Abstract

Pig farming is becoming a key industry of China’s rural economy in recent years. The current pig farming is still relatively manual, lack of latest Information and Communication Technology (ICT) and scientific management methods. This paper proposes an industrial internet platform for massive pig farming, namely, IIP4MPF, which aims to leverage intelligent pig breeding, production rate and labor productivity with the use of artificial intelligence, the Internet of Things, and big data intelligence. We conducted requirement analysis for IIP4MPF using software engineering methods, designed the IIP4MPF system for an integrated solution to digital, interconnected, intelligent pig farming. The practice demonstrates that the IIP4MPF platform significantly improves pig farming industry in pig breeding and productivity.

Highlights

  • Almost all of the pig can be used as food

  • This paper proposes an industrial internet platform for massive pig farming, namely, IIP4MPF, which aims to leverage intelligent pig breeding, production rate and labor productivity with the use of artificial intelligence, the Internet of Things, and big data intelligence

  • There are many styles of farming: intensive commercial units, commercial free range enterprises. All these forms are in use today, intensive farms are the most popular due to their abilities to raise a large amount of pigs in a very cost-efficient manner

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Summary

Introduction

There are many styles of farming: intensive commercial units, commercial free range enterprises All these forms are in use today, intensive farms are the most popular due to their abilities to raise a large amount of pigs in a very cost-efficient manner. For an advanced smart pig farming system, we realize that it’s better to make use of digitalization, infomatization and Internet of things to collect data on pig life cycle for pig industry. With those data to guide pig farming, a pig farm could achieve lean management with high production efficiency and quality.

Related Work
Requirement Analysis
System Users
Functional Requirements
Non-Functional Requirements
System Architecture
Farming Management
Disease Surveillance
Digital Breeding Management
Intelligent Service System
Conclusions and Future Work
Full Text
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