IoT-Driven Livestock Monitoring: Leveraging LoRaWAN for Behavior Analysis and Enhanced Farm Management

Khadijah Febriana, Rahul Thakur, Sudip Roy

2025

Abstract

Cattle play a crucial role in farming by providing essential resources such as milk, meat, leather, and labor, contributing significantly to both economic and social stability in rural areas of India. This work develops an energy-efficient IoT system based on LoRaWAN to monitor and analyze livestock behavior. The system employs an MPU6050 sensor and TTGO T-Beam microcontroller to capture livestock’s movement and positional data. This data is continuously transmitted via a mesh network, utilizing The Things Network and ThingSpeak for remote analytics. A neural network with two hidden layers and ReLU activation functions is trained with sparse categorical cross-entropy loss. Validation on a 20% subset of the training data demonstrates high accuracy in classifying complex animal behaviors. Classification results, including F1-scores, precision, and recall metrics, highlight the model’s strong capability in behavior differentiation. Overall, this system enhances animal health and welfare, improves farm productivity, promotes environmental sustainability, and strengthens India’s food security.

Paper Citation

in Harvard Style

Febriana K., Thakur R. and Roy S. (2025). IoT-Driven Livestock Monitoring: Leveraging LoRaWAN for Behavior Analysis and Enhanced Farm Management. In Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS; ISBN 978-989-758-750-4, SciTePress, pages 273-280. DOI: 10.5220/0013296600003944

in Bibtex Style

@conference{iotbds25,
author={Khadijah Febriana and Rahul Thakur and Sudip Roy},
title={IoT-Driven Livestock Monitoring: Leveraging LoRaWAN for Behavior Analysis and Enhanced Farm Management},
booktitle={Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS},
year={2025},
pages={273-280},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013296600003944},
isbn={978-989-758-750-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS
TI - IoT-Driven Livestock Monitoring: Leveraging LoRaWAN for Behavior Analysis and Enhanced Farm Management
SN - 978-989-758-750-4
AU - Febriana K.
AU - Thakur R.
AU - Roy S.
PY - 2025
SP - 273
EP - 280
DO - 10.5220/0013296600003944
PB - SciTePress