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 Academic Journal of Science, Engineering and Technology 

Vol.7, Issue 1; January - Febuary 2022; 

1252 Columbia Rd NW, Washington DC, United States 

https://topjournals.org/index.php/AJSET/index; mail: topacademicjournals@gmail.com 

  

 

 

30 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

REVOLUTIONIZING AGRICULTURE: MECHANICAL ELECTRONIC 

ENGINEERING IN MACHINERY INTEGRATION CONTROL 

 

Deng, Xiao-Qiang  
1College of Mechanical and Transportation, Southwest Forestry University, Kunming, 650000, Yunnan,  

China 

 

Abstract: The rapid advancements in science and technology have ushered in a new era of intelligent and 

automated agricultural production, propelling the fields of Control Engineering and Mechanical Electronic 

Engineering toward greater intelligence and automation. This symbiotic relationship between the two fields has 

led to an ever-increasing demand for control technology. Consequently, this article delves into the research and 

implementation of an integrated intelligent agricultural machinery system. The primary focus is on elucidating 

the application methodologies of the 3S integration framework, WebGIS, and related technologies within the 

realm of intelligent agricultural machinery. 

The crux of this endeavor revolves around harnessing the power of the 3S (Geographic Information System, 

Global Positioning System, and Remote Sensing) technology, with the overarching objective of constructing an 

agricultural machinery service management integration platform under the robust architecture of WebGIS. 

Furthermore, this research aims to seamlessly incorporate emerging computer concepts like the Internet of Things, 

cloud computing, and the B2C e-commerce model into the framework of intelligent agricultural machinery. 

The integration of these cutting-edge concepts into the 3S technology framework serves as the linchpin of this 

research. The objective is to maximize their inherent strengths, establish a series of technical framework models, 

and expedite the development of a resilient and potent intelligent agricultural machinery integration system. 

Keywords: Intelligent Agriculture, 3S Integration Framework, WebGIS Architecture, Internet of Things, Cloud 

Computing  

1. Introduction  

The development of science and technology has accelerated the intelligent and automatic process of agricultural 

production, and also made machinery and Electronic engineering gradually develop in the direction of intelligence 

and automation, which makes the demand and demand for control technology constantly increase. There is a 

complementary relationship between Control engineering and mechanical Electronic engineering. The 

development of both can not only promote the rapid development of mechanical Electronic engineering, but also 

provide more possibilities and development directions for it. Therefore, this article conducts research on the 

implementation of intelligent agricultural machinery integration system, focusing on exploring the application 

methods of 3S integration framework, WebGIS and other related technologies in intelligent agricultural 

machinery, with the core of building 3S technology and the goal of building an agricultural machinery service 

management integration platform under WebGIS architecture. At the same time, in response to the newly proposed 

concepts in the computer field such as the Internet of Things, cloud computing, B2C e-commerce mode, how to 

apply them in intelligent agricultural machinery and integrate them into the 3s technology framework, in order to 

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 Academic Journal of Science, Engineering and Technology 

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1252 Columbia Rd NW, Washington DC, United States 

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31 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

better utilize their own advantages, establish a series of technical framework models, and quickly develop a stable 

and powerful intelligent agricultural machinery integration system.  

The innovative application of mechanical engineering in agricultural machinery integration is one of the current 

research hotspots, among which Sun Wei's goal is to focus on developing an integrated device for self-cleaning 

air filters of agricultural machinery air conditioning condensers, which can effectively solve the air cooling 

problem of agricultural machinery condensers caused by poor working conditions. Agricultural machinery and 

air conditioning condensers are prone to blockage by dust, pests, weeds, etc., resulting in poor heat dissipation 

and frequent malfunctions. To save resources, improve economic efficiency, adapt to agricultural structural 

adjustment, and improve the technical level of agricultural environmental protection equipment [1]. 

