Advanced Sensors Network Design for Real-Time Livestock Watering Point Monitoring

Efficient management of water resources is essential for sustainable livestock farming. Contamination of water sources by pathogens, chemicals or sediments can lead to serious health problems in livestock and affect growth rates, reproduction and milk production, impacting on economic results. Recently, innovative technologies such as the Internet of Things and cloud computing have improved water management and monitoring in various agricultural contexts. However, most proposed solutions often face limitations in real-time data processing and latency issues, particularly in remote agricultural areas with limited internet connectivity. These challenges hinder immediate response times and accurate realtime monitoring essential for livestock watering point management.In this paper, we propose an innovative and advanced sensor network design leveraging Internet of Things (IoT), Edge-AI technologies to enhance real-time data collection and processing at remote watering points. By reducing latency and improving reliability, the proposed architecture aims to overcome traditional aims to overcome current limitations in traditional approaches. The system integrates advanced sensor/biosensors technologies with local processing capabilities to achieve timely detection and response to water availability and quality issues. We demonstrate the validity of our proposal using the MATLAB simulator, and the results show that the system is scalable, robust and reliable.