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

No abstract

On September 2019, Directorate General of Sea Transportation, the government who in charge for the safe operation of ships in Indonesia, has introduced a new model of ship certification form. It is an electronic certificate that is used for traditional boat and fishing vessel of less than 7 gross tonnage. This electronic certificate is for the first time being applied to a ship in Indonesia. This marks a new era for ship certification in Indonesia. The conventional paper format of certification had been applied before it was changed to electronic certification. Indonesia is implementing electronic certificates on traditional vessels and fishing vessels of less than 7 gross tonnage due to several reasons. The first is the need for durable form material due to lifetime validation of certificates. The second due to problems related to misuse of previous type of conventional paper format certificates that caused difficulties in determining the number of this type of vessels in Indonesia.

The advancement of IoTand thedream of having transportation mode where there is no human presence on board comes true. We have proceedin to the stage where artificial intelligence (AI) technology brings efficiencies in almost all sectors. Maritime Autonomous Surface Ship (MASS) is available now and soon it is expected to be a marine mode of transportation that can sail all over the world. It may visit a place where there is so much difference in culture and custom with the place where it built. While there are several ships with difference of technology used,meet on the same layer of sea surface at the same time.The difficulties in interacting for those type of ships with different technology may exist. The worst condition is that collision accident may occur if one could not detect the presence of other. Present technology of radar detection is still having weakness of detecting small wooden boat. Especially during bad weather and rough seas. The nature of fishing boat fleet where mostly stay still in the middle of ocean during fishing period, might bring the risk of collision if they are not detected properly by the passing MASS. This paper is highlighting the risk of collision between these type of vessels, the options to prevent the risk of collision accidentthat can be implemented both for MASS and Small Traditional Wooden and Fishing Boatare proposed. There are several models that can be used to solve that problem with pros and cons of each option. At the end of the paper, it will be proposed the most effective and efficient method that can be used to prevent such accident.

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.