Pengembangan Dashboard Berbasis Web Untuk Pemantauan Emisi Kapal Secara Real-Time Menggunakan Grafana dan Kerangka IoT
Keywords:
Dashboard, Emisi Kapal, Grafana, IoT, Node-REDAbstract
Penelitian ini menyajikan perancangan dan implementasi dashboard pemantauan berbasis web untuk sistem emisi kapal yang dikembangkan dengan kerangka kerja Internet of Things (IoT). Dashboard dibangun menggunakan Grafana yang terhubung ke database time-series InfluxDB dan diintegrasikan melalui Node-RED sebagai jalur pengelolaan data. Fungsi utamanya adalah menampilkan parameter gas buang CO₂, CO, NO₂, SO₂, dan O₂ yang diterima dari sensor IoT secara real-time. Dashboard menyediakan grafik dinamis, indikator gauge, serta sistem peringatan berbasis warna untuk membantu pengguna memantau perubahan emisi secara langsung. Hasil pengujian menunjukkan bahwa dashboard mampu menampilkan data dengan waktu tunda rata-rata 1,8 detik, tingkat kehilangan paket di bawah 0,1%, dan uptime mencapai 99,5% selama 24 jam operasi berkelanjutan. Antarmuka pengguna dirancang responsif dan dapat diakses melalui berbagai perangkat secara daring. Implementasi ini menunjukkan bahwa dashboard Grafana berbasis open-source yang terintegrasi dengan Node-RED dan InfluxDB memberikan solusi efisien, andal, dan berbiaya rendah untuk visualisasi data emisi kapal secara real-time, serta mendukung kegiatan pemantauan lingkungan dan riset kemaritiman
References
[1] D. Kramel et al., “Global Shipping Emissions from a Well-to-Wake Perspective: The MariTEAM Model,” Environ. Sci. Technol., vol. 55, no. 22, pp. 15040–15050, 2021, doi: 10.1021/acs.est.1c03937.
[2] L. Fan, H. Yang, and X. Zhang, “Targeting the Effectiveness Assessment of the Emission Control Policies on the Shipping Industry,” Sustain. , vol. 16, no. 6, 2024, doi: 10.3390/su16062465.
[3] J. G. K. and A. U. U. Abdulrasheed O. Abdulganiyu, “Development Of An Internet Of Things Based Air Quality Monitoring System Using Machine Learning,” pp. 276–282, 2023.
[4] A. S. P. Pamula, A. Ravilla, and S. V. H. Madiraju, “Applications of the Internet of Things (IoT) in Real-Time Monitoring of Contaminants in the Air, Water, and Soil †,” Eng. Proc., vol. 27, no. 1, 2022, doi: 10.3390/ecsa-9-13335.
[5] M. C. Radha, M. M. Madheswaran, M. M. Lokesh, and M. M. M. Althaf, “Environmental Monitoring in Internet of Things (IOT),” Int. J. Res. Appl. Sci. Eng. Technol., vol. 12, no. 4, pp. 1658–1663, 2024, doi: 10.22214/ijraset.2024.60086.
[6] C. D’ortona, D. Tarchi, and C. Raffaelli, “Open-Source MQTT-Based End-to-End IoT System for Smart City Scenarios,” Futur. Internet, vol. 14, no. 2, 2022, doi: 10.3390/fi14020057.
[7] F. Zhou, J. Liu, H. Zhu, X. Yang, and Y. Fan, “A Real-Time Measurement-Modeling System for Ship Air Pollution Emission Factors,” J. Mar. Sci. Eng., vol. 10, no. 6, 2022, doi: 10.3390/jmse10060760.
[8] C. Bachechi, L. Po, and F. Rollo, “Big Data Analytics and Visualization in Traffic Monitoring,” Big Data Res., vol. 27, p. 100292, 2022, doi: 10.1016/j.bdr.2021.100292.
[9] P. Moens et al., “Scalable fleet monitoring and visualization for smart machine maintenance and industrial iot applications,” Sensors (Switzerland), vol. 20, no. 15, pp. 1–15, 2020, doi: 10.3390/s20154308.
[10] O. E. Guijarro-Rubio, D. R. Vinocunga-Pillajo, O. Del Real-Fleites, E. Guardado-Yordi, and A. Pérez-Martínez, “Monitoring of environmental variables in greenhouse crops through an IoT wireless sensor network,” DYNA, vol. 92, no. 235, pp. 47–56, 2025, doi: 10.15446/dyna.v92n235.115402.
[11] T. Domínguez-Bolaño, V. Barral, C. J. Escudero, and J. A. García-Naya, “An IoT system for a smart campus: Challenges and solutions illustrated over several real-world use cases,” Internet of Things (Netherlands), vol. 25, no. January, p. 101099, 2024, doi: 10.1016/j.iot.2024.101099.
[12] M. Guerbaoui et al., “From Data to Decisions: A Smart IoT and Cloud Approach to Environmental Monitoring,” E3S Web Conf., vol. 601, pp. 1–13, 2025, doi: 10.1051/e3sconf/202560100008.
