Indian Journal Of Natural Sciences Vol.5 / Issue 26/ October 2014
www.tnsroindia.org. © IJONS International Bimonthly
ISSN: 0976 – 0997 RESEARCH ARTICLE
Modeling of Wireless Environment Monitoring System for an Industrial Zone like Underground Mines. Partha sarathi Das1*, Tanmoy Maity2 and Yogendra Singh Dohare3 Department of Electrical Engineering,Durgapur Institute of Advanced Technology and Management, Durgapur- 713212, West Bengal, India. 2Department of Mining Machinery Engineering, Indian School of Mines, Dhanbad,Jh-826004, India. 1
Department of Electrical Engineering, Indian School of Mines, Dhanbad,Jh-826004, India.
2
Received: 23 Aug 2014
Revised: 20 Sep 2014
Accepted: 28 Sep 2014
*Address for correspondence Partha sarathi Das C/oBharati Das, Mission compound, Po.Bolpur, Dt.Birbhum West Bengal- 731204, India. E.mail:
[email protected] /
[email protected]. This is an Open Access Journal / article distributed under the terms of the Creative Commons Attribution License (CC BY-NC-ND 3.0) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. All rights reserved.
ABSTRACT
Wireless sensor network (WSN) have a great impact on different activities in the field of engineering. Uninterrupted self-effacing monitoring of the surrounding working environment can be monitored effectively, efficiently, accurately by the use of wireless sensor network. Safety for workers in an industry is of highest priority. The security for costly equipment is another important objective of any industry. This paper introduced a low-cost, energy efficient, reliable scheme for underground mine purpose. We use different sensors for measurement of different parameters inside underground mines and transmit them to the base station in the control room using ZigBee technology. MATLAB based simulation tools have been used to model and analyze the total system. The proposed system can protect the mine workers as well as equipments inside mines. This work concept can be implemented for other purposes like monitoring the environment of hospitals, multistoried buildings etc. Key words: - Pollution, Hospitals, Environment, Wireless sensor network (WSN), Safety, ZigBee, MATLAB.
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ISSN: 0976 – 0997
Partha sarathi Das et al.
INTRODUCTION In underground mines the probability of occurrence of disaster is more. The surroundings inside underground mine is a rough, risky and problematic for the working personal. The underground mines are explosive prone zone. Fire inside underground mines is very dangerous as there is no traditional ways for the fire fighter to stop it. It claims loss of property, lives and even sometimes the total evacuation of the nearby locality. An alarming system should be there inside underground mines for forecasting about possible disaster. The monitoring system should transmit precision measuring data urgently to host system corresponding to the disaster occurrence [1]. Once an explosion happens or fire ignites, massive destruction can result with in a very short duration of time. Time here is a very vital factor for forecasting any possible disaster before it actually happens. Pre disaster precaution is very much necessary in this regard. Pre disaster warning includes measurements of different parameters such as concentration of different gases in different types of mines. For ex. inside coal mines different hydrocarbon gases which are very much flammable are present. Gas monitoring systems is one of the important means for prevention gas explosion in coal mines [2]. Establishing reliable communication is a very difficult task for underground mining due to the extreme environmental conditions [3].The communication system should be fast, accurate, reliable, effective and uninterrupted. The problem of installation of devices is tough inside underground mines. The communication system must be uninterrupted between underground mine workers and base station. The communication network must be position independent of the workers moving inside the mines. Due to geographical disadvantages it is very much difficult, expensive and unreliable to set up wired network communication system inside underground mines. For a wide variety of sensor applications, a fixed wired connection between the sensor and the evaluation unit cannot be established [4]. If there is any roof fall inside underground mines total collapse of communication system may occur. Sensor technology acting as an essential part in this case. Wireless sensor network plays vital role inside underground mines. The sensor nodes sense and observe the events in the environment and the more powerful actors collect and process information from the sensor nodes and react to the events [5]. It is extremely hard to reinstall the wired communication network inside underground mines subsequent to a roof fall or damage due to any reason. Because of roof slide, if several personnel trapped within the territory of underground mines, it is essential to retain the continuity of the communication system network. It is also enormously significant to identify the definite point and condition of the trapped personnel. To supervise supplementary parameters all through this situation it is extremely essential to retain the communication system network normal. The network should have some characteristic functions like self-recovery, autonomous operation and effective data transmission in urgent [6].Wireless sensors have the