Digital Mine System Training Presentation

1
Digital Mine Using Internet of Things
By
Dr. S.K. Chaulya
Mine Mechanization and Technology Development Group,
CSIR-Central Institute of Mining and Fuel Research
Email: chaulyask@gmail.com

 As per the statistical report of Directorate General of Mines Safety (DGMS)
there were around 2460 fatal accident cases recorded during 1992-2015 in
Indian coal mines in which 2990 miners were died and 446 miners were
injured whereas during the same period around 15991 serious accidents
were occurred in which 16413 miners were injured.
 Further, the major causes of disasters in Indian Underground coal mines
during 1901-2007 were roof fall (57%), side fall (10%), explosion (16%),
inundation (14%) and fire/gas (3%) excluding other causes of mine
hazards.
 Therefore, there is an urgent need for deploying an intelligent system by
integrating IoT-enabled sensors, wireless network and artificial
intelligence for real-time monitoring and prediction of underground
mine parameters causing above hazards and giving audio-visual warning to
the working miners before occurrence of the impending hazards so that
valuable life of miners and mines’ property can be saved.
Accidents in Indian Underground Mines

3
 A digital mine is a simulated version of actual mining
condition in computer screen by transforming physical mine
into a virtual mine.
 Internet of Things (IoT) describes a breadth of devices that
connect to the Internet and that communicate with other
connected devices via wireless networks, and sensors.
 IoT is a network of devices which can sense, accumulate
and transfer data over the internet without any human
intervention.
 The condition of virtual reality is created based on IoT
enable sensors for real-time monitoring and prediction of
fatal accidents and taking precautionary measures in
advance to avoid loss of lives of miners and mine’s property.
Introduction

4
Dimension of Internet of Things

5
Digital Mines using Internet of Things (IoT)

Digital Mine System
– For Efficient and Safe Mining
 Transformation of physical mine into 3D virtual mine
 On-line mine monitoring and prediction of hazards
using IoT-based sensors and AI
 Graphical representation of real-time sensor data,
miners and asset tracking
 Providing audio-visual warning and controlling of
situation using IoT-enabled devices
 Integrated data, voice and video communication
 On-line production monitoring and resource
management

 View 3D virtual mine
 View combination of
datasets
 View miners & assets in
their actual location
 View zone associated with
each sensor
 Predefined path navigation
for miner
 Navigation based on assets,
zones & point of interests
selections
Preparation of 3D Digital Mine
Purpose:

Intrinsically Safe & Flame Proof 3D Laser Scanner
IMAGER 5006EX
of
M/s Zoller+Frohlich, Germany

Steps for formation of 3D digital mine
Formation of 3D Digital Mine
9

 After data processing and analysis phase 3D modeling is
done by geo-referencing and mesh model generation.
 3D Reshaper is a scanner software solution which
processes 3D point clouds.
Point cloud of 3D model of U/G mine
Formation of 3D Digital Mine
3D model of underground mine
10

Setting-up in Underground Mine

Phase – 1: Capture of Information

Digital Mine System Training Presentation

3D walk through model for Chandmari and Victory Mines of Bastacola Area, BCCL

Testing and Certification of the DM System
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Test Indian Standard Testing Laboratory
Frequency and
radiation (ERP) of
antennas
1. IS/IEC 60079: 2007 SAMEER, Kolkata
(MeitY)
Intrinsic safety (IS) 2. IS/IEC 60079-0: 2017
3. IS/IEC 60079-11: 2011
ERTL, Kolkata (MeitY)
Flameproof (FLP) 4. IS/IEC 60079-0: 2017
5. IS/IEC 60079-1: 2014
FLP Lab, CIMFR
Ingress protection
(IP)
6. IS/IEC 60529:2001
(Reaffirmed 2014)
ERTL, Kolkata (MeitY)
Performance test 7. IS/IEC: 60079-35-1: 2011
8. IS/IEC: 60079-35-2: 2011
9. IS 13109 (Part 1) & (Part
21): 1991
MFVMSH Lab, CIMFR
EISTL Lab, CIMFR

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Developed monitoring and prediction software which
includes different modules covering:
(i) Miners tracking, voice and video communication,
(ii) Environment and gas monitoring,
(iii) Strata monitoring,
(iv) Store inventory management,
(v) On-line production and dispatch monitoring,
(vi) Personnel management,
(vii) Fire and explosivity status monitoring,
(viii) On-line form submissions and e-governance,
(ix) Water level monitoring,
(x) Pit and dump slope monitoring, etc.

