Leveraging IIoT to Improve Machine Safety in the Mining Industry

McNinch, Michael; Parks, David; Jacksha, Ronald; Miller, Aubrey

doi:10.1007/s42461-019-0067-5

Cited by 23 publications

(17 citation statements)

References 6 publications

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“…Sinha et al reported the use of IoT based on ZigBee techniques to actively monitor underground mineworkers and provide immediate assistance during an emergency [ 148 ]. As hundreds of mine workers are shown to be involved in machinery-related injuries routinely, the IoT would provide a highly valuable intelligent machine monitoring system [ 149 ] that could be effectively used in detrimental working conditions. Mishra et al developed and established a Zigbee-based WSN and extended it to IoT with an IP-enabled gateway [ 150 ].…”

Section: Resultsmentioning

confidence: 99%

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Pishgar

Issa

Sietsema

et al. 2021

IJERPH

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Introduction: The field of artificial intelligence (AI) is rapidly expanding, with many applications seen routinely in health care, industry, and education, and increasingly in workplaces. Although there is growing evidence of applications of AI in workplaces across all industries to simplify and/or automate tasks there is a limited understanding of the role that AI contributes in addressing occupational safety and health (OSH) concerns. Methods: This paper introduces a new framework called Risk Evolution, Detection, Evaluation, and Control of Accidents (REDECA) that highlights the role that AI plays in the anticipation and control of exposure risks in a worker’s immediate environment. Two hundred and sixty AI papers across five sectors (oil and gas, mining, transportation, construction, and agriculture) were reviewed using the REDECA framework to highlight current applications and gaps in OSH and AI fields. Results: The REDECA framework highlighted the unique attributes and research focus of each of the five industrial sectors. The majority of evidence of AI in OSH research within the oil/gas and transportation sectors focused on the development of sensors to detect hazardous situations. In construction the focus was on the use of sensors to detect incidents. The research in the agriculture sector focused on sensors and actuators that removed workers from hazardous conditions. Application of the REDECA framework highlighted AI/OSH strengths and opportunities in various industries and potential areas for collaboration. Conclusions: As AI applications across industries continue to increase, further exploration of the benefits and challenges of AI applications in OSH is needed to optimally protect worker health, safety and well-being.

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Section: Resultsmentioning

confidence: 99%

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Pishgar

Issa

Sietsema

et al. 2021

IJERPH

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“…While these accidents seem to be erratic with no structure or pattern, it has been shown that ML approaches can indeed predict these accidents reasonably. As part of Industry 4.0, great emphasis has been placed on the Industrial Internet of Things (IIoT) to provide intelligent solutions based on machine monitoring to improve workplace safety 94 . Thus, the development of automated warning and safety systems for glass industries as part of IIoT can thus enhance workplace safety while ensuring reduced expenses associated with the maintenance of the machinery.…”

Section: Grand Challenges In Glass Science Engineering and Technologymentioning

confidence: 99%

Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21^st century

Ravinder

Venugopal

Bishnoi

et al. 2021

Int J of Appl Glass Sci

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The progress of human civilization has always been closely associated with the discovery of new materials. This is probably why the tripartite classification of historical periods is also based on materials-stone, bronze, and iron age.Beyond these materials, there are several others which have significantly improved the quality of human life, namely, steel, aluminum, glass, plastics, the latest in the list being nanomaterials. Among these materials, glasses hold a unique place in human lives, considering their applications ranging from everyday glass utensils and kitchen-wares to

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“…The proposed scheme utilizes an implicit semi-Markov model (HSMM) to predict the direction of motion with high accuracy and low overhead. A previous work for estimating the direction of a mobile node in an IP-based mobile network was based on AOA (a hardware-specific method) [2]. Compared with similar methods, his scheme has advantages in power consumption, switching delay, and packet loss.…”

Section: Related Content With the Development Of The Internet Ofmentioning

confidence: 99%

“…In the scene with noisy background, the boundary obtained by applying the edge detection algorithm contains a large number of noise points [27]. In order to reduce the influence of noise, we modify the matching cost function of formula (2). In formula (2), if h j ðkÞ is equal to zero and h i ðkÞ is not equal to zero, we discard the difference of this component and redefine the matching distance:…”

Section: Human Target Detection Without Pose Restrictionmentioning

confidence: 99%

Application of Posture Recognition Service System Based on Information Fusion Smart Sensor in Dance Training

Gao

2021

Journal of Sensors

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With the development and extension of the Internet of Things technology, many fields have already involved the Internet of Things technology, and its application in dance training has gradually emerged. In order to guide dance training and solve the hidden dangers of dance training, this article mainly introduces the application of posture recognition service system based on information fusion intelligent sensor in dance training. This article uses human body detection, computer interactive Boosting algorithm calculations and establishes standard dance poses. The difference between the trainer’s posture and the standard posture can be clearly seen on the posture recognition service platform. The error is only less than 5%, and it can also help the trainer find their own mistakes in time. Dance and correct your posture in time, and it can reduce the error rate of difficult dances and reduce the error rate of 10%-20%. In addition, through the survey on the satisfaction survey of the security services of the gesture recognition service platform, the satisfaction rate is as high as 90%. Thereby, while ensuring safe training, the dance quality and level of trainers are improved.

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Leveraging IIoT to Improve Machine Safety in the Mining Industry

Cited by 23 publications

References 6 publications

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21^st century

Application of Posture Recognition Service System Based on Information Fusion Smart Sensor in Dance Training

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Leveraging IIoT to Improve Machine Safety in the Mining Industry

Cited by 23 publications

References 6 publications

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

REDECA: A Novel Framework to Review Artificial Intelligence and Its Applications in Occupational Safety and Health

Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21st century

Application of Posture Recognition Service System Based on Information Fusion Smart Sensor in Dance Training

Contact Info

Product

Resources

About

Artificial intelligence and machine learning in glass science and technology: 21 challenges for the 21^st century