Issue |
SHS Web Conf.
Volume 216, 2025
International Conference on the Impact of Artificial Intelligence on Traditional Economic Sectors (ICIAITES 2025)
|
|
---|---|---|
Article Number | 01035 | |
Number of page(s) | 10 | |
Section | Intelligent Systems and Digital Transformation in Agricultural Economy and Sustainable Development | |
DOI | https://doi.org/10.1051/shsconf/202521601035 | |
Published online | 23 May 2025 |
IoT-Enabled Livestock Health Monitoring Systems to Improve Efficiency and Reduce Mortality
1
Department of computers Techniques engineering, College of technical engineering, The Islamic University of Najaf, Iraq The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq The Islamic University of Babylon,
Babylon, Iraq
2
Ahl Al Bayt University,
Karbala, Iraq
3
Department of Civil, GRIET,
Hyderabad, Telangana, India
* Corresponding author: ammar.hameed.it@gmail.com
In terms of livestock monitoring systems, IoT is used to monitor the health metrics such as heart rate and temperature in real time. However, it is this same data that now provides critical data for early detection of health problem, thus enabling timely interventions and optimal practices in the management. Continuous health parameter monitoring and analysis of these health parameters have been improved considerably which resulted in the mortality rates, animal welfare and operational efficiency improved considerably. Real time data collection and processing is done by the IoT enabled livestock health monitoring system by means of heart rate and temperature sensors together with a Raspberry Pi. With a GSM/GPS module integrated with Raspberry Pi, which was connected to a GPIO, it can send data using an ESP8266 module for tracking location and cellular access. Powered by a reliable input source, the system runs constantly and sends data to the cloud where it is monitored remotely at any time through a web interface. If parameters deviate from normal ranges, real time alerts are generated to notify suitable authorities for timely health intervention and improve their livestock management. Results of simulation show a power consumption of about 5 Watts for reliable operation and constant monitoring. Accurate GPS tracking data represent livestock's spatial distribution that serves as a basis for conducting targeted health checks and ensuring optimal use of resources. The system overall improves livestock management through constant delivery of the real time health insights, enabling timely responses and by allowing stable power operation, thus saving operations costs.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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