Claim Missing Document
Check
Articles

Found 1 Documents
Search

Optimalisasi Kontrol Lingkungan Kandang Ayam Tertutup Menggunakan Sensor DHT22 dan MQ135 dengan Analisis Ambang Batas Adaptif Setyawan, Galih; Attaqi, Muhammad Ilham
Jurnal Ilmiah Teknologi dan Rekayasa Vol 30, No 2 (2025)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2025.v30i2.13947

Abstract

This study develops an automatic system to manage the closed poultry house environment, focusing on temperature control and ammonia mitigation, for improved animal health and productivity. Conventional static threshold-based systems often lack efficiency and are prone to excessive actuator activations. The proposed innovation utilizes a DHT22 temperature sensor and an MQ135 gas sensor, selected for their accuracy and responsiveness in monitoring critical parameters. The system integrates with an Arduino Uno, an AC Dimmer module for fan speed control, and a water spraying pump. Fan speed regulation is adjusted based on temperature using a three-level logic: slow mode (30^oC). Meanwhile, the activation of the water spraying pump for ammonia mitigation is controlled by a static threshold of ≥550 ppm. In-depth analysis of MQ135 sensor data from three ammonia testing experiments reveals significant potential for implementing more adaptive pump activation thresholds, specifically using the moving average method. Comparison between the existing static threshold-based control system and this adaptive scenario consistently demonstrates that applying an adaptive threshold can significantly reduce pump activation frequency, by an average of 50% to 60% (from 6-7 activations to 3 activations per experiment). This reduction indicates great potential for mitigating pump chattering, optimizing energy consumption, and extending the operational lifespan of actuators. These results confirm that the developed system effectively operates in maintaining poultry house environmental conditions, while also paving the way for smarter and more adaptive control in the future that can enhance farm operational efficiency.