Pimonratanakan Sudarat's research adopts quantitative and qualitative research methods. Quantitative research 

was used to investigate the reasons and Relations of production of agricultural machinery business [2]. Abuselidze 

George proposed that the current situation requires manufacturers to focus their agricultural machinery activities 

on long-term profits and business efficiency [3]. Tian Hongkun believes that in the future, computer vision 

technology would be combined with intelligent technologies such as deep learning technology, applied to all 

aspects of agricultural production management based on large-scale datasets, and more widely applied to solve 

all aspects of agricultural production management. To solve current agricultural problems and better improve the 

economic, universal, and robust performance of agricultural automation systems, thereby promoting the 

development of agricultural automation equipment and systems towards a more intelligent direction [4]. However, 

due to insufficient data sources, the above research is only in the theoretical stage and lacks practical significance.  

After consulting a large number of literatures, this paper studies and analyzes the Internet of Things, cloud 

computing, B2C mode and 3S (Integration Of Gps, Rs And Gis Technology) integration technology, and integrates 

these Technological convergence together, thus finding a basic framework model suitable for intelligent 

agricultural machinery integrated system [5-6]. Based on 3S technology and the software requirements of the 

system, the design of the system's structural system, functional modules, performance indicators, workflow, and 

database was ultimately achieved. The system's structural system, functional modules, performance indicators, 

workflow, and database were selected, and related software development techniques were used to carry out 

research and development work.  

2. Design and Smart Electromechanical Systems in Agricultural Machinery Integration  

2.1. Overall System Design  

From the perspective of the data needs of the intelligent agricultural machinery integration system, the data 

involved in the system can be divided into three classes for data sharing and services on the intelligent agricultural 

machinery integration platform; Business data includes three categories: agricultural machinery service 

organization, inter data, business data, and resource data, including basic geographic data, remote sensing images 

of agricultural machinery, orders, and related information data of different users, providing data support for 

business systems. The resource data includes information related to data backup, resource management and 

maintenance, user role permissions, etc., providing data support for business applications [7].  

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 Academic Journal of Science, Engineering and Technology 

Vol.7, Issue 1; January - Febuary 2022; 

1252 Columbia Rd NW, Washington DC, United States 

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32 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

The intelligent agricultural comprehensive management system is built on a network foundation, therefore it uses 

a browser/server architecture (B/S, Browser/Server) development method; J2ee with three-tier structure is divided 

into Presentation layer, middle layer, and data service layer; In order to ensure the universality, efficiency, 

portability, and security of the system, this article selects the Java platform for system development and 

deployment; Software system development is carried out through Java language and WEBGIS related 

technologies, and technologies such as the Internet of Things, cloud computing, and B2C e-commerce mode are 

introduced in the research and development. 3S technology is used for data collection, management, calculation, 

analysis, and display to achieve a smart agricultural machinery integration system [8-9]. Based on the principles 

of B/S design mode and j2ee three-tier architecture, and combined with the actual Functional requirement of the 

system, it is divided into three layers: user layer, application layer and data layer, as shown in Figure 1.  

 

 

 
PostgreSQL 

GeoServer 

 

WEB 

service 

 
 

  

Figure 1. Structure diagram of intelligent agricultural machinery integration system  

From Figure 1, it can be seen that the user layer is a place for in machine interaction, where various functional 

pages of the system can be displayed in different browsers. This article adopts the Jquery framework and Ajax 

technology to develop web page interaction functions. With the help of OpenLayers technology, various map 

functions of WEBGIS are completed. Users can send request instructions to the application layer through HTTP 

(Hyper Text Transfer Protocol) requests in the browser, using the Internet's transmission protocol. After the system 

processes these requests, the required data results are returned to complete the user's operation function.  

OpenLayers is a JavaScript package used to develop WebGIS clients, with an application layer deployed on a 

WEB server, consisting of two parts: the control layer and the business logic layer. The control layer is managed 

by Struts, which ensures interaction between the user layer and the business logic layer. The role of Spring can 

be extended to the entire application layer. It can be accessed through the combination of Struts and Spring, using 

Java functional code to access data services in the data layer. Finally, the application layer searches for data based 

on user request instructions and returns it to the user layer, allowing users to perform operations.  

