A network-based solution and knowledge-building portal for monitoring goat feeding behavior pattern and agricultural technology information sharing

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ID: 285968
2023
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Abstract
Goat farming shows potential as one of the solutions for providing quality livestock products in developing countries. However, as with humans, goats require good health to yield high-quality products. Through this study, the researchers created a wearable device consisting of an accelerometer, gyrometer, and temperature sensors to monitor the goat’s feeding behavior. The data collected by these sensors were transmitted to a spreadsheet file for processing in a MATLAB application. This application made use of the k-NN machine-learning algorithm for accurate prediction. Verifying the algorithm was done by comparing video footage with the predictions made by the algorithm. Lastly, a knowledge-building portal was created to relay important information concerning goats to livestock farmers. Results show that the goats felt comfortable wearing the device. The application also predicted the goat’s feeding pattern with an accuracy of 98.02% for the sensor data. Furthermore, the farmers showed interest in the knowledge-building portal and recommended it to other farmers. In improving the study, the researchers recommended using other machine learning algorithms for data classification.
Reference Key
persistent_1760657187_68f17f23ac4d9 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Perez, Samuel C.
Journal Malay Journal
Year 2023
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdb_ece/31
Keywords Keywords not found

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