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All Journal bit-Tech Journal of Integrated Agribusiness Journal Automation Computer Information System (JACIS) Journal Computer Science and Informatic Systems : J-Cosys SIENNA Smart Techno (Smart Technology, Informatic and Technopreneurship) Pengabdian Kepada Masyarakat Cendekia
Gunanto, Sigit
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Journal : bit-Tech

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IoT-Based Automatic Traffic Light Prototype Using ESP32-CAM Antarina, Selvi; Gunanto, Sigit
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3698

Abstract

Traffic congestion at signalized intersections remains a persistent challenge due to the dominance of fixed-time traffic lights that cannot respond to short-term variations in vehicle demand. Although recent advances in computer vision and Internet of Things (IoT) technologies enable adaptive traffic control, many existing solutions depend on costly hardware platforms or simulation-based validation, limiting their applicability in resource-constrained contexts. This study proposes and evaluates a low-cost AIoT-based automatic traffic light prototype that integrates visual sensing, real-time vehicle detection, and adaptive signal control within an end-to-end operational framework. The system utilizes an ESP32-CAM as a vision sensor, a server-side You Only Look Once (YOLO) model for vehicle detection, and an ESP32 microcontroller for traffic light actuation, with communication implemented via WiFi using the HTTP protocol. Experimental validation is conducted under controlled prototype scenarios with traffic densities ranging from zero to three vehicles per lane to examine feasibility under hardware and network constraints. The results indicate reliable vehicle counting performance, achieving 100% accuracy for low to moderate densities and 93.3% accuracy at higher prototype density levels. Compared with a fixed-time strategy, the adaptive mechanism dynamically adjusts green light durations, reducing idle green time under low demand and increasing service time as vehicle density rises. The findings provide empirical insights into the feasibility and performance limits of low-cost vision-based adaptive traffic control systems.
IoT-Based Smart Aquaponics System with Firebase and Telegram Integration Wahyu Ardila, Asti; Gunanto, Sigit
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3754

Abstract

Aquaponic systems require stable environmental control to maintain the balance between fish and plant growth. This study proposes a novel Internet of Things (IoT)-based smart aquaponic system that integrates real-time monitoring, adaptive automatic control, and cloud-based data management within a unified sensor–edge–cloud architecture. The key innovation of this work lies in the seamless integration of the Firebase Realtime Database for low-latency synchronization, an interactive web-based dashboard for real-time visualization, and a hysteresis-based adaptive control mechanism that overcomes the limitations of conventional threshold-based systems, particularly rapid actuator switching (chattering). The system employs an ESP32 as the main processing unit, a DHT11 sensor for temperature and humidity measurement, and a TDS sensor for dissolved nutrient monitoring. Data are transmitted every 10 seconds to the cloud and complemented by event-driven Telegram notifications to enable timely user intervention. Experimental results demonstrate stable system performance, achieving a data transmission success rate of 98.47% over 24 hours. The temperature measurement shows a Mean Absolute Error (MAE) of 0.48°C (≈1.6% relative error), while an average latency of 1.4 seconds indicates responsive real-time synchronization. Furthermore, the implementation of hysteresis-based control effectively reduces actuator instability and enhances system reliability. These findings indicate that the proposed integrated architecture not only improves monitoring accuracy and control stability compared to existing IoT-based aquaponic systems, but also enables practical, remotely accessible, and scalable solutions. The system is particularly suitable for small- to medium-scale aquaponic applications, supporting data-driven decision-making and contributing to sustainable agriculture practices.
Co-Authors Adi Wibowo AGUSTINA, RENI Anjelina, Diah Ayu Antarina, Selvi Boby Arya Putra Dwi Putri, Pelita Fhela Vhantoria Ningrum Hartadi, Subagus M. Fauzi masfa, anes Muinah Nurmala, Intan Sari, Diani Wahyu Ardila, Asti Winalda, Tio