Perancangan dan Analisis Kinerja Sistem Gateway IoT Berbasis RS485 Menggunakan ESP32 untuk Monitoring Intensitas Cahaya secara Real-Time
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Perkembangan Internet of Things (IoT) mendorong penerapan sistem monitoring real-time pada berbagai sektor industri. Penelitian ini bertujuan merancang sistem monitoring intensitas cahaya berbasis IoT dengan komunikasi RS485 menggunakan protokol Modbus RTU serta integrasi MQTT. Sistem menggunakan ESP32 sebagai gateway yang menghubungkan sensor BH1750 dengan platform monitoring. Metode meliputi perancangan perangkat keras, pengembangan perangkat lunak berbasis FreeRTOS, dan pengujian dengan interval satu menit. Evaluasi dilakukan menggunakan Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), rata-rata delay, dan Packet Delivery Ratio (PDR). Hasil menunjukkan sistem mampu bekerja secara real-time dengan akurasi yang baik, ditunjukkan oleh nilai MAE dan MAPE yang rendah. Selain itu, rata-rata delay sekitar 120 ms dan nilai PDR 100% menunjukkan komunikasi data berjalan stabil. Sistem ini memenuhi aspek akurasi, responsivitas, dan keandalan, sehingga berpotensi diterapkan pada monitoring industri skala kecil hingga menengah.
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[1] C. M. Nkinyam, C. Oliver, C. O. Asadu, B. Anyaka, and P. A. Olubambi, “Results in Engineering Development of a low-cost monitoring device for solar electric ( PV ) system using internet of things ( IoT ),” Results Eng., vol. 28, no. September, p. 107324, 2025, doi: 10.1016/j.rineng.2025.107324.
[2] H. Andrianto and V. Jonathan, “Design of IoT-Based Electrical Energy Meter,” 2023 IEEE 9th Int. Conf. Comput. Eng. Des., pp. 1–4, 2023, doi: 10.1109/ICCED60214.2023.10425406.
[3] A. Baratta et al., “ScienceDirect Design and Implementation of Modular IoT Solutions for Environmental Monitoring and Smart Automation : Three Case Studies in the Dominican Republic , Panama , and Italy,” Procedia Comput. Sci., vol. 274, pp. 1140–1148, 2025, doi: 10.1016/j.procs.2025.12.111.
[4] F. Moghaddam, “PLC-Based Remote Monitoring and Automation for Energy Applications,” 2025 7th Exp. Int. Conf., pp. 378–383, 2025, doi: 10.1109/exp.at2565440.2025.11348353.
[5] A. Abu and A. A. A. Shabaneh, “MethodsX Design of a smart hydroponics monitoring system using an ESP32 microcontroller and the Internet of Things,” MethodsX, vol. 11, no. September, p. 102401, 2023, doi: 10.1016/j.mex.2023.102401.
[6] M. Dafare, “LoRa-Enabled Smart RS485 Data Logger and MQTT Gateway for Industrial IoT Applications using ESP32,” 2023 Int. Conf. Circuit Power Comput. Technol., pp. 1297–1302, 2023, doi: 10.1109/ICCPCT58313.2023.10245760.
[7] Z. Naufal, “Machine Learning Models Performance for NPK Soil Sensor Calibration,” 2025 Int. Conf. ICT Smart Soc., no. 2020, pp. 1–6, 2025, doi: 10.1109/ICISS66954.2025.11389538.
[8] C. Revelivan, H. Wiratama, and N. Hanafiah, “ScienceDirect ScienceDirect Door Security System for Home Monitoring Based on ESP32,” Procedia Comput. Sci., vol. 157, pp. 673–682, 2019, doi: 10.1016/j.procs.2019.08.218.
[9] S. P. S. J, C. M. Iniyan, E. M. Barath, G. M. Thangatamilan, R. Gayathri, and M. Apoorva, “Tank Level Control Using Lora and PLC,” 2025 Second Int. Conf. Intell. Technol. Sustain. Electr. Commun. Syst. (iTech SECOM), no. 2009, pp. 1–6, 2025, doi: 10.1109/iTechSECOM64750.2025.11307668.
[10] N. Biswas, M. A. Mahdi, and M. Das Gupta, “Electricity Demand Forecasting for Tetouan, Morocco using Darts in Machine‑Learning: A Comparative Study of Forecasting Models,” Results Eng., p. 110289, 2026, doi: 10.1016/j.rineng.2026.110289.
[11] E. Bebronne and S. Limbourg, “Logistics 5.0 for Public Lighting Systems: Research Agenda,” IFAC Pap., vol. 59, no. 10, pp. 823–828, 2025, doi: 10.1016/j.ifacol.2025.09.140.
[12] Z. Wu, “On-Chip ESD Protection for A / B Bus Ports of RS485 Using Asymmetrical dual-direction Silicon Controlled Rectifier,” 2025 4th Int. Symp. Semicond. Electron. Technol., pp. 148–153, 2025, doi: 10.1109/ISSET66828.2025.11184970.
[13] A. C. Study, “Hybrid Traditional and Deep Learning Approaches for Network Traffic Forecasting with Real-Time Anomaly Detection,” no. May, 2025.
[14] A. Hossain, Z. Harun, T. M. T. Lei, and M. Kumar, “Computers & Industrial Engineering Development , optimization , and benchmarking of zone-specific deep learning architectures for air quality prediction in end-of-life vehicle recycling zones,” Comput. Ind. Eng., vol. 210, no. August, p. 111507, 2025, doi: 10.1016/j.cie.2025.111507.
[15] J. P. Lujan-leon, R. A. Alvarado-lugo, P. W. Lovon-ramos, and C. Benites-condori, “Datalogger for Low-Cost High Mountain Weather Stations : Design , Optimization and Testing of Power Consumption and Compatibility with Satellite Transmitter,” 2023 IEEE XXX Int. Conf. Electron. Electr. Eng. Comput., pp. 1–8, doi: 10.1109/INTERCON59652.2023.10326074.
[16] S. Thakur, “AI-Driven Energy-Efficient Routing in IoT-Based Wireless Sensor Networks : A Comprehensive Review,” 2025.