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1 – 2 of 2Mariam Moufaddal, Asmaa Benghabrit and Imane Bouhaddou
The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”…
Abstract
Purpose
The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”. The ability of companies to cope with these changes is a key competitive advantage requiring the adoption/mastery of industry 4.0 technologies. Therefore, companies must adapt their business processes to fit into similar situations.
Design/methodology/approach
The proposed methodology comprises three steps. First, a comparative analysis of the existing CPSs is elaborated. Second, following this analysis, a deep learning driven CPS framework is proposed highlighting its components and tiers. Third, a real industrial case is presented to demonstrate the application of the envisioned framework. Deep learning network-based methods of object detection are used to train the model and evaluation is assessed accordingly.
Findings
The analysis revealed that most of the existing CPS frameworks address manufacturing related subjects. This illustrates the need for a resilient industrial CPS targeting other areas and considering CPSs as loopback systems preserving human–machine interaction, endowed with data tiering approach for easy and fast data access and embedded with deep learning-based computer vision processing methods.
Originality/value
This study provides insights about what needs to be addressed in terms of challenges faced due to unforeseen situations or adapting to new ones. In this paper, the CPS framework was used as a monitoring system in compliance with the precautionary measures (social distancing) and for self-protection with wearing the necessary equipments. Nevertheless, the proposed framework can be used and adapted to any industrial or non-industrial environments by adjusting object detection purpose.
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Bohee So and Ki Han Kwon
This study, a narrative literature review, aims to examine the combined benefits of the active and passive use of social media (SM) for well-being (WB), physical and mental health…
Abstract
Purpose
This study, a narrative literature review, aims to examine the combined benefits of the active and passive use of social media (SM) for well-being (WB), physical and mental health during the COVID-19 pandemic.
Design/methodology/approach
A search strategy has been carried out in the databases: Riss, PubMed, Medline, Scopus and Google Scholar, including all the articles published until 19 October 2023.
Findings
SM offers various benefits, including global risk awareness, health information, social connections and support. With the natural increase in physical inactivity due to COVID-19 social restrictions, SM has been identified as an appropriate tool for promoting physical activity (PA) at home to improve health.
Research limitations/implications
It suggests that the combined use of active and passive benefits of SM could potentially play an important role in public health by increasing individuals’ health behaviours. In addition, dissemination, sharing and social interaction of information provided by YouTube can encourage healthy behaviours, contribute to WB, physical and mental health and raise public health awareness.
Originality/value
The findings presented in this study highlight the combined benefits of differentiating the features of SM use. Compared to other SM platforms, YouTube can be used as a useful tool for home-based PA that promotes health by enabling people to remain active and avoid barriers to PA due to social restrictions during the global crisis. In addition, some recommendations from the findings may help protect against potential risks and improve public health outcomes during global crises, such as the COVID-19 pandemic, among the general public using SM.
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