Sistem Monitoring Kebisingan Pada Pabrik Beton Berbasis Website - Muhammad Daffi Rizqirobbi; Nabila Nasya Hasanah; Shita Fitria Nurjihan; Toto Supriyanto; Azkia Al Fataya Maulana; Yenniwarti Rafsyam (Spektral, 2026)
Noise levels in industrial environments such as concrete factories often exceed the safe threshold of 85 dB, posing risks to workers’ health and safety. Conventional monitoring methods remain manual and periodic, making them ineffective in providing real-time alerts. This study proposes an automated noise monitoring system based on the Internet of Things (IoT) using an INMP441 sound sensor and ESP32 microcontroller, which transmits data to a server via the MQTT protocol. Noise level data is displayed in real-time through a web interface, and alerts are triggered when the noise exceeds the safe threshold, utilizing DFPlayer Mini, a speaker, and a MAX7219 dot matrix display. Testing was conducted in two factory areas with measurement distances ranging from 1 to 5 meters. The system successfully displayed real-time conditions, such as the message "SAFE AREA" and "NOISE: 78 dB". Network performance testing using Wireshark showed stable results with an average throughput of 745.6 Kbps, latency of 6.821 ms, and 0% packet loss. DDoS attack simulations with up to 500 threads demonstrated that the website remained functional with only 60% CPU usage. The system is proven to be effective for real-time industrial noise monitoring.