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Integrated Software Modules

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Wireless Network for Communication of Data, Voice and Video
Uses single Wi-
Fi network for
transferring
sensor data,
voice and video
from different
locations of
underground
mine to a
remote control
room at
surface.
WLAN network (2.4GHz 802.11b/g/n/ac)

26
Sl.
No.
Device name Device No. Type
(IS/FLP/IP)
Purpose
1 Wall receiver for
Miner’s tracking
DM-WR-1 FLP & IP Receiver device for tracking and locating of
miners working in underground mines
2 Cap lamp transmitter
(Miner’s tracking
device)
DM-MT-1 IS & IP Transmitter device for tracking and locating of
miners working in underground mines.
3 Access point for
wireless network
DM-AP-1 FLP & IP For providing a network for voice, video, and
data communication in U/G mines
4 Wireless voice
communication device
DM-VC-1 IS & IP For facilitating full duplex voice communication
as well as broadcasting in underground mines
5 NO2 gas monitoring
device
DM-NO2-1 FLP & IP For real-time monitoring NO2 gas level in
underground mines
6 O2/ H2S/ CO/SO2 gas
monitoring device
DM-O2/
H2S/
CO/SO2-1
FLP & IP For real-time monitoring O2/ H2S/ CO/SO2 gas
level in underground mines
7 CH4 gas monitoring
device
DM-CH4-1 FLP & IP For real-time monitoring CH4 gas level in
underground mines
8 CO2 gas monitoring
device
DM-CO2-1 FLP & IP For real-time monitoring CO2 gas level in
underground mines
9 Water level monitoring
device
DM-WL-1 IS & IP For real-time monitoring water level
accumulated in sump in underground mines
10 Temperature, humidity
and air velocity
DM-THV-1 IS & IP For real-time monitoring of temperature,
humidity and air velocity of ambient
Developed Hardware

27
Sl.
No.
Device name Device No. Type
(IS/FLP/IP)
Purpose
11 Strata monitoring device
(convergence meter and
load cell)
DM-SM-1 FLP & IP For real-time monitoring of strata
conditions in underground mines
12 Display unit DM-DU-1 FLP & IP For displaying real-time data from
different sensors in underground
mines
13 Audio-visual alarm unit “KEM” V-25
(UG)
FLP & IP For providing real-time warning
system in underground mines
14 Video surveillance system DM-CCTV-1 FLP & IP For video communication in
underground mines
15 Portable DC power
supply unit
DM-PPS-1 IS & IP For providing portable DC power
supply system in underground mines
16 Weather monitoring
system (PM10, PM2.5, SO2,
NOx, wind speed, wind
direction, rain gauge)
DM-WEMS-1 NA (for
mine
surface)
Weather and environment monitoring
Developed Hardware
Hardware Software

Gas monitoring system Strata monitoring system Miner’s tracking system
Wireless voice communication system
Digital Mine Devices

Water level monitoring
device
Temperature, air
velocity, and humidity
monitoring device
CCTV
Audio-visual alarm with display Strata monitoring Portable intrinsically safe DC
power supply
Digital Mine Devices

