Ultra-high Frequency RFID-Based Embedded System for Livestock Management and Automation

The quality of livestock products depends on how they are managed and handled. In traditional livestock management no proper records are kept to trace the medical history and production of the livestock. Furthermore, scientific analysis to improve its daily operation and management is not easy to carry out due to the absence of the records management system. Recently, a monitoring system is introduced for livestock management using a Low Frequency (LF) Radio Frequency System (RFID) system. The problem with this system is that it has short detection range and slower reading speed. Furthermore, it cannot support dense tag environment. It gives problems to farmers to implement this system. In this thesis, the development of an Ultra High Frequency (UHF) RFID-based embedded system for livestock management and automation is proposed. The system consists of a comprehensive database system for five kinds of animals such as cows, goats, deer, sheep, and horses. The database contains the type of disease, medication, vaccination, nutrition, history and current status of livestock. The database is developed using MySQL. In addition, the proposed system is linked to the equipments of the animal house such as lighting, temperature, food, and water container which are connected to the database system. The system is linked to the internet facilities where multiple clients and server concept is implemented. The clients can insert/retrieve data to/from database by using Graphical User Interface (GUI) which is developed using PHP. Each animal is tagged with an UHF RFID transponder. The UHF RFID system is connected to database by Application Programming Interface (API) which is designed using C# programming language. The experimental result indicates that the detection range of UHF RFID system has been increased to 116 cm as comparison to the detection range of 20 cm using LF RFID system. It can also support dens tag environment up to 1000 tags simultaneously. The API gets data from tags and save it to the database successfully. The internet multiple clients and server of the proposed system has been implemented successfully.

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