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

Mahmood, Ibrahim Nasir; Aliedane, Hussein Ali; Abuzaraida, Mustafa Ali

doi:10.3991/ijim.v15i12.22687

Cited by 2 publications

(4 citation statements)

References 7 publications

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“…Data processing is one of the most valuable and useful tools used in computer science applications [17]. It utilizes large volumes of data in order to extract useful knowledge and hidden patterns [18].…”

Section: Data Mining Techniquesmentioning

confidence: 99%

“…Data processing can be employed in various fields such as machine learning, artificial intelligence, database technology, image and signal processing, high-performance computing, and data visualization [18]. Data processing phase is applied to clean and organize the dataset by correcting syntax errors, manipulation of missing values, and removal of outliers [17]. Finally, the clean and structured dataset can be analyzed and explored to identify relationships between target variables.…”

Section: Data Mining Techniquesmentioning

confidence: 99%

“…The structure of data and relationship among various variables become very clear and discoverable during this phase. The organization and distribution of values and characteristics of the data become more noticeable and obvious during data exploration [17].…”

Section: Data Mining Techniquesmentioning

confidence: 99%

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A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

Mahmood¹,

Abuzaraida

2023

Int. J. Interact. Mob. Technol.

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E-learning became the main medium of education in the world for the past two years. COVID-19 virus has pushed all the universities and academic institutions to utilize and activate E-learning platforms and systems. The sudden and urgent transformation from the regular traditional learning system to E-learning system has involved many challenges and limitations. Therefore, the need to evaluate and enhance the current E-learning mechanism in Iraq became very urgent and critical need. The target level was students at higher education institutes which include university students in Basra city. The data collected based on students’ evaluation and opinions about E-learning based on their interaction and usage during two years under COVID-19 spread era. This research involved applying data mining techniques to sample dataset and utilizing the obtained results as feedback for a proposed model suggested by the authors to measure adaptability. The proposed model is derived from the idea of the Technology Acceptance Model (TAM) with focus on the positivity as the main factor to measure adaptability. The results of the research showed approximate adaptation level of 52% which is very close compared to the actual situation in real life which involve limitations and challenges faced by Iraqi students.

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Section: Data Mining Techniquesmentioning

confidence: 99%

Section: Data Mining Techniquesmentioning

confidence: 99%

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A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

Mahmood¹,

Abuzaraida

2023

Int. J. Interact. Mob. Technol.

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“…Fires and explosions can occur at any time and they can be started by a number of causes such as electrical impact, children messing, fire spark, gas leaks, etc. [1], [2]. In Vietnam, thousands of fires are reported annually; for example, there were 2357, 2792 and 5354 reported fires in 2014, 2015 and 2020, respectively, resulting in a large number of deaths and injuries [1], [3]- [4].…”

Section: Introductionmentioning

confidence: 99%

A Simple and Real-Time Support System for Firefighters Using Low-Cost 3-DOF Accelerometer and CO Sensor

et al. 2022

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During the operations, firefighters can be injured or killed because of the smoke and heat emission from the fire area, broken structure elements such as floors, walls, or boiling liquid ejection and gas explosion. Therefore, this paper aims to develop an efficient and portable system to monitor falls and high CO level through integrating a three degrees of freedom accelerometer and an MQ7 sensor to recorded acceleration and measured CO concentration with the embedded fall and high CO detection algorithms. The embedded fall detection algorithm can detect fall events with ultra-high accuracy without mistakenly identifying normal activities such as walking, standing, jogging, and jumping as fall events. The posture recognition and cascade posture recognition after three seconds are proposed in this paper to gain the accuracy of our proposed fall detection system. If a firefighter falls and is unable to stand up, the alert signal message will be sent to their commander outside through the GSM/GPRS module. The embedded high CO detection algorithm used to alert the dangerous CO level to recommend using self-contained breathing apparatuses (SCBA) and saving fresh air with acceptable CO level. We carefully investigated the proposed thresholds and window size before embedding them into the microcontroller. The sensitivity and accuracy achieved were around 96.5% and 93% respectively in our recorded data. Furthermore, the proposed fall detection algorithm also achieved higher geometric mean in comparison with Support Vector Machine classifier (SVM) and a nearest neighbor rule (NN) in the public datasets with the achieved around 99.44%, 98.41% and 95.76% respectively.

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

Cited by 2 publications

References 7 publications

A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

A Proposed Model for E-learning Adaptability Measurement During COVID-19 Pandemic Using Data Mining Techniques

A Simple and Real-Time Support System for Firefighters Using Low-Cost 3-DOF Accelerometer and CO Sensor

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