Indriyanto, T.; Fathurrahman, A.; Rawikara, S.S.; Jenie, Y.I.; Arifianto, O.; Sasongko, R.A. Crash Risk Modelling and Analysis of Drone Operation inIndonesia’s Outermost and Underdeveloped Areas using Bayesian Network Approach. Preprints2023, 2023030019. https://doi.org/10.20944/preprints202303.0019.v1
APA Style
Indriyanto, T., Fathurrahman, A., Rawikara, S.S., Jenie, Y.I., Arifianto, O., & Sasongko, R.A. (2023). Crash Risk Modelling and Analysis of Drone Operation inIndonesia’s Outermost and Underdeveloped Areas using Bayesian Network Approach. Preprints. https://doi.org/10.20944/preprints202303.0019.v1
Chicago/Turabian Style
Indriyanto, T., Ony Arifianto and Rianto Adhy Sasongko. 2023 "Crash Risk Modelling and Analysis of Drone Operation inIndonesia’s Outermost and Underdeveloped Areas using Bayesian Network Approach" Preprints. https://doi.org/10.20944/preprints202303.0019.v1
Abstract
Limited accessibility in some parts of Indonesia causes difficulties in logistic distribution, especially for emergency and medical supplies. Emerging drone cargo technology is a potential solution to improve logistic distribution in those areas. However, implementing drone cargo technology involves unknown risks, both in technical and non-technical aspects. Since data on drone operations in Indonesia is limited, a new method is explored to build a Bayesian Network (BN) model for risk analysis of drone crashes in Indonesia’s outermost and underdeveloped areas. The method optimizes the modelling process, in which significant risk factors are selected based on three drone operator companies’ experiences, which include wind speed, rain intensity, and system component failure or malfunction. Real wind speed and rain probability data are then implemented in the model. The operator’s data shows that wind speed contributes to drone crashes, which can be appropriately modelled in the BN model. The model produced a probability of safe operation of 94.1%, comparable to the annual operator’s data. The result shows that most operations are safe, with a minimum case of crashing and no case of harming human life.
Keywords
Drone operation; Bayesian network; Risk modelling; Risk analysis; Indonesia
Subject
Computer Science and Mathematics, Robotics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
