Ensuring safety and a healthy environment at the workplace in underground coal mines is very important as it is directly related to the life and health of the workers. There have been unfortunate accidents in which casualties occurred due to explosions and burial mine accidents in the human race. In particular, major risk factors related to mine ventilation include harmful gas, explosive gas, dust, temperature, humidity, and radiation. Many theories and models have been designed and implemented to minimize the coal mine accidents
In domestic underground coal mines, many mines are deeply deteriorated due to over-mine. As a result of which safety-related issues may not be provided in the mine and collapses which cause accidents. In addition, pollutants such as exhaust gas generated by the movement of diesel vehicles, equipment during working hours, and post-blast gas generated after blasting work are continuously emitted in underground mines. Also, harmful gas is above the standard value due to the poor ventilation system inside the mine
Parameters |
WPAN |
WLAN |
||
UWB |
Bluetooth |
Zigbee |
Wi-Fi |
|
Communication distance (m) |
<10 |
10 |
50-500 |
50-100 |
Frequency range (GHz) |
3.1-10.6 |
2.4 |
2.4 |
2.4 or 5 |
Data rate (Mbps) |
100-500 |
1 |
0.25 |
11 |
Network capacity (nodes) |
10-500 |
7 |
65,536 |
32 |
Power consumption (mW) |
30 |
1-100 |
20-40 |
500-1000 |
Complexity |
Mid-High |
High |
Low |
High |
Usage in Domestic Mine |
O |
X |
X |
O |
Establishing an environmental monitoring system using a wireless sensor network in an underground mine, with a relatively small amount of data transmission, requires long-distance communication and an extensive network in a long-extended mine shaft. Considering these aspects, Zigbee has been chosen as a communication technology scheme to investigate the coal mine steady. In this steady, a real-time model for underground coal mine has been developed to monitor the Coal Mine situation continuously using wireless Sensors and Zigbee technology. Moreover real time data from wireless sensors has been continuously analyzed to get current threshold limit of data, accordingly safety alert system can be activated to improve the safe working conditions In all the above presented approaches very less or no attention was given towards real time environmental data, No doubt few models
The rest of the paper is organized as follows, in section 2 we describe the methodology of the proposed approach, in section 3 we present results and discussion, furthermore we conclude our paper in section 4.
In the presented approach we follow Zigbee devices with a star topology to build a wireless sensor network. As each node has the advantage of being able to configure in a mesh topology that can be a router, end device, and a full-function device setting as a coordinator. The hardware used in this study consists of a coordinator, a router, and an end device. First of all, the coordinator is a network manager that has only one in each Zigbee network. It is located at the center point of the entire network and becomes the backbone for data transmitted from lower routers and the end devices; it stores the network information and delivers commands to the desired sensor node. So to select the appropriate sensor and process the date between end nodes, three different sections have been chosen to achieve the goal of coal mine safety i.e. i) Selection of Sensors ii) Hardware Configuration and iii) Software Configuration
The sensors used in the Zigbee end device module were selected by referring to the Mine Safety Technical Data Standards and the sensor performance. Various Sensor characteristics that play a critical role in coal mine safety are summarized in
Parameters |
CP-11 |
BW Max XT II |
|||
CO2 |
Temp & Hum |
CO |
O2 |
H2S |
|
Working voltage (V) |
3.4~6.4 |
4.5~5.5 |
3.5~5.5 |
3.5~5.5 |
3.5~5.5 |
Working Temperature (°C) |
-30~40 |
-30~50 |
-30-50 |
-30-50 |
-30-50 |
Working Humidity (RH%) |
15-85 |
15-90 |
15-90 |
15-90 |
15-90 |
output method |
analog voltage signal |
digital signal |
analog voltage signal |
analog voltage signal |
analog voltage signal |
Measuring range |
0-50 PPM |
Temp: -40~80°C Hum: 0~99.9 RH% |
0-100 PPM |
0-80% |
0-100 PPM |
Resolution |
part per billion (ppb) Scale |
1ppm |
part per billion (ppb) Scale |
0.1% Level |
part per billion (ppb) Scale |
Here the selection of sensors is based on the requirement for the safety of working people in the mine. So keeping various safety issues in mind the sensors used to measure activity are noxious gas types such as carbon monoxide (CO), carbon dioxide ({CO2), Hydrogen sulphide (H2S), and oxygen (O2) sensors. In addition, temperature, humidity, earth pressure, and water level sensors are also installed in the module.
Gases |
TLV-TWA |
TLV-STEL |
TLV-C |
Carbon dioxide (CO2) |
0.5% |
3.0% |
1.5% |
Carbon monoxide (CO) |
0.005% |
0.04% |
0.02% |
Hydrogen sulfide (H2S) |
10 ppm |
15 ppm |
15 ppm |
Oxygen (O2) |
>19.5% |
- |
- |
As a sensor selection criterion, it is chosen to measure more than the allowable concentration of harmful gases. Currently, only TLV-TWA is selected as the standard in domestic safe technology standards, which is the allowable concentration for 8 hours.