Details of sensors
30
Sl. No. Parameters Sensors Sensor type Measuring
range
A. Environment
1 Temperature Temperature sensor Semiconductor-based
Sensors, Thermistor
Up to 150 C
2 Air velocity Air velocity sensor MEMS Flow Sensor
(Mass flow sensing
method by using heat
wire)
0–4 m/s
3 Humidity Humidity Sensor Resistive 0–99%
B. Gas
4 Methane CH4 sensor Catalytic Oxidation 0–100% LEL
5 Carbon monoxide CO sensor Electrochemical 0–2000 ppm
6 Carbon dioxide CO2 sensor Infrared 0–5%
7 Oxygen O2 sensor Electrochemical 0–25%
8 Hydrogen sulphide H2S sensor Electrochemical 0–200 ppm
9 Nitrogen dioxide NO2 gas sensor Electrochemical 0.3–50 ppm
10 Sulphur dioxide SO2 gas detector Electrochemical 0-20 ppm
C. Strata conditions and water level
11 Load at particular point of roof Load cell Electromechanical Up to 40
tonne
12 Convergence of roof Convergence indicator Electromechanical 0–15 cm

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Gas Monitoring (Different Gas Analysis from live sensor)

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Underground Miners Tacking and Voice Communication System
Router
• Arduino Nano (ATmega2560) &
NodeMCU (ESP8266)
• Rx Frequency : 434 MHz
• Tx Frequency: 2.4 GHz
• Supply voltage: 3-6 V
• Rx Range in open space: 50 m
End device
• Microcontroller IC: ATTINY 85
• RF transmitter frequency: 434 MHz
• Supply voltage: 3-6 V
• Current consumption: 11 mA
• Range : 50 m (line of sight)
• Emergency switches
Miners Tracking Device:

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Wireless Voice Communication Device
 Portable wireless communication device supports full duplex communication,
which allows both miners to speak and listen simultaneously using common
WLAN network (2.4GHz 802.11b/g/n/ac).
 Developed communication device is based on Raspberry Pi 3B+ as
motherboard for voice processing at 1.4 GHz with 1GB DDR2 SDRAM.
 These IP-based communication devices are used to communicate with a
particular miner and also with multiple miners when broadcasting is required.

Technical specification:
SoC: Broadcom BCM2837
CPU: 4× ARM Cortex-A53, 1.2GHz
GPU: Broadcom VideoCore IV
RAM: 1GB LPDDR2 (900 MHz)
Networking: 10/100 Ethernet, 2.4GHz 802.11n wireless
Bluetooth 4.1 Classic, Bluetooth Low Energy
GPIO: 40-pin header, populated
Storage: microSD
Ports: HDMI, 3.5mm analogue audio-video jack, 4×
USB 2.0, Ethernet, Camera Serial Interface
(CSI), Display Serial Interface (DSI)

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Testing of Wireless Routers and Access Points in
an Underground Coal Mine

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Strata Monitoring System
 System uses 4 sensors, namely load cell,
roof convergence sensor, borehole
extensometer, and stress cell for
measurement of strata condition including
load of roof at a particular point, convergence
of roof, bed separation of roof strata, and
stress on pillars.
 These sensors gather real-time data from
underground mine and send to the server
through wireless network.
 Sensor values are checked against a set of
threshold values and then accordingly, the
software based on algorithm generates three
different levels of audio-visual warning
signal with SMS/email, and various reports.

49
The system is capable of
recording and displaying real
time data of different gases:
1. Oxygen,
2. Carbon dioxide,
3. Carbon monoxide,
4. Methane,
5. Sulphur dioxide,
6. Nitrogen dioxide and
7. Hydrogen sulphide.
Other environmental
parameters:
8. Humidity,
9. Temperature, and
10.Air velocity.
Integrated Weather and Environment Monitoring System for
Underground Mine

Gas Monitoring Module: (Node Info..)
50

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Gas Monitoring Module: (Sensor Info..)

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Gas Monitoring Module: (Sensor live data in tabular Info..)
Gas Monitoring Module: (Sensor live data in tabular Info..)

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Gas Monitoring Module: (Sensor live data in Graph Info..)

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Gas Monitoring Module: (Sensor live data in Map Info..)

