In the last few years, unmanned aerial vehicles (UAVs) are making a revolution as an emerging
technology with many different applications in the military, civilian, and commercial elds. The advent of
autonomous drones has initiated serious challenges, including how to maintain their safe operation during
their missions. The safe operation of UAVs remains an open and sensitive issue since any unexpected
behavior of the drone or any hazard would lead to potential risks that might be very severe. The motivation
behind this work is to propose a methodology for the safety assurance of drones over the Internet (Internet
of drones (IoD)). Two approaches will be used in performing the safety analysis: (1) a qualitative safety
analysis approach and (2) a quantitative safety analysis approach. The rst approach uses the international
safety standards, namely, ISO 12100 and ISO 13849 to assess the safety of drone's missions by focusing
on qualitative assessment techniques. The methodology starts with hazard identi cation, risk assessment,
risk mitigation, and nally draws the safety recommendations associated with a drone delivery use case.
The second approach presents a method for the quantitative safety assessment using Bayesian networks (BN)
for probabilistic modeling. BN utilizes the information provided by the rst approach to model the safety
risks related to UAVs' ights. An illustrative UAV crash scenario is presented as a case study, followed by
scenario analysis, to demonstrate the applicability of the proposed approach. These two analyses, qualitative
and quantitative, enable all involved stakeholders to detect, explore, and address the risks of UAV ights,
which will help the industry to better manage the safety concerns of UAVs.info:eu-repo/semantics/publishedVersio
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