DESIGN OF WIRELESS SENSOR NETWORK FOR MINE SAFETY MONITORING Abdellah Chehri, Wissam Farjow, Hussein. T. Mouftah, Xavier Fernando
School of Information Technology and Engineering, 800 King Edward Avenue Ottawa, Ontario, Canada, K1N 6N5 achehri,
[email protected] Dept. of Electrical and Computer Eng. Ryerson University, 350 Victoria Street Toronto, M5B 2K3 Email: fernando,
[email protected]
ABSTRACT The recent emergence of the sensor networks technology is significantly impacting the capabilities for automated distributed monitoring of environments. The low manufacturing cost of sensors, increased coverage and accuracy in distributed sensing due to their large deployments and their ability to operate in inhospitable terrains has made them an amenable technology for various surveillance and monitoring applications In this paper we evaluate the performance of wireless sensor network technology for underground mine’s safety monitoring. The system is mainly composed of static ZigBee nodes, which are deployed on the underground mine galleries for measuring underground mine parameters such as ambient temperature, fire detection, humidity, level of carbon monoxides etc. The main characteristic of the networks such as the throughput, the received data rate, latency have been evaluated. Index Terms— Wireless Sensor, Monitoring, Mine 1.
INTRODUCTION
Wireless Sensor networks (WSNs) is an emerging technology that has a wide range of potential applications including environment monitoring, military application, ehealth application and smart industrial factories,. Wireless Sensor networks consist of number of nodes that are equipped with processing, communicating and sensing capabilities. Such networks consist of large number of distributed sensor nodes that organize themselves into a multihop wireless network [1]. WSN allow information to be collected with more monitoring points, providing awareness into the environmental conditions that affect overall uptime, safety,
or compliance in industrial environments and enabling agile and flexible monitoring and control systems. These networks collect different critical data from the system or environment and display theses data to the monitoring server. So, the supervisors can, in real time, interpret the data or take immediate action. In addition, with the collected data, they (i.e operational team) get more visibility about the environment. Hence, they will be able to increase the efficiency or prevent accident while reducing the total cost of data acquisition. All of this can add up to a distinct competitive advantage and a head start in the New Industrial Revolution [2], [3], [4]. IEEE 802.15.4/ZigBee defines together a whole protocol stack for a new low-rate wireless network standard designed for automation and control network. The standard is aiming to be a low-cost and low-power solution for systems consisting of unsupervised groups of devices in industrial factories and offices. Expected applications for the ZigBee are building automation, security systems, remote control, remote meter reading and computer peripherals. The ZigBee standard utilizes IEEE 802.15.4 standard as radio layer. The standard low-power solution and network organization abilities make it interesting for the use in security monitoring in underground mines [5]. In this paper we evaluate, via simulation, the performances of IEEE802.15.4/ZigBee sensor network for security and environmental monitoring in underground mine. We are particularly interested in finding out useful metrics to design reliably sensor networks. The reminder of the paper is organized as follows: section II gives an overview of the IEEE 802.15.4 standard. In section III deals with system description. The performance evaluation of the system is given in section IV. Finally, we conclude the paper in section VI.
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2.
ZIGBEEE BASED SENSOR NETWORKS
ZigBee is a wireless network standard which was destined to sensor network applications, control and remote monitoring. The ZigBee is a commercial standard which has been developed from IEEE 802.15.4. It targets low data rate, low power consumption and low cost wireless networking and offers device level wireless connectivity. In fact, ZigBee standard takes a full advantage of a powerful physical radio specified by IEEE 802.15.4, adding logical network, security and application software to the specification [6]. The ZigBee standard is designed for applications that need to transmit small amounts of data while being battery powered so the architecture of the protocols and the hardware is optimized for low power consumption of the end devices [7]. In addition, ZigBee has significantly quicker launching time and lower power consumption, which will lead to a longer battery life-time, than both WLAN and Bluetooth. This is a great advantage when it comes to using ZigBee devices for both long term security and environmental monitoring. The battery life time requirement is essential in order to avoid the necessity of frequent battery changes. Using a ZigBee device with conservative power consumption is both adequate and desirable. The implementation of network topologies has also a great impact on the power consumption. In the ZigBee-based monitoring system, all sensor nodes uses the random access protocol known as the CSMA/CA (Carrier Sense Multiple Access/ Collision Avoidance) medium access control protocol to transmit data between the nodes. The advantage of a random access protocol is the lower system cost coupling with the simplicity of its implementation. ZigBee devices can transmit up to 250 kbs at 2.4 GHz which is sufficient data rate for typical environmental monitoring applications. Each node will encapsulate its sensor data into an 802.15.4 MAC frame and transmit it to the sink node. There are two types of devices defined in the ZigBee architecture. The coordinator is responsible for network establishment, and together with routers, it is responsible for devices joining/leaving the network, network address assignment and routing [8]. The coordinator acts as the administrator and takes care of organization of the network. Typically, a coordinator holds a neighbor table of devices found in the neighborhood. This requires the coordinator to have more memory and processing power. The main issue is usually the memory. An end device represents sensor node in a WSN, which has limited resources and does not allow some of the advanced functions included in the ZigBee standard, due to the fact that it is a low cost end device solution. It is equipped with no routing functionality and supposed to be sleeping a large portion of time with the intent to save power.