In the presented approach we use a coordinator node, a router node, and an end device. Here the coordinator node acts as a network manager in each Zigbee network
Here 3G Modem fulfills our need in all respects as per our requirement, however, one can use 4G and higher modem also by choosing compatible Trans receivers and interface devices.
The role of a router in a Zigbee network is to extend the communication range of the network by relaying data transmission or reception between Zigbee nodes. It also serves as an application that can transmit data to the coordinator node. The router node composes a module with a microcontroller (MCU) and measurement sensor. The Zigbee router module used in this study is shown in
The software employed to operate the above category of hardware devices in the WSN environment is Encardio-rite software and the URL used http://162.168.0.10, in any of the browsers.
Initially, we configure different types of WSN nodes and add necessary sensors into the network to perform simulation results. Information to the added nodes can be checked under the nodes list section of the project window.
In addition, the total data stored in the program can be downloaded as a CSV file whenever required. It can be later utilized for data analysis. Collected data will be interfaced with the Lab View software, a function is developed in which the data is updated to the latest value in the string array corresponding to each sensor and automatically updated in CSV file format.
The data values from the environmental sensor are connected to the end nodes and are received with the monitoring interface program built into the Zigbee gateway. Here we are using LAEERP
Date/time |
CO Level (ppm) |
CO2 Level (ppm) |
H2S Level (ppm) |
O2 Level (%) |
Temp (˚F) |
RH (%) |
Earth Pressure Cell (mV/V) |
7/23/2021 10:16 |
0.57 |
558 |
3.12 |
20.10 |
73.2 |
70.8 |
0.072 |
7/23/2021 11:17 |
0.54 |
558 |
3.14 |
20.20 |
73 |
70.9 |
0.068 |
7/23/2021 12:18 |
0.58 |
558 |
3.24 |
20.80 |
73 |
70.6 |
0.067 |
7/23/2021 13:19 |
0.56 |
558 |
3.45 |
21.00 |
73 |
70.6 |
0.071 |
7/23/2021 14:20 |
0.57 |
556 |
3.11 |
20.40 |
73 |
70.6 |
0.072 |
7/23/2021 15:21 |
0.57 |
555 |
3.29 |
20.92 |
73 |
70.8 |
0.070 |
7/23/2021 16:22 |
0.57 |
558 |
3.22 |
21.06 |
73 |
70.8 |
0.069 |
7/23/2021 17:23 |
0.57 |
558 |
3.24 |
21.20 |
73.2 |
70.9 |
0.068 |
7/23/2021 18:24 |
0.57 |
558 |
3.56 |
21.34 |
73.2 |
71 |
0.072 |
7/23/2021 19:25 |
0.57 |
558 |
3.52 |
21.48 |
73.2 |
70.9 |
0.072 |
7/23/2021 20:26 |
0.57 |
556 |
3.45 |
21.62 |
73 |
70.6 |
0.067 |
7/23/2021 21:27 |
0.57 |
555 |
3.42 |
21.76 |
73 |
71 |
0.071 |
7/23/2021 22:28 |
0.57 |
558 |
3.41 |
21.90 |
73.2 |
70.7 |
0.072 |
7/23/2021 23:29 |
0.57 |
558 |
3.26 |
22.04 |
73 |
70.7 |
0.072 |
7/24/2021 0:30 |
0.58 |
558 |
3.62 |
22.18 |
73.2 |
71.1 |
0.071 |
7/24/2021 1:31 |
0.58 |
558 |
3.12 |
22.32 |
73 |
71 |
0.072 |
7/24/2021 2:32 |
0.58 |
556 |
3.14 |
22.46 |
73 |
70.8 |
0.073 |
7/24/2021 3:33 |
0.58 |
555 |
3.24 |
22.60 |
73 |
70.9 |
0.069 |
7/24/2021 4:34 |
0.58 |
558 |
3.45 |
22.74 |
72.9 |
71 |
0.071 |
7/24/2021 5:35 |
0.58 |
558 |
3.11 |
20.10 |
72.9 |
71.4 |
0.068 |
7/24/2021 6:36 |
0.58 |
558 |
3.29 |
20.20 |
73 |
71.3 |
0.068 |
This demonstrates the necessity of the proposed approach as the real-time data-based decision has to be taken and accordingly safety measures can be implemented in advance.
The network parameters considered for simulation are area of the network is 1500x1500 m2, nodes taken 100, sinks 1, range 100m, packet size 1kbyte, power transmitted 18mw, power received 16mw and buffer size is 256kB.
The overall comparative analysis reveals that the presented approach reduces the error, optimizes the lifetime and energy of the sensor nodes, Furthermore error reduction improves the overall throughput between the end nodes and enhances the performance of the designed system
In this study, a real-time environmental monitoring system using the Zigbee technology model has been developed and implemented for underground coal mines, in which real time sensor data has been collected and analyzed simultaneously to get the current threshold limit of the sensed data and accordingly safety measures have to be taken in advance to reduce coal mine accidents. To run the system smoothly and efficiently a software program has been developed using Lab View software that generates an alert alarm for the working employees in underground coal mines to take desired action of safety in advance. The presented system can be used as a basic building block of the coal mine safety for the research community. The presented model has been validated using Lab View and mat lab.