10% off all books and free delivery over £40
Buy from our bookstore and 25% of the cover price will be given to a school of your choice to buy more books. *15% of eBooks.

Preventing Workplace Incidents in Construction

View All Editions

The selected edition of this book is not available to buy right now.
Add To Wishlist
Write A Review

About

Preventing Workplace Incidents in Construction Synopsis

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.

About This Edition

ISBN: 9781138087453
Publication date: 25th June 2019
Author: Imriyas Kamardeen
Publisher: Routledge an imprint of Taylor & Francis Ltd
Format: Hardback
Pagination: 168 pages
Series: Spon Research
Genres: Construction and heavy industry
Health and safety in the workplace
Data science and analysis: general