advantage to be free from restrictions imposed by cables; furthermore, sensors may be placed in desirable locations that might otherwise be inaccessible to wired sensors [7]. Mine monitoring system requires huge use of sensors. Advancement on underground mine monitoring system requires accurate identification of temperature, pressure, vibration, flammable and poisonous gases. A Wireless Sensor Network (WSN) is a self-organized, multi-hop wireless network, composed of a large number of sensor motes, deployed over an area of interest [8]. Different protocol can be used for transmission of data. From an application point of view, Bluetooth is intended for a cordless mouse, keyboard, and hands-free headset, UWB is oriented to high-bandwidth multimedia links, ZigBee is designed for reliable wirelessly networked monitoring and control networks, while Wi-Fi is directed at computer-tocomputer connections as an extension or substitution of cabled networks [9].ZigBee is a low rate, low power consumption wireless communication technology, which can be widely used in the wireless sensor network (WSN)[10]. However the specification was on hand publicly in 2005, scientists, researchers prefer to use this protocol for its many unique advantages. For the effectively, efficiently, continuously, wireless data transmission, in this work the ZigBee protocol is preferred. The low power ZigBee based network system transmits the information gained from different sensors about different parameters like temperature, humidity, levels of different toxic gases etc.
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ISSN: 0976 – 0997
Partha sarathi Das et al.
METHODOLOGY Proposed Wireless Monitoring System A wireless communication is burning requirement today for rapid, precise & flexible safety for mine workers. It can detect surrounding temperature, pressure, flammable, toxic gases, tracking of underground miners, vehicles and other accessories on real-time basis. MEMS based sensors are used for monitoring, measurement of data though digital wireless communication technique, which is having high accuracy. Microcontroller is used for collecting, processing, manipulating data and making decisions as per the algorithm set by the concerned department, based on which mine workers is informed through alarm and voice system.An agent-based wireless local positioning system with ZigBee technology is proposed, mainly for factory level applications[11]. An economical, reliable, accurate ZigBee-based wireless technology for underground mines with warning on different toxic and inflammable gases with change in concentration, change in temperature, humidity, pressure inside is projected in this system. This article is based on the advancement of a scheme integrated to a ZigBee specification. ZigBee specification is incorporated by many manufacturing industry for their products due to its low power utilization and economical development cost. It offers full wireless mesh networking capable of supporting more than 64,000 devices on a single network [12].The system has real-time continuous monitor the underground environment by using a variety of sensors and wireless sensor network. The block diagram of system is shown in Figure 1. Ultra- low power and low cost wireless sensor network consists of coordinator, router and end-devices. ZigBee network requires at least one full function device as a network coordinator, but endpoint devices may be reduced functionality devices to reduce system cost. Coordinator is the main responsible part in the wireless sensor network and it is also responsible for network access and dynamic address assignment. On the one hand, it receives instructions from server computer for network setting and data packets, and alarm indication sends it to surface server system. Perhaps the most straightforward way to think of the ZigBee routing algorithm is as a hierarchical routing strategy with table-driven optimizations applied where possible. A wireless sensor network(WSNs) are typically low data rate, low latency and self-organizing is a randomly spaced array of nodes that provide three functions; the ability to monitor physical and environmental conditions; and the ability to provide efficient, reliable communications. Prototype of wireless sensor network creates by number of motes as shown in Figure 2.Selforganizing networks allow new nodes to join the network automatically, without the need for manual intervention, and are capable of dynamic self-healing; reconfiguring link associations to form alternative pathways around failed or powered-down nodes. The network usually includes a gateway node which bridges the WSAN to upstream networks and user applications
RESULTS MATLAB SIMULATION The function of each sensor networks is described with characteristics in MATLAB/simulation model we use FIGARO USA INC sensors mostly from TGS series sensors for our experimental set ups. Pressure Sensor Model Schematic diagram of pressure sensor modeling and result is shown in Figure 3 and Figure 3a respectively .In pressure sensor model, if surrounding pressure increases above a particular value or if surrounding pressure decreases below a particular value a signal generates. We utilized this signal to generate a particular type of alarm sound and a particular colour of light glows. The MATLAB simulation of the circuit network is shown here. . The signal information from the field will be transmitted to the base station.