3.
SYSTEM DESCRIPTION
Wireless sensor networks are exposed to many technical limitations including available processing power, transmission rate, synchronization rate and robustness of operation, energy and memory constraints, which limit the battery life and local fate storage for in-network processing respectively. When choosing deployment of WSN in underground mine, for mine safety monitoring, it should be necessary to make a compromise between conflicting requirements. First of all, the wireless sensor networks must use flexible, multihop networking that can follow several architectural topologies, to guarantee that network functions with maximum efficiency and reliability. The priority is to insure a robust global network with battery-operated nodes. Therefore, these types of networks are usually developed with the following goals in mind. On one hand, the nodes must be able to communicate with other nodes via a highly reliable radio module that is compatible with the communication protocol of the network, such as, IEEE 802.15.4 standard in our case. On the other hand, the network should be robust to monitor the required measurements, such as temperature for long time. Reliability in a wireless sensor network can be defined in terms of delay profile, delay jitter and information loss rate. Efficiency of a network can be defined as the ratio of information bits to the total transmitted bits. Reliability of a WBAN will depend on physical and MAC layer procedures as well as on the network topology. IEEE 802.15.4 specifies the physical layer and medium access control layer of wireless personal area networks [8]. The reliability of a remote network which is a fixed network will generally be high; however, occasional packet losses may arise due to congestions and buffer overflow. One of main considerations for a remote medical network will be the TCP/IP (Transmission Control Protocol/Internet Protocol) link. To improve the flexibility and reliability of the network, the multi-route topology, where each node is relayed to sink is the suitable choice. So, if a single node, the remitted data can automatically routed through alternate paths. As shown in Figure 1, the sensor nodes deployed in the appropriate areas to collect the environmental data (temperature, oxygen concentration, humidity) or to supervise continuously some parameters to detect possible anomalies like a fires, explosions (gas explosions, dust explosions, premature explosions of charges), toxic gases (Carbon monoxide, Methane), or even a roof failure. These collected data are transmitted to the sink node using multihop routing. After reception, the sink nodes combine its collected data and forward it to the gateway (Wireless Personal Area Networks). Hence, the observer can query for information from the network. Based on this architecture, the underground mine remote monitoring becomes possible.
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Fig. 1: Architecture for WSN in underground mines (the graph is projected on the 2D plane). 4.
4-1 Throughput and Average Reception Ratio Analysis
SIMULATION
Researchers are often interested in evaluating protocols, algorithms, and systems under a variety of scenarios. These scenarios can vary along a large number of axes, such as the scale of the network, the traffic patterns, mobility, external noise and interference, energy constraints, and many others. In this paper we evaluate the performance of WSN for mine safety monitoring using ns-2. We have considered a wide range of network topologies and test-validated the performance of WSN with all considered topologies. Due to the posed space limitation, we present our results for a static network. We set a 100 m x 100 m area to simulate an underground mine gallery. We consider a complex static network configuration with 25 nodes. At the end of the gallery sits the ZigBee coordinator. It also acts as gateway server, collecting data from different sensors. All sensors are static (Fig 2). Each sensor of the system was mounted at different locations. Table 1 lists simulated applications for sensor nodes and corresponding data rates. Transmit power of devices are configured based on the realistic radio map of sensor node [9]. In addition, the propagation model between nodes which are different from general indoor/outdoor models. In fact, the undergrounds mine radio environments are far from ideal, the high density of scatters caused by the rigorous wall with many metal surfaces to block and reflect radio signal [10]. Table 1. Application Parameters Application Temperature Humidity Oxygen Concentration Methane Detection Carbon monoxide Detection
Fig. 2. Deployment of WSN using ns2.
