| Issue |
E3S Web Conf.
Volume 658, 2025
Third International Conference of Applied Industrial Engineering: Intelligent Models and Data Engineering (CIIA 2025)
|
|
|---|---|---|
| Article Number | 03005 | |
| Number of page(s) | 12 | |
| Section | Intelligent Connectivity | |
| DOI | https://doi.org/10.1051/e3sconf/202565803005 | |
| Published online | 13 November 2025 | |
Impact on cattle welfare with IoT technology and statistical data analytics
1 Technological Business University of Guayaquil, Department of Innovation, Engagement and Sustainability, 090603 Guayaquil, Ecuador.
2 Technological Business University of Guayaquil, Faculty of Engineering, 090603 Guayaquil, Ecuador.
* Corresponding author: gviteri@uteg.edu.ec
The study analyzed the impact of implementing IoT technology combined with statistical analysis to improve the welfare of cattle on the Ecuadorian coast. A quasi-experimental methodology was adopted, validated in a controlled environment using computer simulation, in order to analyze the functionality of the system before its application in real conditions. To this end, five virtual devices were configured in Arduino Cloud to replicate the variables of heart rate, body temperature, and feeding patterns, generating data processed using Python and Django, with alerts sent via WhatsApp when values fell outside the permitted range. The results showed stability in temperature (37.9 °C average, minimum variance), consistency in feeding (mode = 1.0 in most observations), and slight variability in heart rate (79.8 BPM with a non-significant upward trend, p = 0.08). The analysis was performed using descriptive statistics (mean, median, mode, standard deviation) and mixed-effects models, the results of which were represented in box plots showing the homogeneity and variability among the simulated animals. In conclusion, the system demonstrated robustness and scalability for intelligent livestock monitoring, promoting more sustainable and technologically advanced livestock practices.
Key words: Internet of Things (IoT) / Real-time monitoring / Cattle welfare / Statistical data analysis / Python and Django
© 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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