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

• Main Authors: Garces, Anton Luis C., Obusan, Gianne Marcus V., Ong, Julianne Abbe R., Perez, Samuel C.
• Format: text
• Language: English
• Published: Animo Repository 2023
• Subjects: Goats—Monitoring; Goats—Feeding and feeds; Goats—Behavior; Goats—Technological innovations; Electrical and Computer Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etdb_ece/31; https://animorepository.dlsu.edu.ph/context/etdb_ece/article/1036/viewcontent/A_Network_Based2_Solution_and_Knowledge_Building_Portal_for_Monito.pdf
• Institution: De La Salle University

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.