Data Rate 200 bis/sec 200 bits/sec 100 bits/ sec 800 bits/sec 800 bits/sec
Firstly, we evaluate average reception ratio and throughput of the whole network. For all scenarios, we position each WBASN along one certain route to the gateway. The graph of throughput with different packet sizes shows some variation based on packet size. This is expected based on the variation in over the air transmission time of the packets. As more hops are added to the system the throughput decreases. Fig. 3. (a) depicts the throughput for between node and sink for direct link. When sensors are directly connected to the sink, like a star network, almost all packets have reached the destination, exhibiting a throughput up to over 20 Kbps. However, when one more hop is introduced into sink and sensor nodes, network throughput degrades (to 6 Kbps). Average reception ratio shows its largest value, i.e., nearly 100%, when sensors are directly connected to sink (one hop) and tend to be stable when sensors are distanced further away (Fig. 3 (b)). 4 .2 Link Latency Analysis We examine in this subsection how the ZigBee network performs in terms of average delay. Simulation results are shown in Fig. 3. (c). We note the results show a varying of average delay from 0.1 to 0.3 second. This is promising as such a delay is acceptable to most WSN monitoring and security application as well. It is obvious in both Fig. 3 (c) and (b) that larger number of hops results in longer delay (the delay increases as the number of hops increases on the ZigBee link. This is as expected due to the time taken for each router. 4.3 Packet loss vs. number of hop Packet Loss (or Packet Error Rate, PER) can be due to several reasons, such as the congestion of the network, full
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buffers, fails in the reception of packets (e.g. CRC fails, or channel interferences). 4
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The first results show that it is possible to monitor mine from remote locations using the WSN without reasonable delay. In the future, more scenarios will be investigated.
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Fig. 3: Simulation results (a) Throughput Analysis (b) Average Reception Ratio Analysis (c) Link Latency Analysis. The other two main parameters that can affect the PER is the transmitted power and number of hop. By transmitting at different level, we can easily evaluate their impact on PER. Therefore, the experiment was conducted for three transmission power levels 0 dBm, -10 dBm, and -15 dBm. From figure 4 we can see that initially 100 % of transmitted packets are correctly received. This is because the transmitter and sink are within the transmission range. However, when number of hops increase, more packets are dropped. This leads to frequent disconnection between nodes, which cause more packet drops. These dropped packets, spends much less time on route compared to those delivered packets, contribute to smaller averaged delay. 5.
CONCLUSION
IEEE 802.15.4 is a standard that promises great flexibility, low cost, small hardware and low power consumption. And ZigBee is an open standard IEEE 802.15.4 based radio and protocol that supports full mesh networking of up to 65,536 network nodes. The overall goal of this paper was to contribute and help through measurements and simulations towards dimensioning of the sensor networks for environmental monitoring in underground mines. We examined the reliability for both the point-to-point communication and multihop communication using IEEE 802.15.4 standard. These performances are measured in term of delay, throughput and packet error rate.
Fig. 4: Packet loss rate vs. number of hop for different transmission range. REFERENCES [1] K. Holger, A.Willig, “Protocols and Architecture for Wireless Sensor Networks”, John Wiley and Sons, 2005. [2] R. Conant, ”Wireless sensor networks: Driving the New Industrial Revolution”, Industrial Embedded Systems Magazine, Spring 2006. [3] L. K. Bandyopadhyay, S. K. Chaulya, P. K. Mishra, “Wireless Communication in Underground Mines: RFID-based Sensor Networking”, Springer Editions, 2009. [4] A. Chehri, P. Fortier, P.-M. Tardif, ``Deployment of Ad-Hoc Sensor Networks in Underground Mines, Sixth International Conference on Wireless Sensor Networks, WSN 2006, Banff, Alberta, Canada, 3 - 5 July 2006. [5] A. Chehri, H. T. Mouftah, P. Fortier , H. Aniss, “Experimental Testing of IEEE801.15.4 /ZigBee Sensor Networks in Confined Area", IEEE Eighth Annual Conference on Communication Networks and Services Research, Montreal, Québec, Canada, May, 2010. [6] T. Mitsugu “Application of ZigBee sensor network to data acquisition and monitoring“. Measurement Science Review, Volume 9,No. 6, 2009 [7] J. Heo, C. S Hong, S. B, Kang, S. S. Jeon, Wireless Home Network Control Mechanism for Standby Power Reduction. In: Proceedings of the International Conference on Wireless Information Networks and Systems, pp. 70–75 (July 2007). [8] Cuomo, F., Della Luna, S., Monaco, U., Melodia, F.: Routing in ZigBee: Benefits from Exploiting the IEEE 802.15.4 Association Tree. In: IEEE International Conference on Communications, pp. 3271–3276. IEEE Press, New York (2007). [9] https://www.silabs.com/ [10] C. Nerguizian, C. Despins, S. Affes, M. Djadel, ”Radiochannel characterization of an underground mine at 2.4 GHz”, IEEE Transactions on, Wireless Communications, Vol. 4, Issue 5, Sept. 2005, pp:2441 - 2453.
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