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1 – 10 of over 1000Anuoluwapo Ajayi, Lukumon Oyedele, Juan Manuel Davila Delgado, Lukman Akanbi, Muhammad Bilal, Olugbenga Akinade and Oladimeji Olawale
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…
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.
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Kamran Mahroof, Amizan Omar, Emilia Vann Yaroson, Samaila Ado Tenebe, Nripendra P. Rana, Uthayasankar Sivarajah and Vishanth Weerakkody
The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.
Abstract
Purpose
The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.
Design/methodology/approach
The authors used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model was conducted to assess the research’s hypothesised relationships.
Findings
The authors provide empirical evidence to support the contributions of I5.0 drones for cleaner production. The findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations, such as reducing plant diseases, which invariably enhances cleaner production. However, there is less inclination to drone adoption if the aim was pollution reduction, predicting seasonal output and addressing workers’ health and safety challenges. The findings outline the need for awareness to promote the use of drones for addressing workers’ hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.
Originality/value
To the best of the authors’ knowledge, this study is the first to address I5.0 drones’ adoption using a sustainability model. The authors contribute to existing literature by extending the sustainability model to identify the contributions of drone use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators.
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Richard Gruss, David Goldberg, Nohel Zaman and Alan Abrahams
The widespread adoption of online purchasing has prompted increasing concerns about product safety, and regulators are beginning to hold e-commerce sites accountable for dangerous…
Abstract
Purpose
The widespread adoption of online purchasing has prompted increasing concerns about product safety, and regulators are beginning to hold e-commerce sites accountable for dangerous product defects. For online consumers, understanding the many inherent safety risks among the extensive array of products they browse is a formidable task. The authors attempt to address this problem via a client-side software artifact that warns shoppers about potential product safety hazards at the point of sale.
Design/methodology/approach
In this study, the authors built four candidate designs and assessed their effectiveness by means of a large randomized controlled experiment (n = 466). The authors define effectiveness as significant changes in dependent variables associated with health behaviors and technology adoption.
Findings
The authors find that all of the designs score high on adoption likelihood, that designs incorporating highlighting and scoring are better at increasing safety knowledge and that simpler designs are better at enhancing safety awareness.
Originality/value
These findings will inform the design of safety information dissemination systems and open new areas of safety awareness enhancement research. More generally, the authors introduce a novel method of testing text visualization variations and their impact on behavioral decisions.
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Arindam Chakrabarty and Uday Sankar Das
History teaches us that the glorious victory of mankind across the centuries was accomplished through the successful use of information. The gigantic progressions and rapid…
Abstract
History teaches us that the glorious victory of mankind across the centuries was accomplished through the successful use of information. The gigantic progressions and rapid transformation of human societies have endorsed legitimacy of abundant data, multiple dynamic variables & critical complexities which reinforce the academia and researchers for understanding and pioneering into ‘Big Data Analytics (BDA)’. Health is one of the vibrant socio-economic variables which have correlations with other aspects of life, that is, education, poverty, income, etc. In fact, there are unending debates whether health can be a basic input for a holistic developmental process or it is the outcome of various developmental factors. BDAs are being used across various sectors of the economy. The developed nations have been yielding most feasible solutions using various forms of analysis of big data. Astronomical research has been using a large quantum of data for accomplishing various satellite projects, space technology, and numerous space missions for the astronaut. With the advent of fourth industrial revolution, the world community has been thriving toward a new age technological innovations that include artificial intelligence, machine learning, block chain technology, etc., which act a pivotal tool for BDAs. In the health sector, application of BDAs has been attempted and experimented in the developed nations which have resulted prolific and sustainable solutions to the most typical cumbersome problems. This chapter has demonstrated how BDAs can make progressive reforms in the Indian Health sector outlining the present status and emerging challenges.
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Hazwani Shafei, Rahimi A. Rahman and Yong Siang Lee
Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended…
Abstract
Purpose
Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended technologies without aligning with organizational vision. Furthermore, there is no prioritization on which Construction 4.0 technology should be adopted, including the impact of the technologies on different criteria such as safety and health. Therefore, this study aims to evaluate Construction 4.0 technologies listed in a national strategic plan that targets the enhancement of safety and health.
Design/methodology/approach
A list of Construction 4.0 technologies from a national strategic plan is evaluated using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Then, the data are analyzed using reliability, fuzzy TOPSIS, normalization, Pareto, sensitivity, ranking and correlation analyses.
Findings
The analyses identified six Construction 4.0 technologies that are critical in enhancing safety and health: Internet of Things, autonomous construction, big data and predictive analytics, artificial Intelligence, building information modeling and augmented reality and virtualization. In addition, six pairs of Construction 4.0 technologies illustrate strong relationships.
Originality/value
This study contributes to the existing body of knowledge by ranking a list of Construction 4.0 technologies in a national strategic plan that targets the enhancement of safety and health. Decision-makers can use the study findings to prioritize the technologies during the adoption process. Also, to the best of the authors’ knowledge, this study is the first to evaluate the impact of Construction 4.0 technologies listed in a national strategic plan on a specific criterion.