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Gas Monitoring: (Mine Air Analysis)

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Automated Gas Sampling and Analysis System for Sealed-off Area
 The system consists of data acquisition
system, wireless network, 7 gas sensors
fitted inside a box/chamber, 1 temperature
sensor, 2 solenoid valves and a suction
pump.
 The system monitors 7 gases:
 methane (CH4),
 carbon dioxide (CO2),
 carbon monoxide (CO),
 nitrogen oxide (NO),
 nitrogen dioxide (NO2),
 oxygen (O2),
 sulphur dioxide (SO2),
 hydrogen (H2) and
 hydrogen sulphide (H2S)
 as well as temperature.
 The data is stored in the system as well as
transmitted wirelessly to central server at
surface control room after each 8 hours or as

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Gas Monitoring(Different Gas Analysis from live sensor)

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Gas Monitoring(Different Gas Analysis Manual mode)

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Pit and Dump Slope Monitoring System
A real-time monitoring, prediction, warning system has been developed for pit and
dump slope monitoring in opencast mine using different sensors like:
 Rainfall,
 Extensometer (Crackometer),
 Inplace inclinometer,
 Tiltmeter,
 Piezometer, etc.

Portable Weather and Environment Monitoring Station
CSIR-CIMFR
Monitoring of micro-climatic and
environmental parameters in the pit
surface
Features:
 Monitors hourly micro-climatic
parameters: (i) Wind speed, (ii) Wind
direction, (iii) Temperature, (iv)
Rainfall, and (v) Humidity
 Monitors: (i) PM10, (ii) PM2.5, (iii) SO2 (iv)
NOx, and (v) CO
 Generates monthly, seasonal and
annual average reports
 Creates wind rose diagram and
frequency distribution report
Portable weather station
Purpose:

Displaying Live Sensor Data From Wireless Monitoring System
69

Date and Hour duration Report
71

Displaying All Sensor Value
(Average/Hourly)
72

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Wireless Water Level Monitoring Device
 An IP based water level monitoring module has been developed for
underground mine where water is accumulated in sump and need to be
pumped out at regular intervals.
 This sensor module consist of a ultrasonic sensor and wireless node.
 The software collects information from all the sensor through wireless network.
 When sensor value exceeds its preset threshold limit, it generates alarm.
 Graphical and real-time data are displayed in the central monitoring center
on the surface.

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Fixed and Portable Power Supplies
 Intrinsically safe and flame-proof power supply has been developed for
supplying power supply to wireless devices and sensors by tapping 110 V AC
lighting supply of underground mine to 3-12 V DC as well as with battery
backup in case of power failure.
 Where 110 V power supply line is not available, power supply will be
provided wireless devices and sensors by portable intrinsically power bank
and it will be replaced with another power bank after 1-2 months.
 Charging of the portable power bank will be done at surface control room.

 Personnel Management Module is an interface between Employee
and the Administrator responsible for seamless functioning of an
organization.
 Personnel management portal provides self-management tools to
enable employees to enter their details and update shift information.
 Records the current number of employees according to the
division / department with the automatic updating of figures when
people are employed or leave .
 It aims at improving the efficiency in day to day activity by keeping
employee record and their training status, health record, education
up-gradation records, accident record, rescue record, attendance
and leave record, etc.
Personal Management Module

Personal Management Menu UI Manage Mine UI Manage Mine Shift UI
Employee Attendance
Management UI
Employee Training Management
UI
Employee Rescue Management UI
Personal Management Module - UI

• A system to keep track of inventory.
• Increasing visibility of inventory to all mines
which helps in keeping optimum level of inventory
and avoiding the duplicity of similar items in the
mines.
• This software module helps to make proper
utilization of material, avoiding product overstock,
avoiding missing out-of-stock situations and
minimizing inventory cost.
• Sending automatically alert via SMS and mail to
the concerned person of the respective branch
stores to distribute the required products for
proper utilization of inventory.
• A forecast for demand.
Inventory Management

