Low-Cost LoRa-Based System for Continuous GHGs Monitoring in Cattle: Enhancing Agricultural Sustainability
Rising concern over livestock emissions and their contribution to climate change demands innovative and cost-effective monitoring solutions. This study introduces and validates a low-cost, LoRa based system for the continuous monitoring of methane (CH4) and carbon dioxide (CO2) emissions in cattle....
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Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10848069/ |
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Summary: | Rising concern over livestock emissions and their contribution to climate change demands innovative and cost-effective monitoring solutions. This study introduces and validates a low-cost, LoRa based system for the continuous monitoring of methane (CH4) and carbon dioxide (CO2) emissions in cattle. Unlike previous fixed installation systems, our design features a movable cattle collar equipped with gas sensors, enabling real-time data collection directly from the emission source. The system combines advanced sensor technology with long-range LoRa communication, thereby providing a scalable solution for remote agricultural environments. The experimental results demonstrate that the cattle collar system achieves higher accuracy in detecting CO2 emissions owing to its proximity to the emission source, outperforming fixed systems. The closed feeding slot design showed a comparable accuracy for CH4 detection. Both systems proved capable of reliable data transmission over distances of up to 400 m, making them ideal for large-scale deployments. In terms of cost, our system is significantly more affordable than other commercially available systems. The collar’s portability, low power consumption, and long battery life make it well-suited for continuous monitoring in both indoor and outdoor settings. This study highlights the potential of a movable, low-cost solution for monitoring livestock emissions, contributing to agricultural sustainability and climate change mitigation by providing accurate, real-time data for effective emission management strategies. |
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ISSN: | 2169-3536 |