IoT-Enabled Livestock Health Monitoring Systems to Improve Efficiency and Reduce Mortality

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.

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Publication Details

Journal
SHS Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/shsconf/202521601035
Primary Topic
Food Supply Chain Traceability
Type
article
Field-Weighted Citation Impact
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article

IoT-Enabled Livestock Health Monitoring Systems to Improve Efficiency and Reduce Mortality

P. Gopala Krishna, Ammar Hameed Shnain, S. Abdul Ameer
SHS Web of Conferences
Food Supply Chain Traceability
article

IoT-Enabled Livestock Health Monitoring Systems to Improve Efficiency and Reduce Mortality

P. Gopala Krishna, Ammar Hameed Shnain, S. Abdul Ameer
article en

Abstract

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.

SHS Web of ConferencesVol. 216
Ahl Al Bayt University (IQ), Iraqi University (IQ)
Openalex Percentile: Top 87%
Food Supply Chain Traceability
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