Abstract

Storm is defined as a disturbance of the atmosphere marked by winds and usually by rain. Coastal storms must comprise a maritime component, such as waves, currents and/or water levels. Coastal storm detection is necessary so the number of casualties and losses caused by these events can be reduced. The method used in this system is the Sugianto wave forecasting method with standardization of coastal storms using the Beaufort scale. The purpose of this study is to built up an internet of things based system to observe coastal storm information and wave forecasting data from wind speed data that obtained in Timbulsloko, Demak, Central Java, Indonesia. The tidal data is processed using the Admiralty method. This system was built using Arduino Uno equipped with anemometer JL-FS2 to measure wind and waves parameters. The power source from 100 wp solar panels stored in a 40 Ah accumulator. Data from field instrument is stored to the IoT MAPID database using NodeMCU ESP8266. This system is placed in Timbulsloko, Demak. The results of field observation then validated using BMKG. This method could be applied in other location along the north coast of Java. The results of field observation showed an average wind speed 3.9848 m/s; significant wave height 0.4632 m; significant wave period 3.8641 s; wave energy 493.90 J/m2; wind energy 116.74 W/m2.

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