CN113780898A - Mechanical operation evaluation method based on Internet of things - Google Patents
Mechanical operation evaluation method based on Internet of things Download PDFInfo
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Abstract
The invention provides a mechanical operation evaluation method based on the Internet of things, which comprises the following steps: s1, acquiring data of the surrounding environment of the mechanical operation through the environment data acquisition terminal, and importing the data into the data processing module; and S2, passing through a mechanical data acquisition terminal. According to the mechanical operation evaluation method based on the Internet of things, an agricultural operation machine development level evaluation index system is established through a cloud server, the mechanical development level evaluation index parameters in each grid unit are obtained through spatial interpolation calculation, the evaluation contents are obtained through processing of a data processing module, the collected and detected contents are wide, the data is comprehensive, various information such as agricultural product production quality can be reflected, the mechanical operation contents are comprehensively evaluated, the measurement method is simplified, and the data processing efficiency is improved. The information technology such as the internet, the internet of things and big data is effectively used in agricultural machinery operation service.
Description
Technical Field
The invention relates to the technical field of new-generation information technology equipment, in particular to a mechanical operation evaluation method based on the Internet of things.
Background
The prior art mechanical operation evaluation method has the following problems:
firstly, most of monitoring objects in the prior art are changes of soil physicochemical characteristics, information reflecting agricultural product production quality such as the area and depth of monitoring mechanical operation is not provided, methods for calculating static pattern area, displacement and the like are mostly adopted in the existing algorithm for calculating land area, the measuring method is complex, and complex operation conditions such as heavy ploughing and missing ploughing are not considered;
secondly, the evaluation method in the prior art has the problems of heavy weight, light weight, insufficient service and insufficient guidance, and can not effectively use information technologies such as the internet, the internet of things and big data in the operation service of agricultural machinery, so that the evaluation is not comprehensive.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides the mechanical operation evaluation method based on the Internet of things, which has the advantages of high intelligence and high practicability and solves the problems of low intelligence and low practicability.
In order to achieve the purposes of high intelligence and high practicability, the invention is realized by the following technical scheme: a mechanical operation evaluation method based on the Internet of things comprises the following steps:
s1, acquiring data of the surrounding environment of the mechanical operation through the environment data acquisition terminal, and importing the data into the data processing module;
s2, acquiring data of the operation machine through the machine data acquisition terminal, and importing the data into the data processing module;
s3, counting the actual number and classification of the working machines, obtaining the actual data of the working range of the working machines required to work through inquiring data, setting grid units, collecting the working data of the working terrain of the machines, and importing the data into a data processing module;
s4, setting repetition times and time length, repeating the step S2, stopping circulation if the repetition times is more than the set repetition times, uploading the result of each calculation and the original data recorded in real time to a cloud server through a GPRS module, and establishing an agricultural operation machine development level evaluation index system through the cloud server;
and S5, obtaining the mechanical development level evaluation index parameters in each grid unit by utilizing spatial interpolation calculation according to the original data in S4, and processing the parameters through a data processing module to obtain the evaluation content.
Further, the environment data collecting terminal in S1 includes a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor, and a grain moisture measuring instrument, which collect environment and crop data, obtains rainfall, wind speed, terrain, soil moisture, and crop moisture data, and queries a farmland distribution map, a crop distribution map, and a road distribution map.
Further, the mechanical data acquisition terminal in S2 includes a GPS device, an ultrasonic sensor, an oil consumption sensor, an RFID tag, and CAN bus data, and is used to obtain equipment data, which mainly includes mechanical position information such as a name, a brand, a model, power, width equipment information, longitude and latitude, and data such as an actual operation area, actual operation time consumption, road travel time consumption, and oil consumption of the equipment.
Further, in S3, the main manner of performing the operation and data acquisition on the mechanical operation terrain is as follows: in actual topography, square side length is set for operation land, operation track coordinates are collected through a GPS device arranged on an operation machine, real-time depth values of operation are collected through an ultrasonic sensor arranged on the operation machine, the collected coordinates and depth data are recorded and stored through a data collection module, and operation average depth is calculated by utilizing longitude and latitude of the recorded coordinate data and mapping with the recorded depth data.
