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Grant: Collaborative Research and Development Grants

Ryerson University

$80,000.00

A Comprehensive Intelligent Monitoring System for Mines_x000d_ _x000d_

EF 2020-21

Résumé
Every worker's health is influenced by biological, physical, psychological, and other individual traits. This percentage is much higher in the stressful mining sector where work is arduous and often dangerous. No surprise, this workplace fatigue is the primary reason for increased number of various accidents in the mining industry. Every year, the mining industry sees significant losses in terms of human lives and valuable infrastructure due to these incidents. Despite employing only 1% of the global workforce, the mining industry is responsible for approximately 8% of work-related fatalities worldwide (8.2% in Canada). Unfortunately, many of these are preventable. Although technological advancements and tighter regulations have helped in alleviating mining incidents, still the number is too high, especially when over 400,000 worker mostly from remote communities are employed by the mining industry. A human centric approach is necessary to understand the issues and to improve the well-being of miners. This in turn will reduce the number and the impact of occupational hazards in the mining industry. In this project, a comprehensive remote monitoring system will be developed to collect biomedical data from miners in addition to their location and environment data in real time. This multi-sensor data will be fused and Machine learning algorithms will be developed to analyze and interpret the collected data. This will create better understanding of the correlations among miners' ability to function efficiently, environmental factors, their age, work duration and other physiological conditions. The outcome will not only be used to ensure long- and short-term wellbeing of miners, it will also help to alleviate accidents and improve productivity and optimize resource usage in mines. This will be done in collaboration with PBE Canada, a global leader for communication and monitoring systems for mines and tunnels.
Programme
Collaborative Research and Development Grants
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
536337-2018
Name nom
Fernando, Xavier
Department département
Electrical, Computer and Biomedical Engineering
Organization id
43
Institution établissement
Ryerson University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2020
Competition year année de concours
2018
Award amount
80000
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
514
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Communications equipment
Area of application fr
Matériel de télécommunications
Research subject code
2508
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Communications networks
Research subject fr
Réseaux de télécommunications
Installment
inst:2 - 2
Partie
1
Nb partie
2
Application title
A Comprehensive Intelligent Monitoring System for Mines_x000d_ _x000d_
Keyword
NSERC
Application summary
Every worker's health is influenced by biological, physical, psychological, and other individual traits. This percentage is much higher in the stressful mining sector where work is arduous and often dangerous. No surprise, this workplace fatigue is the primary reason for increased number of various accidents in the mining industry. Every year, the mining industry sees significant losses in terms of human lives and valuable infrastructure due to these incidents. Despite employing only 1% of the global workforce, the mining industry is responsible for approximately 8% of work-related fatalities worldwide (8.2% in Canada). Unfortunately, many of these are preventable. Although technological advancements and tighter regulations have helped in alleviating mining incidents, still the number is too high, especially when over 400,000 worker mostly from remote communities are employed by the mining industry. A human centric approach is necessary to understand the issues and to improve the well-being of miners. This in turn will reduce the number and the impact of occupational hazards in the mining industry. In this project, a comprehensive remote monitoring system will be developed to collect biomedical data from miners in addition to their location and environment data in real time. This multi-sensor data will be fused and Machine learning algorithms will be developed to analyze and interpret the collected data. This will create better understanding of the correlations among miners' ability to function efficiently, environmental factors, their age, work duration and other physiological conditions. The outcome will not only be used to ensure long- and short-term wellbeing of miners, it will also help to alleviate accidents and improve productivity and optimize resource usage in mines. This will be done in collaboration with PBE Canada, a global leader for communication and monitoring systems for mines and tunnels.