Abstract

The fishing industry plays a crucial role in the economy, especially for coastal communities. However, monitoring vessel routes and managing energy consumption are still largely manual and experience-based, leading to inefficient fuel usage and potential safety risks during offshore operations. This paper demonstrates the applicability of Internet of Things (IoT) technology in route tracking and energy management for fishing vessels. By utilizing the ESP32-C3 microcontroller combined with a GPS module and the Firebase platform, the project successfully builds a low-cost but highly effective monitoring system. Key highlights of the proposed system include: (1) highly accurate real-time vessel tracking; (2) continuous data updates to the cloud platform; (3) an intuitive and user-friendly web interface; (4) indirect reduction of fuel consumption through comprehensive route analysis; and (5) significant enhancements in the overall efficiency and safety of fishing operations. Future expansions of the system could integrate environmental sensors, weather forecasting APIs, and smart fisheries management networks to further augment its capabilities.

References

• Phi Van Lam, Tran Thi Lan, and Trinh Luong Mien. 2026. “Design and Implementation of an IoT-Enabled Automatic Token Counting Machine for Metro Systems”. Engineering, Technology & Applied Science Research 16 (2). Greece:34337-50. https://doi.org/10.48084/etasr.17737.
• Sureshkumar, M. S., R. Rahul, S. Joshika, and S. Suraj. 2024. “Internet-of-Things-Based Smart Home Energy Management System with Multi-Sensor Data Fusion”. Eng. Proc. 66 (1): 10.
• Phi Van Lam, Tran Thi Lan, and Nguyen Cong Bach. 2025. “Design and development of a smart parking management system on a smartphone platform”. Journal of Construction: 123-127.
• Jung, Sooyeob, Seongah Jeong, Jinkyu Kang, and Joonhyuk Kang. 2023. “Marine IoT Systems with Space-Air-Sea Integrated Networks: Hybrid LEO and UAV Edge Computing”. IEEE Internet of Things Journal 11 (5).
• Phi Van Lam, Tran Thi Lan, and Le Hung Lan. 2022. “Proposal of a Gain-scheduling method to control the twowheeled robot for walking assistance”. Science Journal of Transportation (SJT) 12: 125-135.
• Durlik, Irmina, Tymoteusz Miller, Danuta Cembrowska- Lech, Adrianna Krzemi´nska, Ewelina Złoczowska, and Aleksander Nowak. 2023. “Navigating the Sea of Data: A Comprehensive Review on Data Analysis in Maritime IoT Applications”. Applied Sciences 13 (17): 9742. https://doi.org/10.3390/app13179742.
• Phi Van Lam, Vu Duc Du, and Tran Thi Lan. 2026. “Real-time multi-object recognition and classification on resource-constrained devices for automated robots”. Journal of Measurement, Control and Automation 30 (2): xxx-yyy. https://doi.org/10.64032/mca.v30i2.420.
• Onay, A., G. Ertürk, C. Kıranlı, H. Ate¸s, and Y. E. Isikdemir. 2023. “A Smart Home Energy Monitoring System Based on Internet of Things and Inter Planetary File System for Secure Data Sharing”. Journal of Computer and Communications 11: 64-81.
• Phi Van Lam, and Tran Thi Lan. 2023. “Deep learning application to classification of products in electric car accessories production”. Transport Magazine, special number: 18-22.
• Liu, Shulei, Lijun Zhu, Fanghui Huang, Abual Hassan, Dawei Wang, and Yixin He. 2024. “A Survey on Airto- Sea Integrated Maritime Internet of Things: Enabling Technologies, Applications, and Future Challenges”. Journal of Marine Science and Engineering 12 (1): 11. https://doi.org/10.3390/jmse12010011.