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ISSN: 0976 – 0997
Partha sarathi Das et al. CO Sensor Modeling Schematic diagram of CO sensor modeling and result is shown in Figure.4 and Figure.4a respectively. This sensor is used to detect concentration of carbon monoxide (CO) in the ambient temperature. Little fluctuation of the concentration of CO gas leads to change in the resistivity of the sensing element. This change is converted into pulsed voltage by a pulse generator. We utilize this signal to generate a particular type of alarm sound and a particular colour of light glows. The MATLAB simulation of the circuit network is shown here. The signal information from the field will be transmitted to the base station using ZIGBEE technology. Methane Sensor Modeling Schematic diagram of the methane gas sensor modeling and result is shown in Figure 5 and Figure 5a respectively. It is used to detect both carbon monoxide (CO) as well as methane gas. The principal is same as other gas sensors. Changes in the concentration of both gases lead to changes in the resistivity of the sensor element. That property is utilized to vary a voltage source. Suitable calibration method and measurement gives us the information about the concentration of both the gases. We utilized this signal to generate a particular type of alarm sound and a particular colour of light glows. The MATLAB simulation of the circuit network is shown here. CO2 Gas Sensor Modeling Schematic diagram of CO2 Gas sensor modeling and result is shown in Figure 6 and Figure 6a respectively .This sensor is used to measure concentration of carbon di oxoide (CO2) gas in the sorrounding atmosphere.This sensor maintains a linear relationship between changes in concentration of carbon di oxoide (CO2) gas and changes in voltage in lograthmic scale .This is shown in the MATLAB/SIMULINK model. H2S Gas Sensor Modeling Schematic diagram of H2S gas sensor modeling and result is shown in Figure 7 and Figure 7a respectively. If the Hydrogen sulphide gas (H2S) concentration changes, the temperature of the surrounding changes which actually increases the conductivity of the sensor resistance i,e the sensor resistance increases. The Voltage drop across the load resistance (output voltage) increases, suitable calibration method gives us the information about changes in the gas concentration of Hydrogen sulphide gas (H2S) .In our MATLAB simulation the output graph shows the characteristics of the sensor. The signal generates a particular type of alarm sound and a particular colour of light glows. The MATLAB simulation of the circuit network is shown here. Thermal Sensor Modeling Schematic diagram of temperature sensor modeling and result is shown in Figure 8 and Figure 8a respectively. In Temperature sensor SIMULINK model, if the temperature goes above a particular value or if the temperature falls below a particular level a signal generates. We utilized this signal to generate a particular type of alarm sound and a particular colour of light glows. The signal information from the field will be transmitted to the base station using the proposed scheme.
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ISSN: 0976 – 0997
Partha sarathi Das et al.
CONCLUSION Conventional mine security structure can be successfully replaced by the surveillance and safety system projected in the paper. A larger region and additional depth within risky underground mines are currently can be roofed and probable accidents can be controlled successfully. The system combined the low power; low cost Zigbee based wireless data transmission machinery with modern age small size sensors. The sensor and zigbee module can be preferably installed over the helmet of mine worker. Suitable monitoring and dialogue is promising among the employees and the ground personnel who can help to take suitable actions more quickly and smartly. The scheme too can be effortlessly extended with ZigBee wireless representation transmission facility in future; it will advance scalability of underground environment and expand exact position of miners. This work can be implemented in other places like hospitals, multistoried buildings with necessary modification. Monitoring of environment of shopping malls, commercial places, domestic areas can be monitored using this concept with modifications as per geographical locations. This work concept can be used for industry for security purposes. In industry where chemical gases may produce this work concept will be very helpful. This work can be implemented to any city where pollution is more as an environment monitoring system.
