Tujuan dari penelitian ini adalah untuk mengantisipasi terjadinya kebakaran yang sangat besar dengan memantau kondisi panel listrik yang ada di kapal. Penelitian ini menggunakan kontrol listrik miniatur berukuran tinggi 35,5 cm, panjang 27cm dan lebar 9. Perancangan fire detector panel listrik berbasis mikrokontroler tipe 328 digunakan untuk memonitor keberadaan benda api dan suhu yang melebihi batas maksimal dengan menggunakan sensor suhu DHT22 dan sensor nyala api yang ada pada panel listrik di kapal. Hasil pembacaan sensor akan diproses menggunakan mikrokontroler Atmega 328 yang ditampilkan dalam aplikasi IDE, dalam bentuk data deteksi kebakaran, pembacaan suhu dan kondisi pada panel. Ketika sensor mendeteksi api dan suhu melebihi batas buzzer maksimum dan LED akan menyala untuk menginformasikan alarm dan ketika sensor sensor tidak mendeteksi objek kebakaran atau suhu melebihi batas, buzzer dan LED akan mati.
Water quality is an important factor in supporting the success of vanname shrimp farming. The automatic water quality monitoring system is designed using two hardware, namely the DS18B290 temperature sensor to measure water temperature, the E-201 BNC pH meter kit sensor to measure water pH, and the TDS meter sensor. gravity Dfrobot to measure the salinity of the water, and the RED Turbidity MJKDZ sensor to measure the turbidity of the water, as the data sending hardware (transmitter). Arduino Mega2560 microcontroller, NodeMCU esp8266 as receiver and data processing hardware (reciver). The automatic water quality monitoring system is also designed using three software, namely Arduino IDE software as the main hardware program, ThingSpeak software as a database and MIT APP Inventor software as application development software. The test results for the level of accuracy and error of sensor measurements on water quality monitoring tools show that the sensor has a very good percentage of performance with the temperature sensor accuracy reaching 98.67%, the sensor reaching pH 99.35%, the salinity sensor reaching 99.28%. Meanwhile, the temperature sensor measurement error rate is only 1.32%, the pH sensor is only 0.64% and the salinity sensor is only 0.71%.
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