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All Journal Journal of Technology and System Information
Farel, I
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Computer Science & IT

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Advancing Sustainable Agriculture through Smart Farm Tagging and AI-Driven IoT Dashboards Setiawan, Feri; Kumara, I; Amertha, I; Pioni, Ni; Putra, I; Farel, I
Journal of Technology and System Information Vol. 2 No. 3 (2025): July
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jtsi.v2i3.4859

Abstract

Traditional livestock management often suffers from inefficient tracking, limited real-time data, and minimal automation, leading to reduced productivity and sustainability issues. This paper introduces Smart Farm Tagging with Basic, Pro, and Advanced versions, a smart livestock monitoring system that integrates Artificial Intelligence (AI), Internet of Things (IoT), Near Field Communication (NFC), barcode technologies, and Global Positioning System (GPS). The system enables real-time tracking and monitoring of key parameters such as species type, gender, health status, body weight, and production output. Initial field data include cattle profiles labeled by health status (“Healthy”), gender (“Female” or “Male”), and weight, with birth date validation ongoing. Furthermore, the AI-powered dashboard integrates operational logs with external weather inputs such as temperature, humidity, and light rain conditions recorded in Sayan, Bali, to predict livestock health trends and recommend timely interventions. Statistical models analyze historical and real-time data to detect diseases, optimize breeding schedules, and enhance resource allocation. By integrating AI, IoT, NFC, and barcode technologies, Smart Farm Tagging presents a scalable, cost-effective, and efficient solution for modern smart farming systems.
Co-Authors Amertha, I Kumara, I Pioni, Ni Putra, I Setiawan, Feri