2021
DOI: 10.1109/access.2021.3050193
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iWorksafe: Towards Healthy Workplaces During COVID-19 With an Intelligent Phealth App for Industrial Settings

Abstract: The recent outbreak of the novel Coronavirus Disease (COVID-19) has given rise to diverse health issues due to its high transmission rate and limited treatment options. Almost the whole world, at some point of time, was placed in lock-down in an attempt to stop the spread of the virus, with resulting psychological and economic sequela. As countries start to ease lock-down measures and reopen industries, ensuring a healthy workplace for employees has become imperative. Thus, this paper presents a mobile app-bas… Show more

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Cited by 71 publications
(19 citation statements)
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“…This has been possible due to the recent developments of artificial intelligence (AI) and machine learning (ML)-based tools and techniques which have also been applied successfully to other tasks such as anomaly detection [12][13][14], biological data mining [15,16], cyber security [17], disease detection [18][19][20], earthquake prediction [21], financial prediction [22], text analytics [23,24] and urban planning [25]. Several AI and ML driven approaches have been developed to support COVID-19 [26] through analyzing lung images acquired by means of Computed Tomography (CT) [9], CXR [11] [27], safeguarding workers in workplaces [28], identifying symptoms using fuzzy systems [29], and supporting hospitals using robots [30]. Many of the proposed solutions are based on computationally extensive deep learning (DL) models which are highly complex in nature and often have unreasonable computational costs.…”
Section: Introductionmentioning
confidence: 99%
“…This has been possible due to the recent developments of artificial intelligence (AI) and machine learning (ML)-based tools and techniques which have also been applied successfully to other tasks such as anomaly detection [12][13][14], biological data mining [15,16], cyber security [17], disease detection [18][19][20], earthquake prediction [21], financial prediction [22], text analytics [23,24] and urban planning [25]. Several AI and ML driven approaches have been developed to support COVID-19 [26] through analyzing lung images acquired by means of Computed Tomography (CT) [9], CXR [11] [27], safeguarding workers in workplaces [28], identifying symptoms using fuzzy systems [29], and supporting hospitals using robots [30]. Many of the proposed solutions are based on computationally extensive deep learning (DL) models which are highly complex in nature and often have unreasonable computational costs.…”
Section: Introductionmentioning
confidence: 99%
“…Artificial intelligence has been used for analysis of patterns and classification in diverse fields such as, anomaly detection [ 29 , 36 – 44 ], biological data mining [ 45 , 46 ], disease detection [ 47 – 58 ], monitoring of human [ 59 – 62 ], financial forecasting [ 63 ], image analysis [ 64 , 65 ], and natural language processing [ 66 68 ]. Most of the time, these algorithms are composed of multiple layers of neurons for processing of non-linear information and were inspired by how the human brain works.…”
Section: Methodsmentioning
confidence: 99%
“…On the other hand, AI and Machine Learning (ML) techniques are notable for their predictive abilities in a number of fields such as anomaly detection [30]- [33], biological data mining [34], [35], cyber security [36], disease detection [37]- [45], earthquake prediction [46], elderly care [47], [48], elderly fall detection [49]- [51], financial prediction [52], safeguarding workers in workplaces [53], text analytics [54], [55], and urban planning [56].…”
Section: Introductionmentioning
confidence: 99%