[13] M. A. A. Radia, M. K. E. Nimr, and A. S. Atlam, “IoT-based wireless data acquisition and control system for photovoltaic module performance analysis,” e-Prime - Adv. Electr. Eng. Electron. Energy, vol. 6, no. August, p. 100348, 2023, doi: 10.1016/j.prime.2023.100348.
[14] A. Mehdi, M. K. Bali, S. I. Abbas, and M. Singh, “‘Unleashing the Potential of Grafana: A Comprehensive Study on Real-Time Monitoring and Visualization,’” 2023 14th Int. Conf. Comput. Commun. Netw. Technol. ICCCNT 2023, 2023, doi: 10.1109/ICCCNT56998.2023.10306699.
[15] J. Zhao and T. Tong, “A Ship Exhaust Gas Monitoring Equipment based on NBIoT,” Front. Sci. Eng., vol. 2, no. 11, pp. 7–17, 2022, doi: 10.54691/fse.v2i11.2971.
[16] S. A. Bagal, N. K. Choudhari, and A. R. Chaudhari, “Development of Internet of Things (IoT) Based Monitoring of Hazardous Exhaust Compounds in Air - A Review,” ITM Web Conf., vol. 50, p. 01002, 2022, doi: 10.1051/itmconf/20225001002.
[17] I. Nur Fajar and S. Prayogi, “Monitoring CO2 and SO2 Exhaust Gas Emissions on Tanker Ships With An IoT Based PLC Controller,” J. Emerg. Supply Chain. Clean Energy, Process Eng., vol. 3, no. 1, pp. 31–36, 2024, doi: 10.57102/jescee.v3i1.80.
[18] A. U. Khan, M. E. Khan, M. Hasan, W. Zakri, W. Alhazmi, and T. Islam, “An Efficient Wireless Sensor Network Based on the ESP-MESH Protocol for Indoor and Outdoor Air Quality Monitoring,” Sustain., vol. 14, no. 24, 2022, doi: 10.3390/su142416630.
[19] S. Banerjee, P. Kumari, and T. Maity, “Development of MQTT Protocol-Based Sensor Data Subscription Using Raspberry-Pi as a Server Mode for IIoT Application,” 2024 IEEE Int. Conf. Smart Power Control Renew. Energy, ICSPCRE 2024, pp. 1–5, 2024, doi: 10.1109/ICSPCRE62303.2024.10675281.
[20] B. Mishra and A. Kertesz, “The use of MQTT in M2M and IoT systems: A survey,” IEEE Access, vol. 8, pp. 201071–201086, 2020, doi: 10.1109/ACCESS.2020.3035849.
[21] N. N. Kumar and M. P. Panchal, “Building a Secure IoT Platform for Smart Home Automation: A Comprehensive Integration,” Int. J. Res. Appl. Sci. Eng. Technol., vol. 12, no. 1, pp. 302–309, 2024, doi: 10.22214/ijraset.2024.57917.
[22] G. S and Sowmya, “Real Time Environmental Time Series Data Analysis Using Influx DB,” Int. J. Adv. Sci. Inov., vol. 01, no. 01, pp. 1–5, 2020, doi: 10.5281/zenodo.4641703.
[23] M. Mayer, A. Mohapatra, and V. S. Peric, “IoT Integration for Combined Energy Systems at the CoSES Laboratory,” 7th IEEE World Forum Internet Things, WF-IoT 2021, pp. 195–200, 2021, doi: 10.1109/WF-IoT51360.2021.9596000.
[24] M. W. Jones et al., “National contributions to climate change due to historical emissions of carbon dioxide, methane, and nitrous oxide since 1850,” Sci. Data, vol. 10, no. 1, pp. 1–23, 2023, doi: 10.1038/s41597-023-02041-1.
[25] A. A. Rahmadani, Y. W. Syaifudin, B. Setiawan, Y. Y. F. Panduman, and N. Funabiki, “Enhancing Campus Environment: Real-Time Air Quality Monitoring Through IoT and Web Technologies,” J. Sens. Actuator Networks, vol. 14, no. 1, pp. 1–26, 2025, doi: 10.3390/jsan14010002.
[26] M. N. A. Ramadan, M. A. H. Ali, S. Y. Khoo, M. Alkhedher, and M. Alherbawi, “Real-time IoT-powered AI system for monitoring and forecasting of air pollution in industrial environment,” Ecotoxicol. Environ. Saf., vol. 283, no. August, p. 116856, 2024, doi: 10.1016/j.ecoenv.2024.116856.
[27] J. Mostafa, S. Wehbi, S. Chilingaryan, and A. Kopmann, SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things, vol. 1, no. 1. Association for Computing Machinery, 2022. doi: 10.1145/3538712.3538723.
[28] B. Shah, P. M. Jat, and K. Sasidhar, “Performance Study of Time Series Databases,” Int. J. Database Manag. Syst., vol. 14, no. 5, pp. 1–13, 2022, doi: 10.5121/ijdms.2022.14501.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
