Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules

Authors

  • Ibrahim Nasir Mahmood Basra University for Oil and Gas
  • Hussein Ali Aliedane Basra University for Oil and Gas
  • Mustafa Ali Abuzaraida Universiti Utara Malaysia

DOI:

https://doi.org/10.3991/ijim.v15i12.22687

Keywords:

Data Mining, Association Rules, Fire Accidents Analysis, Data Analysis, Data Cleaning

Abstract


Due to the increased rate of fire accidents which cause many damages and losses to people souls, material, and property in Basra city. The necessity of analyzing and mining the data of the fire accidents became an urgent need to find a solution. The need increased for a solution that helps to mitigate and reduce the number of accidents. In this paper, data mining techniques and applications including data preprocessing, data cleaning, and data exploration have been applied. Data mining applications is performed to analyze and discover the hidden knowledge in ten years of data (fire accidents happened from 2010 – 2019) which is approximately 20k record of accidents. These data mining techniques along with the association rules algorithm is applied on the dataset. The applied approach and techniques resulted in discovering the patterns and the nature of the fire accidents in Basra city. It also helped to reach to recommendations and resolutions for mitigating the fire accidents and its occurrence rate.

Author Biographies

Ibrahim Nasir Mahmood, Basra University for Oil and Gas

Ibrahim Nasir Mahmood is a lecturer in computer science field. He received his BSc degree in Software Engineering on 2008. He holds Master’s degree in Computer Science from University of Bridgeport, CT, USA. He received his degree with Academic Achievement Award and Honors, He is a member of the UPE International Computing Society. He works at the Department of Chemical and Oil Refinery Engineering in Faculty of Oil and Gas Engineering, Basra University for Oil and Gas. His research interests include data mining, data science, machine learning, IoT, and E-learning, and Algorithms.

Hussein Ali Aliedane, Basra University for Oil and Gas

Dr. Hussein Ali Khouhdor Aliedane is a senior lecturer at the Department of Oil and Gas Engineering in Faculty of Oil and Gas Engineering, Basra University for Oil and Gas. He holds PhD degree in Computer Science. He currently works as vice dean for scientific affair. His research interests include Data Mining, GIS, Data Science, E-Learning, Digital Image Processing and Algorithms

Mustafa Ali Abuzaraida, Universiti Utara Malaysia

Dr. Mustafa Ali Abuzaraida is international senior lecturer.. He obtained his master degree in (Intelligent System) from University Utara Malaysia (UUM) in 2006 and a Ph.D. in (Computer Science) from International Islamic University Malaysia (IIUM) in 2015. His research interest is on Image processing, Data science, Data mining, Artificial intelligence application, and Natural Language Processing (NLP) mainly on text normalization and sentiment analysis and recognizing online handwritten text. Currently, he is working at School of Computing, College of Arts and Sciences, University Utara Malaysia as international senior lecturer.

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Published

2021-06-18

How to Cite

Mahmood, I. N., Aliedane, H. A., & Abuzaraida, M. A. (2021). Applications of Data Mining in Mitigating Fire Accidents Based on Association Rules. International Journal of Interactive Mobile Technologies (iJIM), 15(12), pp. 158–169. https://doi.org/10.3991/ijim.v15i12.22687

Issue

Vol. 15 No. 12 (2021)

Section

Papers