Preventing Workplace Incidents in Construction: Data Mining and Analytics Applications (Spon Research)

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.

Copyright:

2020

Book Details

Book Quality:

Publisher Quality

ISBN-13:

9781351616133

Related ISBNs:

9781315110462, 9781138087453, 9781138087453

Publisher:

CRC Press

Date of Addition:

07/09/19

Copyrighted By:

Imriyas Kamardeen

Adult content:

No

Language:

English

Has Image Descriptions:

No

Categories:

Nonfiction, Art and Architecture, Home and Garden, Technology, Law, Legal Issues and Ethics

Submitted By:

Bookshare Staff

Usage Restrictions:

This is a copyrighted book.