Further, the index system for evaluating the development level of the agricultural machinery in S4 includes: agricultural mechanized ecological benefit and agricultural mechanized management service level.
Further, the calculation method of the spatial interpolation in S5 is mainly a grid moving average method, that is:
firstly, acquiring a grid unit, dividing regions through the grid unit, and constructing an effective grid set;
and secondly, calculating the agricultural mechanized ecological benefit increase and agricultural mechanized management service level survey grading data in each grid.
And thirdly, calculating the distribution data in the residual grids, and carrying out average calculation on the obtained distribution data.
A mechanical operation evaluation system based on the Internet of things comprises an environmental data acquisition terminal, a mechanical data acquisition terminal, a data processing module, a GPRS module and a cloud server;
environmental data acquisition terminal: the agricultural mechanical ecological benefit evaluation system comprises a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor and a grain yield measuring instrument, wherein the collected initial data is sent to a data processing module, the initial data is collected again after the set time length, the collected data is sent to the data processing module, the average data is calculated through data processing, and the obtained average data is an agricultural mechanical ecological benefit evaluation parameter;
mechanical data acquisition terminal: the system comprises a GPS device, an ultrasonic sensor, an oil consumption sensor and an RFID electronic tag, wherein the acquired initial data is sent to a data processing module, the data is acquired again after the set time length, the acquired data is sent to the data processing module, average data is calculated through data processing, and the obtained average data is an agricultural mechanized management service level evaluation parameter;
a data processing module: processing data of an environment data acquisition terminal and a mechanical data acquisition terminal, corresponding the data of the environment data acquisition terminal and the data of the mechanical data acquisition terminal to the grid units, and calculating by utilizing spatial interpolation to obtain mechanical development level evaluation index parameters in each grid unit;
a GPRS module: transmitting data of the environmental data acquisition terminal and the mechanical data acquisition terminal;
cloud server: storing the original data and storing the evaluation index data of the development level of the agricultural operation machine;
the environment data acquisition terminal and the mechanical data acquisition terminal are connected with the GPRS module, the GPRS module is connected with the data processing module, and the data processing module is connected with the cloud server.
Advantageous effects
Compared with the prior art, the invention provides a mechanical operation evaluation method based on the Internet of things, which has the following beneficial effects:
1. according to the mechanical operation evaluation method based on the Internet of things, an agricultural operation machine development level evaluation index system is established through a cloud server, collection and detection are carried out through a new generation of information technology, intellectualization is improved, mechanical development level evaluation index parameters in each grid unit are obtained through spatial interpolation calculation, so that the collection and detection contents are wide, the evaluation quality is effectively improved on the premise that the evaluation data quantity is guaranteed, the evaluation contents are obtained through processing of a data processing module, the data is comprehensive, various information such as agricultural product production quality and the like can be reflected, the mechanical operation contents are comprehensively evaluated, the measurement method is simplified, the data processing efficiency is improved, and therefore the service level is improved.