Inventory Management – Module UI
Add Supplier UI Add Product UI Add Inventory UI
Deduct Inventory UI Distribute Product UI Manage All

Inventory Management – Various Reports UI
View All Products UI Expired Product Report UI
Product About to Out Of Stock
Report UI
Near by Expiry Report UI
Product Utilization Report UI
Alternate Product with Out of
Stock Report UI

On-line Production and Dispatch Monitoring
 Production and dispatch monitoring using weighbridge, weightometer, on-
board weighing system, etc.
 RFID enabled tub/truck/tripper/dumper
 Production of waste material
 Provision for manual entry of production/dispatch using:
 Tub count
 Rail/belt conveyor
 Truck
 Different Production & Dispatch Reports on:
 Daily basis / Monthly basis/ Yearly basis
 Surveillance using wireless camera
87

91
Architecture of AI-based forecasting model

92
Hybrid CNN-LSTM
model for mine
hazards prediction

MHQI prediction using hybrid CNN-LSTM model
A new approach has been used for measuring the miner’s health
quality index (MHQI).
MHQI for the working face of an underground coal consists of two
indexes, namely, mine air quality health index (MAQHI) and heat
comfort index (HCI).
The 80% of the MHQI values have been used for model training
process using hybrid CNN-LSTM model and remaining 20% have
been used for testing.

MHQI prediction using hybrid CNN-LSTM model Contd …
MHQI is divided into 4 health risk zones, namely low, moderate,
high and very high heal risk.
The prediction model processes these results using the developed
prediction of algorithm.
Intelligence system displays the result using graphical user
interface and provide warnings.

Miner’s Health Quality Index

Table 6 MHQI index for underground coal mines (Moridi et al., 2015)
MHQI Health risk
for MAQHI
Health risk
for HCI
Underground mine environment status and warning
message
0–50 Very low Relaxed Underground mine air health is very good. Miners
can do their work most efficiently
51–100 Low Mostly
relaxed
Underground mine air health quality is good. Any
miners can do their regular activity
101–200 Moderate Comfort Underground mine air health is moderate. Only
healthy miners can be allowed to do their activity
201–300 High Discomfort Underground mine air is not safe, so miners should
quickly evacuate their place
301–500 Very high Dangerous Permission to enter the mine/area is strictly
prohibited.
Miner’s Health Quality Index (MHQI)

Schematic diagram of gas monitoring and prediction system
for underground coal mine
Predicts fire and
explosibility status in the
sealed-off area.
The system uses a WSN
which transfers the sensors’
data to the surface control
room.
The UMAP-LSTM predict gas
UMAP and LSTM neural network based fire status and
explosibility prediction in UG coal mine
Uniform Manifold Approximation and Projection (UMAP)

Methodology
(1) Dimension reduction by UMAP; (2) Prediction of gas concentration by LSTM; (3)
Prediction of explosibility and displaying the result in Ellicott's extension graph.

Fire Status prediction result
Day Actual gas sensor data (%) Status of fire
O2 CO CH4 CO2 H2 N2 C2H4 Graham
ratio
Youg ratio CO/CO2 ratio JTR C/H ratio Explosibility
status
Jan. 14 4.4 1.2 2.8 13.04 4.55 74.01 0 7.89 (B.F.) 85.72 (B.F.) 9.20 (A.F.) 0.84 (I.F.) 0.00 (S.H.) P.E.
Jan. 15 4.06 1.22 2.9 13.39 4.7 73.707 0.023 7.89 (B.F.) 86.54 (B.F.) 9.11 (A.F.) 0.85 (I.F) 10.99 (A.F.) P.E.
Jan. 20 3.06 1.36 3 14.21 5.3 73.07 0 8.34 (B.F.) 87.16 (B.F.) 9.57 (A.F.) 0.85 (I.F) 0.00 (S.H.) P.E.
Day UMAP-LSTM predicted gas concentraion (%) Predicted status of fire Predicted
explosibility
status
O2 CO CH4 CO2 H2 N2 C2H4 Graham
ratio
Young ratio CO/CO2
ratio
JTR C/H ratio
Jan. 14 2.948 1.314 3.022 13.308 5.470 73.680 0.006 7.93 (B.F.) 80.28 (B.F.) 9.88 (A.F.) 0.78 (I.F.) 8.31 (A.F.) P.E.
Jan. 16 2.716 1.330 3.118 13.451 5.578 73.463 0.016 7.94 (B.F.) 80.30 (B.F.) 9.89 (A.F.) 0.78 (I.F.) 8.21 (A.F ) P.E.
Monitored data
Predicted data
Key: P.E. - Potential explosive, B.F. - Blazing fire, A.F. - Active fire, S.H. - Spontaneous
heating, and I.F. - Indicative of coal/oil/conveyor fire.