In the data layer, it includes GeoServer servers and PostgreSQL databases, as well as some distributed web 

services and map services. The application layer utilizes access to the GeoServer server and PostgreSQL database 

B rowser model 

Jquery 、 Ajax 
、 OpenLayers 

J2EE three-tier architecture 

Control layer 

Business  
logic layer 

browser 

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 Academic Journal of Science, Engineering and Technology 

Vol.7, Issue 1; January - Febuary 2022; 

1252 Columbia Rd NW, Washington DC, United States 

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33 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

to obtain basic geographic information data and business data. The Java functional code in the application layer 

can directly call the agricultural machinery terminal monitoring data service published by the data center, or use 

the internet to call the slicing service of published remote sensing images and vector maps, and feedback the data 

to the user's hands in the application layer. The data layer provides sufficient data support for the entire system's 

work [10-11].  

2.2. System Module Design  

The intelligent agricultural machinery integration system is mainly used by farmers, agricultural machinery 

service organizations and governments. Each user would have different Functional requirement, and there would 

be certain data logical relationships between different users [12-13]. Therefore, when designing the system 

modules, it should design each functional module of the system based on the user's Functional requirement and 

the relationship between them. The intelligent agricultural machinery integration system mainly includes three 

subsystems, namely the agricultural machinery operation service system, the agricultural machinery operation 

scheduling and supervision management system, and the agricultural machinery operation auxiliary decision-

making system. Each subsystem is composed of different functional modules [14]. The overall module design of 

the intelligent agricultural machinery integration system is shown in Figure 2:  

 
Operation service system agricultural machinery operation management system 

Figure 2. Intelligent Agricultural Machinery Integrated System  

The agricultural machinery operation service system mainly includes four modules: homepage, supply 

information, order management, and job allocation. It provides farmers with functions such as agricultural 

machinery service organization retrieval, map display operation, order management (adding, deleting, modifying, 

querying), and assigning agricultural machinery service organizations to orders.  

The agricultural machinery job scheduling and monitoring management system consists of modules such as 

homepage, order management, job scheduling, job supervision, job analysis, information management, trajectory 

Intelligent 

integrated agricultural 

machinery syste

m

Agricultural 

machinery 

Agricultural machinery 

operation scheduling and 

monitoring 

Auxiliary decision 

system for 

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 Academic Journal of Science, Engineering and Technology 

Vol.7, Issue 1; January - Febuary 2022; 

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34 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

point management, etc., enabling users of agricultural machinery service organizations to manage orders, 

schedule jobs, monitor agricultural machinery and operators, and manage relevant information under the 

organization [15-16].  

The main content of agricultural machinery operation assistance decision-making includes: agricultural 

machinery dynamics and theme dynamics on the homepage, operation analysis, emergency management of 

emergency and temporary orders and emergencies, operation quality monitoring, service organization 

management, and user management. These can be utilized by government users to monitor and manage 

agricultural machinery service organizations, work quality, and emergency events, help farmers expand orders, 

and conduct statistics and analysis on various data of agricultural production and agricultural machinery service 

organizations in Beijing, providing data support for local agricultural production, economic development, and 

policy formulation [17].  

2.3. Process Design  

According to the main Functional requirement of users, the business process of the intelligent agricultural 

machinery integration system can be divided into six aspects: demand service, order scheduling, agricultural 

machinery operation, dynamic management, statistical analysis and auxiliary decision-making, as shown in 

Figure 3:  

Farmer 

 Agricultural 

machinery 

service 

organization 

 

Government 

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 Academic Journal of Science, Engineering and Technology 

Vol.7, Issue 1; January - Febuary 2022; 

1252 Columbia Rd NW, Washington DC, United States 

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35 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

 
  

Figure 3. Business Process of Intelligent Agricultural Machinery Integration System  

From Figure 3, it can be seen that:  

Demand service: Farmers can find agricultural machinery service institutions on this service site and submit their 

service needs. They can also request their needs from agricultural machinery service institutions and relevant 

government departments by phone, and then the agricultural machinery institutions and government department 

staff would complete the filling of the order, and finally inform the farmers of the processing results of the order.  

