherein cleansing and analyzing the data in the relational database further comprises: the required data is converted into a standard data format.
6. The method of claim 1, wherein,
the satellite orbit visualization model takes satellite ephemeris and sensor parameters as input and outputs the satellite infrasatellite point coordinates and the transit time of an interested area;
the fire danger level early warning model takes soil, meteorological data, local terrain and human factors as input and outputs the probability of fire occurrence for a period of time.
7. The method according to claim 1, wherein the fire discrimination model takes satellite hot spot data as input, and the satellite hot spot data is screened through the land use type data and the pseudo hot spot database and output as screened hot spot data.
8. The method of claim 1, wherein the step S103 further comprises: and forming two-dimensional or three-dimensional visual forest fire prediction and forecast and fire comprehensive query by depending on the relational database and the fire identification data model and using a map engine.
9. The method of claim 1, wherein the Web front end software architecture comprises a database, a service framework, a Web data interface, and a reverse proxy server,
the database is a relational database MySQL, the service framework is a node. Js Express framework and a Python flash framework,
the Web data interface is a RESTful API,
the reverse proxy server is NginX, the user sends a request for accessing the Web server through the domain name, and the personal mobile terminal obtains system service.
10. A remote-on-conduction-based integrated forest fire monitoring system for performing the method of claim 1, the forest fire monitoring system comprising: a data acquisition module, a real-time data analysis module, a fire behavior identification module and a user terminal, wherein,
the data acquisition module is used for acquiring hot spot data downloaded on the satellite in real time and data generated by the integration of communication and remote communication and storing the data into the relational database according to data categories;
the real-time data analysis module is used for cleaning and analyzing the data in the relational database and inputting data in a standard format to a forest fire monitoring system;
the fire recognition module is used for carrying out algorithm processing on the data, recognizing fire and then transmitting the fire to each user side through the Internet.
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