Application of cloud and fog computing for data processing on board aircraft

Аuthors

Glushak E. V.^*, Klyuev D. S.^**

,

*e-mail: evglushak@yandex.ru
**e-mail: klyuevd@yandex.ru

Abstract

This article examines the integration of Internet of Things (IoT) technologies, fog computing, and cloud computing for monitoring and predicting the technical condition of aircraft. A mathematical model has been developed to describe the processes of collecting, pre‑processing, and analysing data from onboard sensors. Algorithms have been designed to calculate the integral degradation index, failure probability, residual life of components, and to predict maintenance schedules. An architecture of a distributed system is proposed, in which fog nodes perform local data filtering and primary analysis, while cloud platforms carry out long‑term analytical processing and optimisation of maintenance schedules. The degradation processes of equipment have been simulated using time series of sensor data. Graphs have been constructed to illustrate changes in failure probability, residual life, and predicted maintenance schedules. The simulation results demonstrate that the use of fog computing significantly reduces delays in anomaly detection, while cloud computing enhances the accuracy of predictions regarding residual life and maintenance schedules.

Keywords:

cloud and fog computing, sensors, probability of failure, delays, remaining resource

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