Order delivery: The agricultural technology promotion agency shall deliver the required machinery and 

machinery personnel to the designated locations according to the requirements in the order, and carry out 

agricultural technology promotion for farmers.  

Agricultural machinery operation: The agricultural machinery service agency informs the operator through SMS 

on their mobile phones. The operator drives the agricultural machinery to the work site according to the 

requirements of the order, carries out agricultural work, and timely transmits work tasks and status information 

to the system [18].  

Dynamic supervision: Through the data transmitted by the agricultural machinery mobile terminal, the operation 

path and status of the agricultural machinery are controlled, and real-time positioning of the agricultural 

machinery and manipulator is carried out. The agricultural machinery operation trajectory points can be replayed, 

and the operation area can be estimated [19].  

Demand service 

Service website Demand order 

Order scheduling 

Agricultural machinery  
operation 

Dynamic supervision 

Statistical analysis 

Telephone 

Job quality 

Agricultural machinery  
service organization  

information 

Aid decision making 

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36 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

Statistical analysis: According to the situation of agricultural machinery, machinery operators, and operation time, 

agricultural machinery service agencies have conducted statistics and analysis on the operation area, crop types, 

and operation types.  

Assistance in decision-making: The government has conducted real-time understanding of agricultural machinery 

service institutions, number of agricultural machinery, agricultural machinery operation area, crop types, 

operation quality, operation time, and other information, providing scientific, comprehensive, and direct data 

support for the formulation of various agricultural production plans and support subsidy policies in Beijing.  

2.4. Database Design  

The Web mapping used in the intelligent agricultural machinery integration system mainly calls the WMTS map 

slicing service and remote sensing image slicing service issued by Tianmap.com. Remote sensing images are 

mainly used for the operation quality analysis module under the agricultural machinery operation assistant 

decision-making system. The WMTS (Western Main Transportation Services) remote sensing image slicing 

service released by GEOServer is called, and the image data provides real-time and reliable monitoring data for 

field area, crop types, crop yield estimation, crop maturity, harvesting range, etc., ensuring the statistical analysis 

and scientific decision-making work of government departments. Other spatial data, system business data, and 

resource data are all stored in the local PostgreSQL database. The system would obtain data uploaded by 

agricultural machinery mobile terminals from the data center in real-time through service requests, and save the 

data in the local database for quick use by the intelligent agricultural machinery integration system. The intelligent 

agricultural machinery integration system is composed of three subsystems, each independent and interrelated, 

composed of data in the database, separated from each other and not interfering with each other, but some data 

(such as spatial data) is shared. Identify the attribution of data through ID identification and grouping in the data 

table. When designing the database design, all data tables and fields ensure users of different types and 

permissions according to data, structure, logical relationship and certain data. There is no conflict between data 

to prevent system errors. The user information table and spatial information table are shown in Tables 1 and 2:  

Table 1. User Information Table  

Field Name  Model  Meaning  

Lid  Character Varying  Usergroup Id  

Luserid  Character Varying  User Id  

Loginname  Character Varying  Username  

Password  Character Varying  Password  

Login Title  Character Varying  Name  

Lid Card  Character Varying  Id Number  

Imobilephone  Character Varying  Contact Number  

Table 2. Spatial Information Table  

Field Name  Model  Meaning  

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37 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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Gdsid  Character Varying  Identification Id  

Gdstitle  Character Varying  Place Name  

Centerx  Numeric(10,2)  Longitude Of Center 

Point  

Centery  Numeric(10,2)  Latitude Of Center Point  

Gdstreelevel  Smallint  Layer Level  

Among them, the user information table in Table 1 includes the user's personal identification ID and group ID, as 

well as the user name, password, name, contact number, ID number and other basic registered information. The 

spatial information table shown in Table 2 includes basic geographical information of the country and stores 

spatial information data such as place names, center point coordinates, layer levels, spatial dimensions, etc., at 

the provincial, municipal, county, township, and village levels, providing sufficient geographic information for 

displaying electronic maps.  

