Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Informatik : Jurnal Ilmu Komputer
M Wahyu Firmansyah
Politeknik Manufaktur Bandung
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Implementation Of Kalman Filter at IoT Animal Weighing Nuryanti; Danu Jaya Saputro; Ismail Rokhim; Hendy Rudiansyah; Sandy Bhawana Mulia; Wahyu Adhie Candra; M Wahyu Firmansyah
Informatik : Jurnal Ilmu Komputer Vol 22 No 2 (2026): August 2026
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v22i2.13604

Abstract

Animal weighing is an important aspect of livestock farming, as it plays a role in feed determination, growth monitoring, and economic evaluation. However, accuracy is often compromised by animal movement, which causes fluctuations in sensor data and unstable readings, making it difficult to determine the actual weight. To address this, this study proposes an IoT-based animal weighing system equipped with a Kalman Filter algorithm to reduce noise and improve measurement stability. The system utilizes four 200 kg load cells, connected via HX711 and controlled by an ESP32 microcontroller, which is supported by an RFID module for automatic animal identification, an RTC for time logging, and Firebase as a cloud storage platform with real-time visualization capabilities through Node-RED. Experimental for moving object weighing results show that the Kalman Filter reduces measurement errors to less than 2% and maintains the coefficient of variation below 2%, demonstrating high precision and stability. Therefore, this system is proven effective for automatic, accurate, and remote-accessible animal weight monitoring, with strong potential for implementation in modern livestock industries.
Co-Authors Danu Jaya Saputro Hendy Rudiansyah Ismail Rokhim Nuryanti Sandy Bhawana Mulia Wahyu Adhie Candra