Proceedings of the 11th International Applied Business and Engineering Conference, ABEC 2023, September 21st, 2023, Bengkalis, Riau, Indonesia

Research Article

Characterizing a NodeMCU-based MAC Address Detector for Enhanced Coastal Tourism Management System

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  • @INPROCEEDINGS{10.4108/eai.21-9-2023.2342975,
        author={Yoanda Alim Syahbana and Rufina  Pramudita},
        title={Characterizing a NodeMCU-based MAC Address Detector for Enhanced Coastal Tourism Management System},
        proceedings={Proceedings of the 11th International Applied Business and Engineering Conference, ABEC 2023, September 21st, 2023, Bengkalis, Riau, Indonesia},
        publisher={EAI},
        proceedings_a={ABEC},
        year={2024},
        month={2},
        keywords={internet of things nodemcu mac address coastal tourism management system},
        doi={10.4108/eai.21-9-2023.2342975}
    }
    
  • Yoanda Alim Syahbana
    Rufina Pramudita
    Year: 2024
    Characterizing a NodeMCU-based MAC Address Detector for Enhanced Coastal Tourism Management System
    ABEC
    EAI
    DOI: 10.4108/eai.21-9-2023.2342975
Yoanda Alim Syahbana1,*, Rufina Pramudita1
  • 1: Politeknik Caltex Riau
*Contact email: yoanda@pcr.ac.id

Abstract

The coastal tourism management system plays a crucial role in ensuring sustainable tourism activities and integrates various elements and stakeholders of tourism. In this research, the NodeMCU is used to prototype an IoT product, MAC Address Detector. It is aimed to effectively address the issue of overcrowding in coastal tourism management systems. The proposed solution uses NodeMCU, which comes pre-equipped with a WiFi chip functioning as a sensor. The monitoring concept revolves around identifying active MAC addresses derived from smartphones or tablets used by visitors. The characterization covers experiments on detection distance, device brand, Operating System (OS), and active connection type. Results from the experiment show that device connection, OS, and distance are the most critical factors in implementing the solution. Excluding the characterizing result from airplane mode connection type, iPhone device with iOS, and GPS connection type, the proposed idea achieves a 98.36% success rate in detecting nearby MAC addresses for all distance variation. Based on this result, the implementation of NodeMCU as a sensor to detect overcrowding in coastal tourism is possible to be implemented. In the future, it will be challenging to continue the research for multiple detectors across a broad coastal area to evaluate their coverage, accuracy, response time, and energy consumption performance.