Open AccessPhotogrammetry using Intelligent-Battery UAV in Different Weather for Volcano Early Warning System Application
Author(s) -
Maria Evita,
Azka Zakiyyatuddin,
W. Srigutomo,
Nina Siti Aminah,
Irwan Meilano,
Mitra Djamal
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1772/1/012017
Subject(s) - orthophoto , real time computing , flight plan , remote sensing , warning system , computer science , volcano , photogrammetry , software , meteorology , artificial intelligence , telecommunications , geology , geography , seismology , programming language
We have developed a new volcano early warning system based on sensor node, internet of things (IoT) and UAV to overcome some problems in Indonesian volcano monitoring system. Data (monitored by sensor node) transmission and communication is managed by the IoT while UAV is used for remote sensing data to complete the system to predict the geological status of the volcano. An intelligent-battery UAV is needed for this purpose which manage the power utilization for field application. First stage of the remote sensing process is volcano region mapping for constructing an orthophoto before it is combined with field sensor data. Therefore, we have conducted a laboratory experiment to map some region in ITB, Bandung in different weather as real volcano condition. We have constructed day, night, sunny and cloudy maps of ITB after some data collected through flight and control plan as real volcano environment. Some grid flight plans were chosen for expected result as well as battery saving for each 5 meters data collection. A 3D software has been used for modelling of the orthophoto construction and resulted in 0 – 8 meters error of 20000 – 24000 m 2 monitored area. Therefore, this method could be used in real volcano application.