Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports

Aziida Nanyonga; Hassan Wasswa; Graham Wild

doi:10.1109/GCITC60406.2023.10426306

Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports

Aziida Nanyonga^*
, Hassan Wasswa
, Graham Wild

^*Corresponding author for this work

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

15 Scopus citations

Abstract

Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learning models, including LSTM, CNN, Bidirectional LSTM (BLSTM), and simple Recurrent Neural Networks (sRNN), to classify flight phases in safety reports from the Australian Transport Safety Bureau (ATSB). The models exhibited high accuracy, precision, recall, and F1 scores, with LSTM achieving the highest performance of 87%, 88%, 87%, and 88%, respectively. This performance highlights their effectiveness in automating safety occurrence analysis. The integration of NLP and Deep Learning technologies promises transformative enhancements in aviation safety analysis, enabling targeted safety measures and streamlined report handling.

Original language	English
Title of host publication	2023 Global Conference on Information Technologies and Communications, GCITC 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350308167
DOIs	https://doi.org/10.1109/GCITC60406.2023.10426306
State	Published - 2023
Externally published	Yes
Event	2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023 - Karnataka, India Duration: 1 Dec 2023 → 3 Dec 2023

Publication series

Name	2023 Global Conference on Information Technologies and Communications, GCITC 2023

Conference

Conference	2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023
Country/Territory	India
City	Karnataka
Period	1/12/23 → 3/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

ATSB
Aviation Safety
Deep learning
Flight phase
NLP

ASJC Scopus subject areas

Information Systems and Management
Safety, Risk, Reliability and Quality
Control and Optimization
Health Informatics
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications

Access to Document

10.1109/GCITC60406.2023.10426306

Cite this

Nanyonga, A., Wasswa, H., & Wild, G. (2023). Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports. In 2023 Global Conference on Information Technologies and Communications, GCITC 2023 (2023 Global Conference on Information Technologies and Communications, GCITC 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GCITC60406.2023.10426306

Nanyonga, Aziida ; Wasswa, Hassan ; Wild, Graham. / Aviation Safety Enhancement via NLP & Deep Learning : Classifying Flight Phases in ATSB Safety Reports. 2023 Global Conference on Information Technologies and Communications, GCITC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 Global Conference on Information Technologies and Communications, GCITC 2023).

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title = "Aviation Safety Enhancement via NLP \& Deep Learning: Classifying Flight Phases in ATSB Safety Reports",

abstract = "Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learning models, including LSTM, CNN, Bidirectional LSTM (BLSTM), and simple Recurrent Neural Networks (sRNN), to classify flight phases in safety reports from the Australian Transport Safety Bureau (ATSB). The models exhibited high accuracy, precision, recall, and F1 scores, with LSTM achieving the highest performance of 87\%, 88\%, 87\%, and 88\%, respectively. This performance highlights their effectiveness in automating safety occurrence analysis. The integration of NLP and Deep Learning technologies promises transformative enhancements in aviation safety analysis, enabling targeted safety measures and streamlined report handling.",

keywords = "ATSB, Aviation Safety, Deep learning, Flight phase, NLP",

author = "Aziida Nanyonga and Hassan Wasswa and Graham Wild",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023 ; Conference date: 01-12-2023 Through 03-12-2023",

year = "2023",

doi = "10.1109/GCITC60406.2023.10426306",

language = "English",

series = "2023 Global Conference on Information Technologies and Communications, GCITC 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 Global Conference on Information Technologies and Communications, GCITC 2023",

address = "United States",

}

Nanyonga, A, Wasswa, H & Wild, G 2023, Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports. in 2023 Global Conference on Information Technologies and Communications, GCITC 2023. 2023 Global Conference on Information Technologies and Communications, GCITC 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023, Karnataka, India, 1/12/23. https://doi.org/10.1109/GCITC60406.2023.10426306

Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports. / Nanyonga, Aziida; Wasswa, Hassan; Wild, Graham.
2023 Global Conference on Information Technologies and Communications, GCITC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 Global Conference on Information Technologies and Communications, GCITC 2023).

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

TY - GEN

T1 - Aviation Safety Enhancement via NLP & Deep Learning

T2 - 2023 IEEE Global Conference on Information Technologies and Communications, GCITC 2023

AU - Nanyonga, Aziida

AU - Wasswa, Hassan

AU - Wild, Graham

PY - 2023

Y1 - 2023

N2 - Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learning models, including LSTM, CNN, Bidirectional LSTM (BLSTM), and simple Recurrent Neural Networks (sRNN), to classify flight phases in safety reports from the Australian Transport Safety Bureau (ATSB). The models exhibited high accuracy, precision, recall, and F1 scores, with LSTM achieving the highest performance of 87%, 88%, 87%, and 88%, respectively. This performance highlights their effectiveness in automating safety occurrence analysis. The integration of NLP and Deep Learning technologies promises transformative enhancements in aviation safety analysis, enabling targeted safety measures and streamlined report handling.

AB - Aviation safety is paramount, demanding precise analysis of safety occurrences during different flight phases. This study employs Natural Language Processing (NLP) and Deep Learning models, including LSTM, CNN, Bidirectional LSTM (BLSTM), and simple Recurrent Neural Networks (sRNN), to classify flight phases in safety reports from the Australian Transport Safety Bureau (ATSB). The models exhibited high accuracy, precision, recall, and F1 scores, with LSTM achieving the highest performance of 87%, 88%, 87%, and 88%, respectively. This performance highlights their effectiveness in automating safety occurrence analysis. The integration of NLP and Deep Learning technologies promises transformative enhancements in aviation safety analysis, enabling targeted safety measures and streamlined report handling.

KW - ATSB

KW - Aviation Safety

KW - Deep learning

KW - Flight phase

KW - NLP

UR - https://www.scopus.com/pages/publications/85191683533

U2 - 10.1109/GCITC60406.2023.10426306

DO - 10.1109/GCITC60406.2023.10426306

M3 - Conference contribution

AN - SCOPUS:85191683533

T3 - 2023 Global Conference on Information Technologies and Communications, GCITC 2023

BT - 2023 Global Conference on Information Technologies and Communications, GCITC 2023

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 1 December 2023 through 3 December 2023

ER -

Nanyonga A, Wasswa H, Wild G. Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports. In 2023 Global Conference on Information Technologies and Communications, GCITC 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 Global Conference on Information Technologies and Communications, GCITC 2023). doi: 10.1109/GCITC60406.2023.10426306

Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this