Description
Book SynopsisThe 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 tec
Table of Contents
Preface i
Acknowledgements ii
Figures iii
Tables v
Abbreviations vi
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- Introduction
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- Curtailing construction fatalities using analytics
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- Reducing uncertainties in compensation for occupational diseases in construction using analytics
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- Curbing psychological injuries in construction using analytics
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- Predicting and preventing secondary psychological injuries in construction using analytics
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- Conclusion
Index
