Summary of project experience in developing intelligent agricultural management system using C#

Smart agriculture is the current trend of agricultural development, using advanced technological means to improve agricultural production efficiency, reduce production costs, and ensure food security. In order to better realize agricultural intelligence, my team developed an intelligent agricultural management system using the C# programming language. Now I will share the project experience with you, hoping to provide some inspiration to readers in need.

1. Requirements Analysis

Before the project started, we conducted a detailed requirements analysis, including functional requirements and non-functional requirements. Functional requirements mainly include planting management, process monitoring, data statistics, etc. Non-functional requirements include safety, ease of use, performance, etc. Through demand analysis, we clarified the goals and direction of the project and laid the foundation for subsequent development.

2. Architecture design

During the development process, we adopted the MVC (Model-View-Controller) architecture pattern to separate business logic, interface design and data processing to facilitate different team members. Collaborative development. At the same time, we also use the N-layer architecture to split the application into multiple layers, including the presentation layer, application service layer, domain layer, data access layer, etc., to facilitate project maintenance and management.

3. Technology Selection

In project development, we chose the C# programming language and used the .NET framework for development. At the same time, we also used the ASP.NET MVC framework and Entity Framework framework to quickly develop efficient and reliable web applications. In addition, we also apply SQL Server database and Azure cloud platform to achieve data storage and security management.

4. Process Management

In project development, we adopt agile development methods, dividing the development cycle into multiple short-term iterations, and perform requirements analysis, design, coding and Testing and other work. At the same time, we also use TFS (Team Foundation Server) for version control and collaboration management to ensure smooth code collaboration and communication among team members.

5. Problem Solving

During the development process, we also encountered many problems. For example, during system testing, data statistics errors occurred. We conducted detailed troubleshooting and repairs for this issue, and finally successfully resolved it. The emergence of these problems reminds us to pay attention to details during the development process, strengthen testing and debugging, and ensure the integrity and stability of system functions.

Through the above experience summary, we have successfully developed an intelligent agricultural management system and applied it to actual agricultural production. We believe that this system will play an important role in the future development of agricultural intelligence. At the same time, we also hope that more developers can join in the development of smart agriculture and use technological means to promote the development of modern agriculture.

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