Pengiriman Data Surveillance Sensing Menggunakan Sistem Nirkabel Pada Frekuensi 433 MHz Untuk Kebakaran Hutan - Rizadi Sasmita Darwis; Hamid Azwar; Emansa Hasri Putra; Muhammad Saputra (Politeknik Caltex Riau, 2022)
The fires that hit Indonesia in 2015 are considered one of the biggest environmental disasters of the 21st century so far. The World Bank estimates that the 2015 fire crisis cost Indonesia US16 billion in forestry, agriculture, tourism and other industries. The smog causes respiratory and other illnesses in hundreds of thousands of people across the region. So far, efforts to mitigate forest and land fires have often been carried out by the government and the forest fire task force, starting from creating an early warning system, increasing community participation, and forest fire control techniques. However, all of these mitigation efforts are more dominantly carried out after forest and land fires have occurred. Whereas when a fire has occurred and the fire has grown bigger, fire mitigation efforts become more difficult and expensive because they have to involve helicopters to extinguish the fire from the air. So a land and fire mitigation effort requires one that is easy to use, fast and cheap to implement, and can reach a wider area than a forest area. The research aims to create a surveillance sensing system for forest fire for forest fire mitigation based on drone technology, and sensor technology. This research is an innovation and development of science and technology that is beneficial to the community, the forest fire task force and the local government. The research stages start from the design, manufacture, and design of a surveillance sensing system for forest fire in the Telecommunication Network laboratory. The output of this research is a prototype surveillance sensing system for forest fire. Test results within a certain time span indicate that the sensor is running well. All sensors used will show a change in value when a heat source and fire are detected. The average temperature sensor result is 72.34 C. While the dust particle sensor result is 665.45 g/m3 . And for air quality sensors the average is 0.225 ppm. For GPS sensor data it has 99.5% accuracy. which the Arduino reads before sending. The maximum delivery distance that can be used is 0-40 meters.