2. According to the mechanical operation evaluation method based on the Internet of things, data of an environment data acquisition terminal and data of a mechanical data acquisition terminal are processed through a data processing module, the data of the environment data acquisition terminal and the data of the mechanical data acquisition terminal correspond to grid units, mechanical development level evaluation index parameters in each grid unit are obtained through spatial interpolation calculation, the comprehensiveness of the evaluation method in the prior art is improved, and information technologies such as the Internet, the Internet of things and big data are effectively used in agricultural machinery operation services.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention is further described below by way of examples:
the first embodiment is as follows:
a mechanical operation evaluation method based on the Internet of things comprises the following steps:
s1, collecting data of the surrounding environment of the mechanical operation through an environment data collecting terminal, wherein the environment data collecting terminal comprises a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor and grain moisture measuring instrument equipment for collecting environment and crop data, obtaining rainfall, wind speed, terrain, soil moisture and crop moisture data, inquiring a farmland distribution map, a crop distribution map and a road distribution map, and guiding the data into a data processing module;
s2, performing data acquisition on the operation machine through a mechanical data acquisition terminal, wherein the mechanical data acquisition terminal comprises a GPS device, an ultrasonic sensor, an oil consumption sensor, an RFID electronic tag and CAN bus data, is used for acquiring equipment data, mainly comprises mechanical position information such as equipment name, brand, model, power, breadth equipment information, longitude and latitude and the like, actual operation area, actual operation time consumption, road driving time consumption, oil consumption and the like, and imports the data into a data processing module;
s3, counting the actual quantity and classification of the operation machines, obtaining the actual data of the operation range required by the operation machines by inquiring the data, setting the grid cells, and carrying out operation and data acquisition on the mechanical operation terrain in the following main modes: setting square side length on working land, collecting working track coordinate by GPS device on working machine, collecting real-time depth value of working by ultrasonic sensor on working machine, recording and storing the collected coordinate and depth data by data collecting module, utilizing longitude and latitude of the recorded coordinate data to make mapping with recorded depth data to obtain working average depth, converting the longitude and latitude coordinate into relative coordinate by coordinate conversion algorithm to generate coordinate sequence of two-dimensional coordinate system, placing the coordinate sequence in a rectangle of coordinate system, including all coordinate sequences, then gridding the working rectangle with a certain side length, determining effective grid number according to the coordinate sequence number in each grid and combining real-time depth value, and adopting grid line scanning or column scanning average value to reduce error, finally, removing the severe shift points of the GPS data, calculating the effective number of grids to obtain the actual working area, wherein the effective depth value is a positive depth value, and importing the data into a data processing module;
s4, setting the repetition times and the time length, repeating the step S2, stopping circulation if the repetition times is more than the set repetition times, uploading the result of each calculation and the original data recorded in real time to a cloud server through a GPRS module, and establishing an agricultural operation machine development level evaluation index system through the cloud server, wherein the agricultural operation machine development level evaluation index system comprises: the method comprises the following steps of carrying out weight assignment on the calculation index of the agricultural mechanized ecological benefit and the calculation index of the agricultural mechanized management service level, wherein the calculation index of the agricultural mechanized ecological benefit comprises unit mechanized agricultural machine operation cost, unit mechanical operation time and mechanized operation area increment;
s5, based on the original data in S4, obtaining the mechanical development level evaluation index parameters in each grid unit by utilizing spatial interpolation calculation, wherein the spatial interpolation calculation mode is mainly a grid moving average method, namely:
firstly, acquiring a grid unit, dividing regions through the grid unit, and constructing an effective grid set;
and secondly, calculating the agricultural mechanized ecological benefit increase and agricultural mechanized management service level survey grading data in each grid.
Thirdly, calculating the distribution data in the residual grids, and carrying out average calculation on the obtained distribution data;
and processing the data through a data processing module to obtain evaluation content.
Example two:
a mechanical operation evaluation system based on the Internet of things comprises an environmental data acquisition terminal, a mechanical data acquisition terminal, a data processing module, a GPRS module and a cloud server;
environmental data acquisition terminal: the agricultural mechanical ecological benefit evaluation system comprises a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor and a grain yield measuring instrument, wherein the collected initial data is sent to a data processing module, the initial data is collected again after the set time length, the collected data is sent to the data processing module, the average data is calculated through data processing, and the obtained average data is an agricultural mechanical ecological benefit evaluation parameter;
mechanical data acquisition terminal: the system comprises a GPS device, an ultrasonic sensor, an oil consumption sensor and an RFID electronic tag, wherein the acquired initial data is sent to a data processing module, the data is acquired again after the set time length, the acquired data is sent to the data processing module, average data is calculated through data processing, and the obtained average data is an agricultural mechanized management service level evaluation parameter;
a data processing module: processing data of the environmental data acquisition terminal and the mechanical data acquisition terminal, corresponding the environmental data acquisition terminal and the mechanical data acquisition terminal to grid units, and obtaining mechanical development level evaluation index parameters in each grid unit by utilizing spatial interpolation calculation;
a GPRS module: transmitting data of the environmental data acquisition terminal and the mechanical data acquisition terminal;
cloud server: storing original data and agricultural operation machine development level evaluation index data;
the environment data acquisition terminal and the mechanical data acquisition terminal are connected with the GPRS module, the GPRS module is connected with the data processing module, and the data processing module is connected with the cloud server.
