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All Journal Formosa Journal of Computer and Information Science
Zulhamsyah Fachrurrazi Nasution
Universitas Sumatera Utara
Computer Science & IT

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IoT-Based Multi-Sensor Fusion for Goat Behavioral Pattern Recognition Using K-Means Clustering in a Smart Farming Environment Yudhistira Pratama; Normalina Napitupulu; Zulhamsyah Fachrurrazi Nasution; Adli Abdillah Nababan
Formosa Journal of Computer and Information Science Vol. 5 No. 1 (2026): March 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjcis.v5i1.16599

Abstract

Monitoring goat behavior in commercial farms typically relies on direct observation, which does not scale and misses conditions that develop gradually. This study deployed an eight-sensor IoT network across two zones of a slatted-floor goat pen in North Sumatra, Indonesia, and applied K-Means clustering to 49 days of sensor data. After a systematic data cleaning step that removed sensor dropouts, ADC saturation events, and an isolated methane spike, 213,704 records were retained (98.6% of raw data). K-Means with K=8 on the cleaned dataset yielded a Silhouette Score of 0.297 and Davies-Bouldin Index of 1.177, identifying eight behavioral and environmental states without a dedicated anomaly cluster. Results include two heat stress levels (THI means 90.7 and 92.1), three nocturnal resting states differentiated by waste pit gas concentration, a daytime active-vocal state, and an evening post-feeding fermentation peak.
Co-Authors Adli Abdillah Nababan Normalina Napitupulu Yudhistira Pratama