Causes of Occupational Accidents and Injuries in Construction Industry in Jeddah City

Abukhashabah, Emad Abukhashabah Emad

doi:10.4197/met.28-1.9

Cited by 6 publications

(5 citation statements)

References 17 publications

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“…The existing literature on construction safety in Saudi Arabia also confirms the menace of FFH accidents [8,9]. Strikingly, Abukhashabah et al [10] reported that FFH consists of 80% of the accidents in the construction sector in the city of Jeddah in Saudi Arabia. Hence, the need to understand, and consequently control the rate of FFH accidents in Saudi Arabia is obvious.…”

mentioning

confidence: 75%

Fall From Height Accidents in the Construction Industry in Saudi Arabia

Mahmoud

Sanni-Anibire

Alsafwani

2023

Architecture, Civil Engineering, Environment

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Falls from height (FFH) are considered the most dangerous accident in the global construction industry, especially in emerging economies like Saudi Arabia. This study investigates the causative factors responsible for FFH accidents in the construction industry in Saudi Arabia. The approach used by the study entailed a review of the extant literature to identify the main causes of FFH accidents. The identified causes were used to develop a questionnaire survey, which was administered to construction professionals in Saudi Arabia. Useable feedback from ninety-one responses was obtained and consequently analysed using the Relative Agreement Index (RAI). The results revealed that the top three causes include “lack of training”, “no safety inspection”, and “no safety meeting and seminar between stakeholders”. The causes were also categorized into three groups including “unsafe acts”, “unsafe conditions”, “communication barriers”, and “management commitment”, where “unsafe acts” was the most influential category. The significance of this study is its potential to help control the occurrence of FFH in the construction industry through the adoption of relevant controls, safety training, and risk-based decision-making in the planning and execution of construction works.

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confidence: 75%

Fall From Height Accidents in the Construction Industry in Saudi Arabia

Mahmoud

Sanni-Anibire

Alsafwani

2023

Architecture, Civil Engineering, Environment

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“…To measure the sensitivity of a model, we use recall. Recall tells us how many TP observations the model detected correctly; see Equation (3). The mean average precision (mAP) is used to measure the accuracy of the object detection model across all classes in a given dataset, as shown in Equation ( 4), where AP is the average of all precisions (see Equation ( 5)), and n is the total number of classes [22].…”

Section: Testing and Evaluationmentioning

confidence: 99%

“…Construction sites are known to be highly hazardous environments due to their dynamic and temporary nature. Some studies showed that accidents at construction sites can be caused by many factors, as follows [2,3]: lack of awareness and experience among workers, lack of safety training among workers, workers not wearing personal protective equipment (PPE), no safety officer located in danger zones and machinery defects and errors. Construction workers are involved in many activities that might expose them to risks and accidents.…”

Section: Introductionmentioning

confidence: 99%

“…Construction workers are involved in many activities that might expose them to risks and accidents. Some of the hazards on construction sites may involve falling from heights, being electrocuted, being struck by heavy equipment or falling materials, being caught in equipment and many more, depending on the nature of the site [3]. Those accidents can be prevented by following safety policies and rules such as providing appropriate safety training for the workers, monitoring PPE compliance, regularly inspecting machines for defects and errors, identifying danger zones and assign a safety officer to each danger zone [2].…”

Section: Introductionmentioning

confidence: 99%

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Construction Site Hazards Identification Using Deep Learning and Computer Vision

Alateeq

Ali

2023

Sustainability

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Workers on construction sites face numerous health and safety risks. Authorities have made numerous attempts to enhance safety management; yet incidents continue to occur, impacting both worker health and the project’s forward momentum. To that end, developing strategies to improve construction site safety management is crucial. The goal of this project is to employ computer vision and deep learning methods to create a model that can recognize construction workers, their PPE and the surrounding heavy equipment from CCTV footage. Then, the hazards can be discovered and identified based on an analysis of the imagery data and other criteria including weather conditions, and the on-site safety officer can be contacted. Our own dataset was used to train the You Only Look Once model, version 5 (YOLO-v5), which was put to use as an object detection model. The detection model’s performance in tests showed promise for fast and accurate object recognition in the field.

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“…It has been determined that the main factors of happening these accidents can be found human errors, unsafe behavior, a lack of knowledge and safety training, and poor and ineffective management at the sites (Abukhashabah et al 2019;Bussier and Chong 2022;Namian et al 2022b). One of the accident prevention methods is identifying, evaluating, and controlling potential dangers (Christian et al 2009).…”

Section: Epic Series In Built Environmentmentioning

confidence: 99%

Prevalence of Fatigue Among Construction Workers in The United States

Taherpour,

Namian,

Garay

et al.

EPiC Series in Built Environment

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Within dynamic and complex construction environments, fatal and non-fatal occupational records are alarming all over the world. Fatigue among workers is one of the key causes which affects their ability to operate safely. To improve safety management, the prevalence of fatigue among workers must be investigated to implement effective interventions for fatigue mitigation. However, the prevalence of fatigue among construction workers in the United States has not been studied. Therefore, this research explores this gap by recruiting 120 workers in the U.S. To achieve the research goals, the worker's level of fatigue (i.e., acute, chronic, and inteshift recovery) was measured using a validated OFER scale. Data analysis revealed (1) the prevalence of fatigue among construction workers is alarming (OFER Score=34.23), that acute fatigue, among all aspects of it, has the most profound impact on workers, and (2) there are no statistical correlations between measured fatigue levels and age and experience of construction workers. The findings of this study will be beneficial to practitioners and researchers in construction to implement effective safety measures to prevent accidents in workplaces.

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Causes of Occupational Accidents and Injuries in Construction Industry in Jeddah City

Cited by 6 publications

References 17 publications

Fall From Height Accidents in the Construction Industry in Saudi Arabia

Fall From Height Accidents in the Construction Industry in Saudi Arabia

Construction Site Hazards Identification Using Deep Learning and Computer Vision

Prevalence of Fatigue Among Construction Workers in The United States

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