In summary, according to the mechanical operation evaluation method based on the internet of things, an agricultural operation machine development level evaluation index system is established through a cloud server, mechanical development level evaluation index parameters in each grid unit are obtained through spatial interpolation calculation, processing is performed through a data processing module, evaluation contents are obtained, the collected and detected contents are wide, data are comprehensive, various information such as agricultural product production quality can be reflected, the mechanical operation contents are comprehensively evaluated, the measurement method is simplified, and the data processing efficiency is improved.
According to the mechanical operation evaluation method based on the Internet of things, data of the environment data acquisition terminal and data of the mechanical data acquisition terminal are processed through the data processing module, the data of the environment data acquisition terminal and the data of the mechanical data acquisition terminal correspond to grid units, mechanical development level evaluation index parameters in each grid unit are obtained through spatial interpolation calculation, the comprehensiveness of the evaluation method in the prior art is improved, and information technologies such as the Internet, the Internet of things and big data are effectively used in agricultural machinery operation services.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A mechanical operation evaluation method based on the Internet of things is characterized by comprising the following steps:
s1, acquiring data of the surrounding environment of the mechanical operation through the environment data acquisition terminal, and importing the data into the data processing module;
s2, acquiring data of the operation machine through the machine data acquisition terminal, and importing the data into the data processing module;
s3, counting the actual number and classification of the operation machines, obtaining the actual data of the operation range required by the operation machines through inquiring data, setting grid units, carrying out operation and data acquisition on the operation terrain of the machines, and importing the data into a data processing module;
s4, setting repetition times and time length, repeating the step S2, stopping circulation if the repetition times is more than the set repetition times, uploading the result of each calculation and the original data recorded in real time to a cloud server through a GPRS module, and establishing an agricultural operation machine development level evaluation index system through the cloud server;
and S5, obtaining the mechanical development level evaluation index parameters in each grid unit by utilizing spatial interpolation calculation according to the original data in S4, and processing the parameters through a data processing module to obtain the evaluation content.
2. The mechanical work evaluation method based on the internet of things according to claim 1, wherein: and the environment data acquisition terminal in the S1 comprises a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor and grain moisture measuring instrument equipment for acquiring environment and crop data, acquires rainfall, wind speed, terrain, soil moisture and crop moisture data, and inquires a farmland distribution map, a crop distribution map and a road distribution map.
3. The mechanical work evaluation method based on the internet of things according to claim 1, wherein: the mechanical data acquisition terminal in the S2 comprises a GPS device, an ultrasonic sensor, an oil consumption sensor, an RFID electronic tag and CAN bus data, is used for acquiring equipment data, and mainly comprises mechanical position information such as the name, the brand, the model, the power, the breadth equipment information, the longitude and the latitude and the like of the equipment, and data such as the actual operation area, the actual operation time consumption, the road driving time consumption and the oil consumption.
4. The mechanical work evaluation method based on the internet of things according to claim 1, wherein: in S3, the main manner of performing operation and data acquisition on the mechanical operation terrain is as follows: in actual topography, square side length is set for operation land, operation track coordinates are collected through a GPS device arranged on an operation machine, real-time depth values of operation are collected through an ultrasonic sensor arranged on the operation machine, the collected coordinates and depth data are recorded and stored through a data collection module, and operation average depth is calculated by utilizing longitude and latitude of the recorded coordinate data and mapping with the recorded depth data.
5. The mechanical work evaluation method device based on the internet of things according to claim 1, wherein: the agricultural operation machine development level evaluation index system in the S4 comprises the following steps: agricultural mechanized ecological benefit and agricultural mechanized management service level.
