Photogrammetry using Intelligent-Battery UAV in Different Weather for Volcano Early Warning System Application

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 m² monitored area. Therefore, this method could be used in real volcano application.