A NOVEL APPROACH FOR INTERNET OF THINGS BASED INTELLIGENT WEATHER DATA ACQUISITION IN AIRCRAFT

  • Doğu Sırt Computer Engineering Department, Istanbul Technical University
  • Evren Dağlarlı Computer Engineering Department, Istanbul Technical University
  • Erke Arıbaş Computer Engineering Department, Istanbul Technical University
Keywords: Weather data, sensors, big data, internet of things, machine-to-machine (M2M) interaction

Abstract

Today, every device which is connected to the Internet collects, shares and augments data of each other. This key feature fosters researchers to use the power of sensors while designing intelligent and cognitive systems. One of the widespread usage area of sensors is weather data acquisition because of their place in internet of things. In previous works, it is not found a well-coordinated approach for collecting and sharing weather data in aircraft. In our approach, we propose a novel system which has the capability of self-exploring, self-learning and self-decision under different weather circumstances. An aircraft equipped by powerful sensors is expected to designate its next step according to weather data including deciding whether to fly or flight safety while on air. By applying genetic (evolutionary) algorithm to aircraft sensors, it becomes possible to optimize parameters of remote sensing devices and analyze them in terms of weather data. According to IOT mechanism of our system, it is provided for all electronic devices to be labeled and to be ready for data exchange. Despite the fact that every mechanism works properly in our system, one prominent limitation becomes discontinuous data flow between different sensors. As a result, our system becomes capable of preventing problems while weather data is being shared among different devices.

Downloads

Download data is not yet available.

References

A. K. Jardine, D. Lin and D. Banjevic, “A review of machinery diagnostics and prognostics implementing condition-based maintenance”, Mechanical Systems and Signal Processing, Vol 20, No 7, 2006, pp. 1483-1510.

M. Gerdes, D. Galar and D. Scholz, "Genetic algorithms and decision trees for condition monitoring and prognosis of A320 aircraft air conditioning." Insight-Non-Destructive Testing and Condition Monitoring Vol 59, No 8, 2017, pp. 424-433.

J. N. Warner, D.R.II. George, "System, Methodology, and Process for Wireless Transmission of Sensor Data Onboard an Aircraft to a Portable Electronic Device." U.S. Patent Application No. 15/386,301.

K. Y. Wong, C. L. Yip, P. W. Li, “Automatic identification of weather systems from numerical weather prediction data using genetic algorithm”, Expert Systems with Applications, Volume 35, Issues 1–2, 2008, pp. 542-555.

https://www.nasa.gov/vision/earth/environ-ment/2006ams_TAMDAR.htm

Published
2018-06-29
How to Cite
Sırt, D., Dağlarlı, E., & Arıbaş, E. (2018). A NOVEL APPROACH FOR INTERNET OF THINGS BASED INTELLIGENT WEATHER DATA ACQUISITION IN AIRCRAFT. International Journal of Scientific Research in Information Systems and Engineering (IJSRISE), 4(1), 1-3. Retrieved from http://www.ijsrise.com/index.php/IJSRISE/article/view/1
Abstract viewed = 0 times
PDF downloaded = 0 times

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.