6. The mechanical work evaluation method device based on the internet of things according to claim 1, wherein: the calculation mode of the spatial interpolation of S5 is mainly a grid moving average method, namely:
firstly, acquiring a grid unit, dividing regions through the grid unit, and constructing an effective grid set;
calculating agricultural mechanized ecological benefit increase and agricultural mechanized management service level survey grading data in each grid;
and thirdly, calculating the distribution data in the residual grids, and carrying out average calculation on the obtained distribution data.
7. A system using the internet of things based machine work evaluation method of claim 1, characterized in that: the system comprises an environmental data acquisition terminal, a mechanical data acquisition terminal, a data processing module, a GPRS module and a cloud server;
environmental data acquisition terminal: the agricultural mechanical ecological benefit evaluation system comprises a rainfall sensor, a wind speed sensor, a gradiometer, a soil moisture sensor and a grain yield measuring instrument, wherein the collected initial data is sent to a data processing module, the initial data is collected again after the set time length, the collected data is sent to the data processing module, the average data is calculated through data processing, and the obtained average data is an agricultural mechanical ecological benefit evaluation parameter;
mechanical data acquisition terminal: the system comprises a GPS device, an ultrasonic sensor, an oil consumption sensor and an RFID electronic tag, wherein the acquired initial data is sent to a data processing module, the data is acquired again after the set time length, the acquired data is sent to the data processing module, average data is calculated through data processing, and the obtained average data is an agricultural mechanized management service level evaluation parameter;
a data processing module: processing data of an environment data acquisition terminal and a mechanical data acquisition terminal, corresponding the data of the environment data acquisition terminal and the data of the mechanical data acquisition terminal to the grid units, and calculating by utilizing spatial interpolation to obtain mechanical development level evaluation index parameters in each grid unit;
a GPRS module: transmitting data of the environmental data acquisition terminal and the mechanical data acquisition terminal;
cloud server: storing the original data and storing the evaluation index data of the development level of the agricultural operation machine;
the environment data acquisition terminal and the mechanical data acquisition terminal are connected with the GPRS module, the GPRS module is connected with the data processing module, and the data processing module is connected with the cloud server.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116703335A (en) * | 2023-08-04 | 2023-09-05 | 山东创恩信息科技股份有限公司 | Engineering supervision method and system based on Internet of things data sharing |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105652840A (en) * | 2016-02-03 | 2016-06-08 | 西北农林科技大学 | Mechanical deep scarification work quality monitoring and evaluation method and system |
| CN109685267A (en) * | 2018-12-21 | 2019-04-26 | 华中农业大学 | A kind of agricultural mechanical operation service analysis system and method |
| CN110119869A (en) * | 2019-03-18 | 2019-08-13 | 中国农业大学 | A kind of movable type farmland quality and/or production capacity research and appraisal system and method for ploughing |
| CN111880239A (en) * | 2020-08-31 | 2020-11-03 | 自然资源部第一海洋研究所 | Quantitative evaluation method for cobalt-rich crust resources in Haishan |
-
2021
- 2021-11-04 CN CN202111296721.8A patent/CN113780898B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105652840A (en) * | 2016-02-03 | 2016-06-08 | 西北农林科技大学 | Mechanical deep scarification work quality monitoring and evaluation method and system |
| CN109685267A (en) * | 2018-12-21 | 2019-04-26 | 华中农业大学 | A kind of agricultural mechanical operation service analysis system and method |
| CN110119869A (en) * | 2019-03-18 | 2019-08-13 | 中国农业大学 | A kind of movable type farmland quality and/or production capacity research and appraisal system and method for ploughing |
| CN111880239A (en) * | 2020-08-31 | 2020-11-03 | 自然资源部第一海洋研究所 | Quantitative evaluation method for cobalt-rich crust resources in Haishan |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116703335A (en) * | 2023-08-04 | 2023-09-05 | 山东创恩信息科技股份有限公司 | Engineering supervision method and system based on Internet of things data sharing |
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