2.5. System Data Platform Services  

On the intelligent agricultural machinery Big data system, based on the analysis of historical data such as 

agricultural machinery distribution data, agricultural machinery operation data, and agricultural machinery 

purchase data, the development of agricultural machinery in various regions was analyzed [20]. The analysis of 

the development of agricultural machinery consists of six aspects, namely: analysis of the number of agricultural 

machinery owned, analysis of the number of newly purchased agricultural machinery, analysis of the proportion 

of imported agricultural machinery, ranking of agricultural machinery brands, analysis of agricultural machinery 

subsidy data, and analysis of agricultural machinery maintenance data. Introducing the annual average growth 

rate into the study of the ownership of agricultural machinery can better reflect the development of agricultural 

machinery. The year-on-year development rate refers to the relative development rate achieved in the current 

period compared to the same period last year. Its mode is:  

l −u 

v =                                     (1) u 

v represents the year-on-year development speed, l represents the development level of the current period, and u 

represents the development level of the same period last year. The analysis of agricultural machinery ownership 

in this article adopts this indicator, such as the development speed calculated by comparing a certain year with 

the same period of the previous year. The month on month comparison is based on the current data as the reporting 

period, and the previous data as the base period. The comparison between the reporting period and the base period 

is the month on month comparison. The change in the number of agricultural machinery is represented by year-

on-year growth and month on month growth rate, and the formula is:  

m 

p =                                     (2) n rb −rs 

 q=                                   (3)  

rb 

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38 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

Among them, p represents year-on-year growth, m represents the quantity of agricultural machinery last year, n 

represents the quantity this year, q represents the month on month growth rate, r
b represents the quantity of 

agricultural machinery this month, and rs represents the quantity of agricultural machinery in the previous month 

[21-22].  

3. Testing and Intelligent Agricultural Machinery Integration System  

In the network environment, the network environment has a significant impact on the responsiveness of the 

network environment. The response rate experiment in this article aims to detect changes in the corresponding 

response time of the system as there are more and more concurrent requirements in the system. The calculation 

of response time is a request made from the client. After it arrives at the server, it undergoes a series of interactions 

(such as reading request files, querying relevant database information, etc.), and then returns to the client from 

the server to complete the response. In some testing tools, the response time is referred to as TTLB, as shown in 

Figure 4:  

 
Figure 4. Response Time Statistics  

As shown in Figure 4, the response time increases with the increase of concurrency, with an average response 

time of 236ms, a maximum response time of 698ms, and a minimum response time of 178ms when the 

concurrency is 100. When the concurrency is 1000, the average response time is 798ms, the maximum response 

time is 1236ms, and the minimum response time is 514ms.  

  

0 

200 

400 

600 

800 

1000 

1200 

1400 

100 200 300 400 500 600 700 800 900 1000 

Type 

Average response time Minimum response time Maximum response time 

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39 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

4. Conclusions  

Mechanised agriculture is a key indicator of agricultural modernization. In this process, modern computer 

technology should be brought into full play to build a set of agricultural machinery service management 

integration system suitable for the The Internet Age. This would help to improve the level of China's agricultural 

machinery informatization, strengthen the macro control of government departments on Mechanised agriculture, 

and promote the overall development of Mechanised agriculture and informatization. A set of agricultural 

machinery informatization service management system that matches the economic system can be constructed. 

This is a major method of combining agricultural production with information technology. In recent years, 

information technology has been increasingly applied in agricultural production, and digitalization of agricultural 

machinery service management is a representative example of the development of agricultural informatization. 

Building a new model of agricultural machinery service management can help agricultural machinery service 

organizations schedule orders in a timely manner during busy agricultural seasons, manage all agricultural 

machinery and operators under them, and quickly provide agricultural machinery services to farmers. This has 

completely transformed the traditional management methods of agricultural machinery services, making the 

intelligent and information-based development of agricultural machinery operation services possible.  

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40 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

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41 | A c a d e m i c  J o u r n a l  o f  S c i e n c e ,  E n g i n e e r i n g  a n d  T e c h n o l o g y  

|  https://topjournals.org/index.php/AJSET 

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