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Tawseef Ayoub Shaikh and Rashid Ali
Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing…
Abstract
Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing record, clinical information, streaming information from sensors, biomedical image data, biomedical signal information, lab data, and so on brand it substantial as well as mind-boggling as far as changing information positions, which have stressed the abilities of prevailing regular database frameworks in terms of scalability, storage of unstructured data, concurrency, and cost. Big data solutions step in the picture by harnessing these colossal, assorted, and multipart data indexes to accomplish progressively important and learned patterns. The reconciliation of multimodal information seeking after removing the relationship among the unstructured information types is a hotly debated issue these days. Big data energizes in triumphing the bits of knowledge from these immense expanses of information. Big data is a term which is required to take care of the issues of volume, velocity, and variety generally seated in the medicinal services data. This work plans to exhibit a survey of the writing of big data arrangements in the medicinal services part, the potential changes, challenges, and accessible stages and philosophies to execute enormous information investigation in the healthcare sector. The work categories the big healthcare data (BHD) applications in five broad categories, followed by a prolific review of each sphere, and also offers some practical available real-life applications of BHD solutions.
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Mamata Rath and Binod Pattanayak
With the development of emerging engineering technology and industrialization, there are greater changes in the life style of people in smart urban cities; therefore, there is…
Abstract
Purpose
With the development of emerging engineering technology and industrialization, there are greater changes in the life style of people in smart urban cities; therefore, there is also more chance of various health problems in urban areas. The life style of persons in metro urban areas with the expansive volume of population is similarly influenced by different application and administration frameworks. These are affecting the human health system up to an extended extent and there are more health-related issues and health hazard concerns that can be identified in urban areas. The purpose of this paper is to present an analytical study on various aspects of the smart health care system in a smart perspective by analyzing them with respect to emerging engineering technologies such as mobile network, cloud computing, Internet of Things (IoT), big data analytics and ubiquitous computing. This paper also carries out a detailed survey of health issues and improved solutions in automated systems using these technologies. Second, the paper also presents a novel health care system using smart and safe ambulances and their appropriate control at traffic points with safety and security features in a smart city, so that the valuable life of patients can be saved in time by immediate treatment in nearest hospital or health care units.
Design/methodology/approach
In this paper, an analytical survey was conducted for improvement in the health care sector using computer technology and IoT-based various modern health care applications. An idea of Smart Health Care Hospital using sensors, mobile agent smart vehicle configuration and safety traffic control for ambulance was proposed.
Findings
A simulation was carried out to see the performance of a safety mechanism in the proposed approach. Comparative analysis was carried out with other approaches to know the execution time, response time and probable delay due to the implementation of this approach.
Originality/value
It is an original research work with motivation inspired from current emergent technology to apply in the health care system.
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Erika A. Parn, David Edwards, Zainab Riaz, Fahad Mehmood and Joseph Lai
This paper aims to report upon the further development of a hybrid application programming interface (API) plug-in to building information modelling (BIM) entitled confined spaces…
Abstract
Purpose
This paper aims to report upon the further development of a hybrid application programming interface (API) plug-in to building information modelling (BIM) entitled confined spaces safety monitoring system “CoSMoS”. Originally designed to engineer-out environmental hazards associated with working in a building’s confined spaces (during the construction phase of a building’s life-cycle), this second generation version is expanded upon to use archival records to proactively learn from data generated within a sensor network during the building’s operations and maintenance (O&M) phase of asset management (AM).
Design/methodology/approach
An applied research methodological approach adopted used a two-phase process. In phase one, a conceptual model was created to provide a “blueprint map” to integrate BIM, sensor-based networks and data analytics (DA) into one integral system. A literature review provided the basis for the conceptual model’s further development. In phase two, the conceptual model was transposed into the prototype’s development environment as a proof of concept using primary data accrued from a large educational building.
Findings
An amalgamation of BIM, historical sensor data accrued and the application of DA demonstrate that CoSMoS provides an opportunity for the facilities management (FM) team to monitor pertinent environmental conditions and human behaviour within buildings that may impact upon occupant/worker safety. Although working in confined spaces is used to demonstrate the inherent potential of CoSMoS, the system could readily be expanded to analyse sensor-based network’s historical data of other areas of building performance, maintenance and safety.
Originality/value
This novel prototype has automated safety applications for FM during the asset lifecycle and maintenance phase of a building’s O&M phase of AM. Future work is proposed in several key areas, namely, develop instantaneous indicators of current safety performance within a building; and develop lead indicators of future safety performance of buildings.
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Background: Insurance was discovered many centuries before Christ (BC). In the second and third millennia BC, Chinese and Babylonian traders traded risks. Insurance is now the…
Abstract
Background: Insurance was discovered many centuries before Christ (BC). In the second and third millennia BC, Chinese and Babylonian traders traded risks. Insurance is now the backbone of the economy, but penetration is low in developing countries. Big data, internet of things (IoT), and InsurTech have recently ushered in the fourth industrial revolution in insurance.
Objective: This study examines the Indian challenges and solutions of using Big Data Analytics (BDA).
methodology: A SLR was used to extract themes/variables related to challenges and solutions in adopting BDA in the Indian insurance sector. Google Scholar was searched for relevant literature using keywords. Inclusion and exclusion criteria were used to filter the studies.
Findings: This study identified several barriers to BDA adoption in the Indian insurance industry. Policymakers could use the suggestions to improve insurance service delivery.
Practical implication: Insurers can understand the challenges, and accordingly, they can adopt the proposed solution in this study to enhance the insurance penetration in India.
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