Intelligent Monitoring System for Broiler Chicken Houses Blower using Fuzzy Logic

Abstract

This research presents the design and implementation of an intelligent early warning system for monitoring blower performance in Closed House broiler farms. The system aims to reduce financial losses and mitigate livestock health risks caused by poor air circulation due to blower degradation or failure. It integrates multiple sensors, including anemometers for wind speed, MQ-135 for ammonia gas, and MQ-7 for carbon monoxide. Data are processed by an ESP32 microcontroller within a distributed architecture of two monitoring boxes connected via NRF24L01 wireless modules. A fuzzy logic algorithm enables multi-variable decision-making, allowing the system to activate backup blowers, trigger alarms, and send real-time notifications through Telegram. Experimental results confirm system reliability, with anemometer accuracy ranging from 85% to 92%, buzzer intensity reaching 92–115 dB, and stable wireless communication up to 91 meters. The fuzzy logic controller successfully classified environmental conditions and blower performance, generating tiered alerts (Warning 1, Warning 2, Emergency). The findings demonstrate that the proposed system provides a proactive and intelligent solution, offering greater adaptability than conventional threshold-based methods while supporting productivity and animal welfare in poultry farming.