Big data platform for health and safety accident prediction

Abstract

Purpose The purpose of this paper is to highlight the use of the big data technologies for health and safety risks analytics in the power infrastructure domain with large data sets of health and safety risks, which are usually sparse and noisy. Design/methodology/approach The study focuses on using the big data frameworks for designing a robust architecture for handling and analysing (exploratory and predictive analytics) accidents in power infrastructure. The designed architecture is based on a well coherent health risk analytics lifecycle. A prototype of the architecture interfaced various technology artefacts was implemented in the Java language to predict the likelihoods of health hazards occurrence. A preliminary evaluation of the proposed architecture was carried out with a subset of an objective data, obtained from a leading UK power infrastructure company offering a broad range of power infrastructure services. Findings The proposed architecture was able to identify relevant variables and improve preliminary prediction accuracies and explanatory capacities. It has also enabled conclusions to be drawn regarding the causes of health risks. The results represent a significant improvement in terms of managing information on construction accidents, particularly in power infrastructure domain. Originality/value This study carries out a comprehensive literature review to advance the health and safety risk management in construction. It also highlights the inability of the conventional technologies in handling unstructured and incomplete data set for real-time analytics processing. The study proposes a technique in big data technology for finding complex patterns and establishing the statistical cohesion of hidden patterns for optimal future decision making.

Construction practitioners’ perception of key drivers of reputation in mega-construction projects

“…Hence, the level at which construction megaproject adhere or abandon green initiatives determines their reputation. On the contrary, whereas it is commonplace that the construction industry is bedevilled with health and safety risks, there has been a concentrated effort by health and safety executives to reduce site injuries/deaths to the bare minimum (Ajayi et al , 2019). The extent to which health and safety functions are maintained and casualties were non-existent on construction projects determines the megaproject’s reputation.…”

La seguridad y salud ocupacional a través de los años

“…Mientras que la tecnología de Big Data, gracias a su función de procesamiento paralelo y a su capacidad para manejar competentemente datos de gran dimensión y ruido con relaciones no lineales, resultará ventajosa y fructífera en el análisis de los riesgos para la salud y la seguridad (Ajayi, 2019). Este tipo de tecnologías, con el desarrollo de modelos sólidos, logran ser efectivas para prevenir riesgos laborales como muertes, lesiones o incluso reducir el impacto ambiental en las empresas; además de darles mayor seguridad a los trabajadores en su respectiva zona de trabajo y producir una mejor toma de decisiones, basadas en el análisis de datos que permitirán prever incidentes a futuro.…”

“…7 Representan un apoyo significativo para monitorear la labor cognitiva y física de los trabajadores; esto, debido a los sensores corporales inteligentes en el operador 4.0 que miden la conductancia de la piel, el movimiento del cuerpo y la frecuencia cardiaca, los cuales enviarán datos a un sistema de inteligencia artificial que se encarga de optimizar la ayuda cognitiva y física en función del operario. De esta manera el robot se adaptará a las necesidades cognitivas, físicas, rítmicas y demás a la salud del operador (Ajayi, 2019). • Así mismo, la nueva generación de equipos de protección inteligentes, están impulsados por el desarrollo de wearables inteligentes y sensores de temperatura, humedad, ruido, luz, calidad del aire del entorno laboral en los lugares de trabajo industriales; además de los sensores de ubicación de movimiento y ubicación de los operadores.…”

Impact of big data analytics capabilities on supply chain sustainability

“…In fact, BDA systems creates competitive advantage against rivals and enhances enterprise agility (Côrte-Real and Oliveira, 2016). Based on the research by Ajayi et al (2019), in which the relation between BD platform and safety accident prediction was assessed. This paper results showed that a significant improvement was obtained in information management.…”