Real-time investigation of flight delays based on the internet of things data

Abdulwahab Aljubairy; Ali Shemshadi; Quan Z. Sheng

doi:10.1007/978-3-319-49586-6_57

Real-time investigation of flight delays based on the internet of things data

Abdulwahab Aljubairy, Ali Shemshadi^*, Quan Z. Sheng

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

13 Citations (Scopus)

Abstract

Flight delay is a very important problem resulting in the wasting of billions of dollars each year. Other researchers have studied this problem using historical records of flights. With the emerging paradigm of Internet of things (IoT), it is now possible to analyze sensors data in real-time. We investigate flight delays using real-time data from the IoT. We crawl IoT data and collect the data from various resources including flights, weather and air quality sensors. Our goal is to improve our understanding of the roots and signs of flight delays in order to be able to classify a given flight based on the features from flights and other data sources. We extend the existing works by adding new data sources and considering new factors in the analysis of flight delay. Through the use of real-time data, our goal is to establish a novel service to predict delays in real-time.

Original language	English
Title of host publication	Advanced data mining and applications
Subtitle of host publication	12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings
Editors	Jinyan Li, Xue Li, Shuliang Wang, Jianxin Li, Quan Z. Sheng
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	788-800
Number of pages	13
ISBN (Electronic)	9783319495866
ISBN (Print)	9783319495859
DOIs	https://doi.org/10.1007/978-3-319-49586-6_57
Publication status	Published - 2016
Externally published	Yes
Event	12th International Conference on Advanced Data Mining and Applications, ADMA 2016 - Gold Coast, Australia Duration: 12 Dec 2016 → 15 Dec 2016

Publication series

Name	Lecture Notes in Artificial Intelligence
Publisher	Springer
Volume	10086
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	12th International Conference on Advanced Data Mining and Applications, ADMA 2016
Country/Territory	Australia
City	Gold Coast
Period	12/12/16 → 15/12/16

Keywords

Data mining
Flight delay analysis
Internet of things
Machine learning
Prediction

Access to Document

10.1007/978-3-319-49586-6_57

Cite this

Aljubairy, A., Shemshadi, A., & Sheng, Q. Z. (2016). Real-time investigation of flight delays based on the internet of things data. In J. Li, X. Li, S. Wang, J. Li, & Q. Z. Sheng (Eds.), Advanced data mining and applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings (pp. 788-800). (Lecture Notes in Artificial Intelligence; Vol. 10086). Springer, Springer Nature. https://doi.org/10.1007/978-3-319-49586-6_57

Aljubairy, Abdulwahab ; Shemshadi, Ali ; Sheng, Quan Z. / Real-time investigation of flight delays based on the internet of things data. Advanced data mining and applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings. editor / Jinyan Li ; Xue Li ; Shuliang Wang ; Jianxin Li ; Quan Z. Sheng. Cham : Springer, Springer Nature, 2016. pp. 788-800 (Lecture Notes in Artificial Intelligence).

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abstract = "Flight delay is a very important problem resulting in the wasting of billions of dollars each year. Other researchers have studied this problem using historical records of flights. With the emerging paradigm of Internet of things (IoT), it is now possible to analyze sensors data in real-time. We investigate flight delays using real-time data from the IoT. We crawl IoT data and collect the data from various resources including flights, weather and air quality sensors. Our goal is to improve our understanding of the roots and signs of flight delays in order to be able to classify a given flight based on the features from flights and other data sources. We extend the existing works by adding new data sources and considering new factors in the analysis of flight delay. Through the use of real-time data, our goal is to establish a novel service to predict delays in real-time.",

keywords = "Data mining, Flight delay analysis, Internet of things, Machine learning, Prediction",

author = "Abdulwahab Aljubairy and Ali Shemshadi and Sheng, {Quan Z.}",

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Aljubairy, A, Shemshadi, A & Sheng, QZ 2016, Real-time investigation of flight delays based on the internet of things data. in J Li, X Li, S Wang, J Li & QZ Sheng (eds), Advanced data mining and applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings. Lecture Notes in Artificial Intelligence, vol. 10086, Springer, Springer Nature, Cham, pp. 788-800, 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, Gold Coast, Australia, 12/12/16. https://doi.org/10.1007/978-3-319-49586-6_57

Real-time investigation of flight delays based on the internet of things data. / Aljubairy, Abdulwahab; Shemshadi, Ali; Sheng, Quan Z.
Advanced data mining and applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings. ed. / Jinyan Li; Xue Li; Shuliang Wang; Jianxin Li; Quan Z. Sheng. Cham: Springer, Springer Nature, 2016. p. 788-800 (Lecture Notes in Artificial Intelligence; Vol. 10086).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Aljubairy, Abdulwahab

AU - Shemshadi, Ali

AU - Sheng, Quan Z.

PY - 2016

Y1 - 2016

N2 - Flight delay is a very important problem resulting in the wasting of billions of dollars each year. Other researchers have studied this problem using historical records of flights. With the emerging paradigm of Internet of things (IoT), it is now possible to analyze sensors data in real-time. We investigate flight delays using real-time data from the IoT. We crawl IoT data and collect the data from various resources including flights, weather and air quality sensors. Our goal is to improve our understanding of the roots and signs of flight delays in order to be able to classify a given flight based on the features from flights and other data sources. We extend the existing works by adding new data sources and considering new factors in the analysis of flight delay. Through the use of real-time data, our goal is to establish a novel service to predict delays in real-time.

AB - Flight delay is a very important problem resulting in the wasting of billions of dollars each year. Other researchers have studied this problem using historical records of flights. With the emerging paradigm of Internet of things (IoT), it is now possible to analyze sensors data in real-time. We investigate flight delays using real-time data from the IoT. We crawl IoT data and collect the data from various resources including flights, weather and air quality sensors. Our goal is to improve our understanding of the roots and signs of flight delays in order to be able to classify a given flight based on the features from flights and other data sources. We extend the existing works by adding new data sources and considering new factors in the analysis of flight delay. Through the use of real-time data, our goal is to establish a novel service to predict delays in real-time.

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ER -

Aljubairy A, Shemshadi A, Sheng QZ. Real-time investigation of flight delays based on the internet of things data. In Li J, Li X, Wang S, Li J, Sheng QZ, editors, Advanced data mining and applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12–15, 2016, proceedings. Cham: Springer, Springer Nature. 2016. p. 788-800. (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-319-49586-6_57

Real-time investigation of flight delays based on the internet of things data

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