Explosibility prediction in Ellicott's extension graph

101
Field Trial of Devices at Hindustan Copper Limited, Malanjkhand
Copper Project, Balaghat (MP)

102
Digital Mine Field Trial Hardware & Software Architecture
Demonstrated at HCL, MCP

103
 Prepared 2 patent proposals and 2
copyright documents:
1. Patent 1 - Digital Mine using Internet
of Things
2. Patent 2 - Portable Weather and
Environment Monitoring System
3. Copyright 1 - Digital Mine (DM)
Software
4. Copyright 2 - Mine Environment
Monitoring and Prediction (MEMP)
software
 Published a book on “Sensing and
Monitoring Technologies for Mines and
Hazardous Areas”, by Elsevier, USA
(Authors: S.K. Chaulya and G.M. Prasad).
 Paper Publications: 8
IPR Generation

Technology Transferred to 3 Firms for Commercialization:
1. M/s Knowledge Lens Pvt. Ltd., Bengaluru
2. M/s Coresonant Systems Pvt. Ltd., Secunderabad.
3. M/s Optimized Solutions Limited, Ahmedabad

Deployment of the Digital Mine System will facilitates:
 Improvement in safety and production of underground
mines,
 Miners’ tracking,
 Facilitates wireless data, voice and video transmission from
an underground mine,
 Provides 3D digital mine display with mining conditions data,
 Predicts mine hazards in real-time,
 Provides warning of hazards,
 Initiates precautionary measures, etc.
Conclusions

Extra Curriculum Activities
• Carry out practical work on the subject area:
– Thrust on practical work in the respective field
– Assign multidisciplinary project work to small
group in each semester
– Assess the project and award the best
• Undertake industrial or R&D training during
vacation after semester
• Carry out final semester project work seriously
on important topic
• Attend on-line training being organized by
different institutes 107

Extra Curriculum Activities (Contd…)
• Conduct group discussion and debate in the
student club
• Practice speaking in English
• Practice writing paper, patent and copyright
• Prepare for facing interview board:
– Aptitude
– Personality
– Presentation with good PPT
– Practice probable questions and answers
available in the internet
• Prepare for GATE examination 108

109
a) Dey, P., Kumar, C., Mitra, M., Mishra, R., Chaulya, S.K., Prasad, G.M.,
Mandal, S.K., Banerjee, G. (2021) “Deep convolutional neural network based
secure wireless voice communication for underground mine”, Ambient
Intelligence and Humanized Computing, DOI:
https://doi.org/10.1007/s12652-020-02700-w, IF: 7.104.
b) Kumari, K., Dey, P., Kumar, C., Pandit, D., Mishra, S.S., Kisku, V., Chaulya,
S.K., Ray, S.K. and Prasad, G.M. (2021) “UMAP and LSTM neural network
based fire status and explosibility prediction for sealed-off area in underground
coal mine”, Process Safety and Environmental Protection, 2020, DOI:
https://doi.org/10.1016/j.psep.2020.12.019, IF: 6.158.
c) Dey, P., Chaulya, S.K. and Kumar, S. (2021) “Hybrid CNN-LSTM and IoT-
based coal mine hazards monitoring and prediction system”, Process Safety
and Environmental Protection, 2021, 152: 249-263, DOI:
https://doi.org/10.1016/j.psep.2021.06.005, IF: 6.158.
d) Dey, P., Chaulya, S. K., and Sanjay Kumar (2021) “Secure decision tree twin
support vector machine training and classification process for encrypted IoT
data via Blockchain platform”, Concurrency and Computation Practice and
Experience, DOI: 10.1002/cpe.6264, IF: 1.536.
Publications