REFERENCES 1. Ohbayashi R, Nakajima Y, Nishikado H, Takayama S, editors. Monitoring system for landslide disaster by wireless sensing node network. SICE Annual Conference, 2008; 2008 20-22 Aug. 2008. 2. Aiguo L, Lina S, editors. Multisensor Correlation Analysis and its Application in Coal Mines. Intelligent Systems, 2009 GCIS '09 WRI Global Congress on; 2009 19-21 May 2009. 3. Yarkan S, Gu, x, zelgo, z S, Arslan H, et al. Underground Mine Communications: A Survey. Communications Surveys & Tutorials, IEEE. 2009;11(3):125-42. doi: 10.1109/surv.2009.090309. 4. Pohl A. A review of wireless SAW sensors. Ultrasonics, Ferroelectrics, and Frequency Control, IEEE Transactions on. 2000;47(2):317-32. doi: 10.1109/58.827416. 5. Akbas MI, Brust MR, Turgut D, editors. Local positioning for environmental monitoring in wireless sensor and actor networks. Local Computer Networks (LCN), 2010 IEEE 35th Conference on; 2010 10-14 Oct. 2010. 6. Taenaka S, Akiyama J, Fujiki T, Takayama S, editors. Design of flexible wireless sensing network system for landslide disaster monitoring. SICE Annual Conference (SICE), 2012 Proceedings of; 2012 20-23 Aug. 2012. 7. Sanchez-Azofeifa GA, Rankine C, Marcos do Espirito Santo M, Fatland R, Garcia M, editors. Wireless Sensing Networks for Environmental Monitoring: Two Case Studies from Tropical Forests. E-Science (e-Science), 2011 IEEE 7th International Conference on; 2011 5-8 Dec. 2011. 8. Barrenetxea G, Ingelrest F, Schaefer G, Vetterli M, Couach O, Parlange M, editors. SensorScope: Out-of-the-Box Environmental Monitoring. Information Processing in Sensor Networks, 2008 IPSN '08 International Conference on; 2008 22-24 April 2008. 9. Jin-Shyan L, Yu-Wei S, Chung-Chou S, editors. A Comparative Study of Wireless Protocols: Bluetooth, UWB, ZigBee, and Wi-Fi. Industrial Electronics Society, 2007 IECON 2007 33rd Annual Conference of the IEEE; 2007 5-8 Nov. 2007. 10. Liu Y, Wang C, Qiao X, Zhang Y, Yu C, editors. An improved design of ZigBee Wireless Sensor Network. Computer Science and Information Technology, 2009 ICCSIT 2009 2nd IEEE International Conference on; 2009 811 Aug. 2009. 11. Hing Kai C. Agent-Based Factory Level Wireless Local Positioning System With ZigBee Technology. Systems Journal, IEEE. 2010;4(2):179-85. doi: 10.1109/jsyst.2010.2048653. 12. Patel NASaY. ZIGBEE: A Low Power Wireless Technology for Industrial Applications. International Journal of Control Theory and Computer Modelling (IJCTCM). 2012;2(3):pp 27-33. Epub 33.
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Indian Journal Of Natural Sciences Vol.5 / Issue 26/ October 2014
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 1. Overall block diagram for the proposed system
Figure 2. Prototype of wireless sensor network
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ISSN: 0976 – 0997
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Figure 3. Schematic diagram of pressure sensor modeling using matlab/simulink
Figure 3a.Plotting of voltage vs time for pressure sensor
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 4. Schematic diagram of CO sensor modeling using matlab/simulink
Figure 4a. Plotting of voltage vs time for CO sensor
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 5. Schematic diagram of methane sensor modeling using matlab/simulink
Figure 5a. Plotting of voltage vs time for methane gas sensor
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 6. Schematic diagram of CO2 Gas sensor modeling using matlab/simulink
Figure 6a. Plotting of voltage vs time for CO2 Gas sensor
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Indian Journal Of Natural Sciences Vol.5 / Issue 26/ October 2014
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 7. schematic diagram of H2S gas sensor modeling using matlab/simulink
Figure 7a. Plotting of voltage vs time for H2S gas sensor
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Indian Journal Of Natural Sciences Vol.5 / Issue 26/ October 2014
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ISSN: 0976 – 0997
Partha sarathi Das et al.
Figure 8. Schematic diagram of temperature sensor modeling using matlab/simulink
Figure 8a.Plotting of voltage vs time for temperature sensor
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