Preventing Workplace Incidents in Construction

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A01=Imriyas Kamardeen
accident
advanced safety data mining
Australian Construction Industry
Author_Imriyas Kamardeen
Category=GPH
Category=KNJ
Category=KNXC
CHAID Algorithm
Compensation Claim Date
Construction Fatalities
Construction Incidents
construction risk assessment
Construction safety
data analytics
data mining
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Greater Hearing Impairment
H&S
health and safety
health and safety in construction
Hearing Protection Devices
HSE
Human Suffering
incident data analysis
Lost Time Injury Frequency Rates
Low Prediction Error
MCA Analysis
MCA Result
MSD Prevalence
Multiple Correspondence Analysis
Neural Network Model
Noise Induced Hearing Loss
occupational health
OSHA
predictive modelling
prevention
Psychological Injuries
RFID Reader
RFID Tag
Safe Work Australia
safety
safety analytics
Temporary Incapacities
Unmanned Aerial Vehicles
WHS
Widowed Marital Status
work health and safety
work illnesses
work injuries
Work Injury
workplace incidents
workplace injury prevention

Product details

  • ISBN 9781032177915
  • Weight: 258g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Sep 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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The construction industry is vital to any national economy; it is also one of the industries most susceptible to workplace incidents. The unacceptably high rates of incidents in construction have huge socio-economic consequences for the victims, their families and friends, co-workers, employers and society at large. Construction safety researchers have introduced numerous strategies, models and tools through scientific inquiries involving primary data collection and analyses. While these efforts are commendable, there is a huge potential to create new knowledge and predictive models to improve construction safety by utilising already existing data about workplace incidents. In this new book, Imriyas Kamardeen argues that more sophisticated approaches need to be deployed to enable improved analyses of incident data sets and the extraction of more valuable insights, patterns and knowledge to prevent work injuries and illnesses.

The book aims to apply data mining and analytic techniques to past workplace incident data to discover patterns that facilitate the development of innovative models and strategies, thereby improving work health, safety and well-being in construction, and curtailing the high rate of incidents. It is essential reading for researchers and professionals in construction, health and safety and anyone interested in data analytics.

Imriyas Kamardeen is Professor of Construction Management at Deakin University, Australia. He is also the Editor of the international journal Construction Economics and Building. His research and teaching interests predominantly lie in Construction Informatics and Workplace Health and Safety. He has authored two books previously with Routledge: OHS Electronic Management Systems for Construction (2013), and Fall Prevention Through Design in Construction: The Benefits of Mobile Computing (2015).

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