IoT-Driven Smart Management in Broiler Farming: Simulation of Remote Sensing and Control Systems
Sandra Coello Suarez, V. Sanchez Padilla, Ronald Ponguillo-Intriago, Albert Espinal
TL;DR
This paper evaluates an IoT-driven approach to broiler management through a simulation of sensor networks, embedded hardware, and a gateway architecture that monitors temperature and feed, with cloud dashboards for real-time visualization. The authors demonstrate a low-cost, modular setup using Arduino, Raspberry Pi, and Ubidots to validate automated control logic, alerts, and data logging, aiming to guide stakeholders in sustainable, scalable poultry production. The study contributes a practical blueprint for integrating IoT into broiler operations and highlights considerations for deployment, data reliability, and training. The work holds practical relevance for improving productivity and resource use in tropical coastal farming, with alignment to UN SDGs on rural development and sustainable production.
Abstract
Parameter monitoring and control systems are crucial in the industry as they enable automation processes that improve productivity and resource optimization. These improvements also help to manage environmental factors and the complex interactions between multiple inputs and outputs required for production management. This paper proposes an automation system for broiler management based on a simulation scenario that involves sensor networks and embedded systems. The aim is to create a transmission network for monitoring and controlling broiler temperature and feeding using the Internet of Things (IoT), complemented by a dashboard and a cloud-based service database to track improvements in broiler management. We look forward this work will serve as a guide for stakeholders and entrepreneurs in the animal production industry, fostering sustainable development through simple and cost-effective automation solutions. The goal is for them to scale and integrate these recommendations into their existing operations, leading to more efficient decision-making at the management level.