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Monitoring the movement of boats in shallow waters requires a real-time monitoring system. However, for small-size wooden boats, they are still monitored manually, and data is unavailable in real time, which makes it difficult to effectively monitor them. The integration of IoT platforms with the boat monitoring system is a challenging task, especially in the transport system. This paper has the objective of developing an architectural model of a modified LoRaWAN-based boat monitoring system that is connected to a GPS-based mobile device and base station. The proposed architectural model is an integration of Bluetooth Low Energy (BLE) and LoRaWAN networks, which are also tested in real time to solve the boat traffic monitoring issues. The field tests with parameters of signal transmission, location coordinates, and position of the boats are also presented. The analysis result shows the proposed model is suitable for waters with high noise levels, especially in shallow water and delta rivers. The signal noise can be reduced by extracting the real-time data. In addition, signal interference can be minimized. The performance of this system is also compared to the reference system in real conditions, which shows an adequate correlation result. This proof of concept forms an important basis for deploying it for large-scale applications and commercialization capabilities. Doi: 10.28991/ESJ-2023-07-04-011 Full Text: PDF

Abstract This paper presented the implementation of Bluetooth low energy (BLE) devices implanted on 7 small wooden boats. The BLE implantation is aimed at boat identification and certification. We use four parameters to measure the performance of BLE signal strength, e.g., solar panel usage (with/without solar panel usage), weather effect (sunny/rain), sea wave form (shallow/tidal waters), and distance. The specification of BLE and boat identification system is also presented. From the experiment, we found that BLE signal strength performance is impacted by four parameters including its combined parameters: (a) the highest hour of the detected signal is generated when the boats are connected to the solar panel; (b) the boats transmitting the signal in sunny weather; (c) the boats are in shallow water sea wave; (d) the boats are in sunny weather and connected to solar panel will have a detectable distance for up to 30 m compared to without solar panel connection, it will only have a detectable distance for up to 15 m. It is suggested for future recommendations to expand this study with the newest BLE version and better solar panel equipment to get higher signal strength performance.