Design Predictive Model for RFID Tag Based Livestock Identification and Monitoring System

Velmurugan Lingamuthu, Tensae Endrias Zewdu, Paul Mansingh

2024

Abstract

In the last recent years, the level of automation in the farming process has increased significantly. The key component of these new techniques is live-stock identification and monitoring. As it is known, Ethiopia is rich in its livestock sector but has never gained adequate profit from it. The basic problem is farm management issues, attention given to it, and the livestock value chain inharmoniousness. The research aimed at automating the traditional farm management practice using analytical processes. This paper uses an individual identification of cattle intended for any farm using an ear tag embedded with radio frequency identification (RFID) technology, where each cattle is tagged with an identifying number as a reference. The data was collected from Alfa fooder & Dairy Farm P.L.C of years 2015 to 2020. The data then faded to a data mining software to make a prediction based on the input data set. In this research work, an at-tempt has been made to apply the comparative classification model predictive data mining techniques in the cattle livestock sector for the milk, meat, and skin and hide quality yield products. Machine learning classification algorithms such as Naïve Bayes, decision tree classifier and J48 classifier have been practiced. The overall model accuracy of Naïve Bayes Net (94.24%) shows it has a better prediction.

Paper Citation

in Harvard Style

Lingamuthu V., Zewdu T. and Mansingh P. (2024). Design Predictive Model for RFID Tag Based Livestock Identification and Monitoring System. In Proceedings of the 1st International Conference on Emerging Innovations for Sustainable Agriculture - Volume 1: ICEISA; ISBN 978-989-758-714-6, SciTePress, pages 20-26. DOI: 10.5220/0012879300004519

in Bibtex Style

@conference{iceisa24,
author={Velmurugan Lingamuthu and Tensae Zewdu and Paul Mansingh},
title={Design Predictive Model for RFID Tag Based Livestock Identification and Monitoring System},
booktitle={Proceedings of the 1st International Conference on Emerging Innovations for Sustainable Agriculture - Volume 1: ICEISA},
year={2024},
pages={20-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012879300004519},
isbn={978-989-758-714-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Emerging Innovations for Sustainable Agriculture - Volume 1: ICEISA
TI - Design Predictive Model for RFID Tag Based Livestock Identification and Monitoring System
SN - 978-989-758-714-6
AU - Lingamuthu V.
AU - Zewdu T.
AU - Mansingh P.
PY - 2024
SP - 20
EP - 26
DO - 10.5220/0012879300004519
PB - SciTePress