110
e) Singh P., Singh, V.A., and Chaulya, S.K. (2020) “Numerical analysis of LSPR
based fiber sensor for low refractive index detection”, Optik, 224, 165704,
DOI: https://doi.org/10.1016/ j.ijleo.2020.165704, I.F. 2.443.
f) Singh, P, Chaulya, S.K. and Singh, V.A. (2020) “Development of microwave
radar based periphery surveillance system in a selected mining area”,
Journal of Electromagnetic Waves and Applications, DOI:
https://doi.org/10.1080/09205071.2020, I.F. 1.373.
g) Dey, P., Saurabh, K., Kumar, C., Pandit, D. Chaulya, S.K., Ray, S.K., Prasad,
G.M. and Mandal, S.K. (2021) “t-SNE and variational auto-encoder with a bi-
LSTM neural network-based model for prediction of gas concentration in a
sealed-off area of underground coal mines”, Soft Computing, DOI: https://
doi.org/10.1007/s00500-021-06261-8, I.F. 3.643.
h) Chaulya, S.K., Prasad, G.M., Mitra, S., Mishra, P., Nadeem, M. (2021),
“Development of a digital mine for safe and efficient mining”, BCREC
Engineering & Science Transaction, 2(1): 1-21.
Publications

MHQI for the working face of underground coal mines consists of two
indexes, namely, (i) mine air quality health index (MAQHI) and (ii) heat comfort
index (HCI).
The MAQHI parameters (CO, CO2, CH4, SO2, NO2, and H2S gas
concentration) and HCI parameters (temperature, air velocity, and humidity of
the underground mine) are used to measure MHQI.
Thus, the MHQI is expressed as:
MHQI=0.8(MAQHI)+0.2(HCI)
Miner’s
health
risk
CH4
level (ppm)
CO2
level (ppm)
CO
level (ppm)
H2S
level (ppm)
SO2
level (ppm)
NO2
level (ppm)
Very low 0–1000 0–2000 0–12 0.0–3.0 0.0–2.5 0.0–1.0
Low 1001–2000 2001–3000 13–22 3.1–5.0 2.6–4.0 1.1–2.0
Moderate 2001–4000 3001–4000 23–30 5.1–13.0 4.1–6.0 2.1–3.0
High 4001–5000 4001–5000 31–49 13.1–20.0 6.1–8.0 3.1–4.0
Very high >5000 >5000 >50 >20 >8 >4
Breakpoint of multiple gases inside a mine for MAQHI
Miner’s Health Quality Index

Table 5 MHQI value for different coefficients and gas concentration values
Test
case
CH4
(ppm)
CO
(ppm)
CO2
(ppm)
Temp
(°C)
Humidity
(%)
MAQHI HCI Calculated MHQI
with different
coefficients of
MAQHI and HCI
Actual
MHQI
range as
per
Tables 4
and 6
0.6,
0.4
0.7,
0.3
0.8,
0.2
1 2000 22 3000 34.5 48 100 64.2 85.7 89.2 92.8 51–100
2 2001 23 3001 35 50 112.5 64.8 93.4 97.4 102.9 101–200
3 2270 23 3100 35.2 50 113.5 65.1 94.1 98.9 103.8 101–200
4 2300 23 3150 35.5 51 115 65.4 95.1 100.1 105.0 101–200
5 4000 30 4000 38.2 54 200 70.6 148.2 161.1 174.1 101–200

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