| Title | Modified Grey Wolf Optimization(GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Majhi, D., Rao, M., Sahoo, S., Dash, S. P., Mohapatra, D. P. |
| Conference Name | 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA) |
| Keywords | Accident, accident deterrence, computerised monitoring, deterrence, grey systems, grey wolf optimization, health conditions, Heart rate, Human Behavior, industrial accidents, Internet of Things, Internet of Things (IoT), Introduction, IoT, mine workers, mining industry, occupational health, occupational safety, optimisation, patient monitoring, Personnel, production engineering computing, pubcrawl, Resiliency, Scalability |
| Abstract | The occurrences of accidents in mining industries owing to the fragile health conditions of mine workers are reportedly increasing. Health conditions measured as heart rate or pulse, glycemic index, and blood pressure are often crucial parameters that lead to failure in proper reasoning when not within acceptable ranges. These parameters, such as heartbeat rate can be measured continuously using sensors. The data can be monitored remotely and, when found to be of concern, can send necessary alarms to the mine manager. The early alarm notification enables the mine manager with better preparedness for managing the reach of first aid to the accident spot and thereby reduce mine fatalities drastically. This paper presents a framework for deterring accidents in mines with the help of the Grey Wolf Optimization approach. |
| DOI | 10.1109/ICCSEA49143.2020.9132882 |
| Citation Key | majhi_modified_2020 |
Modified Grey Wolf Optimization(GWO) based Accident Deterrence in Internet of Things (IoT) enabled Mining Industry