However this could be analyzed in the future work. The 2. The development environment includes an IDE, evaluation C compiler, software libraries, and a several code example. The software library includes the The kit also includes an adapter for programming and debugging from the IDE environment as shown in Figure 1 b.
This example builds an ad-hoc These topologies are predefined and downloaded first to each node via a USB connector. For our measurements, cluster tree, star and linear topologies were separately adopted. Wireless sensor network is used to transfer the sensor data frames from the sensor unit over a radio interface to the central node. If a radio link can be established between these modules for peer-to-peer communication, the radio modules put each sensor data frame into a radio message, send the message over the radio link, and extract the sensor data frame from the received radio message.
Figure 2 shows that the sensor data are transmitted directly from the sensor node to the central node, which then transmits them to the base station. Node A is the designated master central node in this topology. The network organizes itself and is self-healing, i. The static nodes SN are normally wall-powered and in a fixed known location, however, the mobile nodes MN , which need to be battery-powered.
The system was designed to work under normal conditions. The temperature measurement could for example prevent from fire by continually monitoring of different value. The deployment of sensor nodes in the physical environment may take several forms [ 15 ]. In the case of an underground mine, the deployment may be random unexplored part of mine , at deliberately chosen spots on the top of the gallery or at a fixed position on the gallery walls.
In manual deployment, the sensors are manually placed and the data are routed through predetermined path. The deployment operation may be a one-time activity, where the installation and the use of a sensor network are strictly separate activities. However, deployment may also be a continuous process, with more nodes being deployed at any time during the use of the network, for example, to replace failed nodes or to improve coverage of the network. The WSN has to be able to interact with other information devices, for example, a moving miner equipped with a PDA will be able to read the temperature sensors even if this node is located in different mine gallery.
To this end, the WSN first of all has to be able to exchange data with such a mobile device. This scheme can be generalized to other important security parameter carbon monoxides, or smoke concentration, for example.
Therefore, for the proposed WSN monitoring system, we evaluated the performance and interoperability of sensor network with various networks such as In this scheme, the nodes communicate with the central node, which is connected to a laptop on site.
This last one has the capability of communicating wirelessly with other computers located in a monitoring room via IEEE The number of access points of both WiFi and wireless mesh network should be sufficient to ensure a total coverage of mine gallery.
The system is connected to the Internet through a gateway. The gateways play the role of communication between WSNs and Internet access. So the ambient temperature of a mine gallery can be measured and displayed in real time no matter where we are. The global scheme of WSN mine gallery temperature monitoring is shown in Figure 2. The system was designed to work in a normal condition. The sensors are responsible for monitoring the environment.
When a fire or toxic gas is detected, the mobile sensor can utilize the information reported from sensors and find a shortest path to visit all emergency sites.
Therefore this sensor-based monitoring system could provide real-time emergency-related information. In addition, compared with wire-line solution, the wireless links are able to work in accidents fire or collapse. This huge advantage helps to save miner's life.
We have performed the measurements at the 70 m level. Figure 3 shows an example the node placement in the mine gallery for LOS line-of-sight. In this measurement configuration, the central node remained at a fixed position whereas the slave node was moved at different locations in the mine gallery. The measurements were taken for both static and moving nodes. In this section, we describe some preliminary results of measured link characteristics from the testbed.
Specifically, we discuss some statistics of the wireless link performance in terms of delay, received signal level, link quality indicator and throughput. Figure 4 shows the received signal strength versus the distance. One can observe two regions of path loss. In the first region 1 m to 40 m , signal attenuation is about 40 dB between 1 m and 40 m, which is significant considering that the transmitter and the receiver are in line-of-sight in this case.
However, the second region from 40 m to m is characterized by small signal attenuation. This small attenuation is due to the topology of the gallery. The received signal of a node vs. In fact, this region of the gallery is represented as a narrow corridor in which the multipath adds; therefore the signal can travel a long distance with a small attenuation.
This result agrees with other works, many of which support the use of so-called breakpoint models that employ higher values of the path loss exponent close to the transmitter.
These breakpoint distances called dp are located in the range of 40 meters from the transmitter in the LOC scenario and in the range of 20 meters for NLOS configuration. The average end-to-end latency is the sum of transmission delay and signal sampling time, illustrated in Figure 5. Approximately, the end-to-end latency is a linear function of the payload size. The reason for this is that for a certain data packet size, the signal sampling time is much longer than the packet transmitting time.
The delay increases as the number of hops increases on the ZigBee link. In addition, the variation also increases significantly when there are more hops. However, we do not observe such a strong correlation between distance and link latency though. As shown in Figure 5 , the latency does not increase from 1 m to m. This delay is acceptable to most WSN monitoring applications [ 16 ].
Designing a wireless sensor network for data monitoring in underground mine involves several steps, including the selection of node locations and power assignments. Network performance indicators such as throughput, delay or latency and packet loss of a central node in the target area of a wireless sensor network depend on the received signal strength at the node. These collected data in this paper could help the network designer by providing useful information.
These data are used to modify node locations to ensure adequate coverage for users in the target area of service. The selected network topology and the node separation are also key parameters. The number and distribution of such test points depend upon the size of the underground mine gallery area as well as its physical topology and anticipated number of miners.
Proper selection of preliminary sensor node locations is also important for an effective site survey and design. In this paper, an experimental deployment of a WSN in the underground mine gallery has been described.
The performances of ZigBee sensor networks over real measurement configurations have been presented. Firstly, we evaluate the interoperability of wireless sensor network with various networks such as IEEE In addition, we describe the measured link characteristics from the testbed. Specifically, we discuss some statistics of the wireless link performance in terms of delay, received signal loss, link quality indicator and throughput.
National Center for Biotechnology Information , U. Journal List Sensors Basel v. Sensors Basel. Published online Mar 4. Author information Article notes Copyright and License information Disclaimer.
Abstract Wireless Sensor networks WSNs are created by small hardware devices that possess the necessary functionalities to measure and exchange a variety of environmental data in their deployment setting. Keywords: link-quality, measurement, wireless sensor networks, ZigBee nodes. Introduction In recent years, wireless sensor networks have attracted significant attention due to their integration of wireless, computing, and sensor technology.
The general objectives can be summarized as follows [ 2 ]: Real-time monitoring of gases and other parameters; Monitoring equipment locations and operation statuses to improve productivity and reduce fatal collision accident; Locating and tracking miners in case of disaster for emergency rescue operations; Tracking and monitoring asset equipment; Monitoring miner's unsafe practices and warning; Generally speaking, the measurement of physical parameters makes the sensors the most suitable technology for monitoring and reporting important quantifiable measurements.
Wireless Sensor Network Testbed In this section, an overview of the hardware implementation and the software protocol is given. Hardware Description The Silicon Laboratories 2. Open in a separate window. Figure 1. Software Description The 2. Network Architecture Wireless sensor network is used to transfer the sensor data frames from the sensor unit over a radio interface to the central node. Figure 2. Block diagram of the heterogeneous wireless network deployment.
Dec Posted by rkris. RSSI stands for received signal strength power indication in dBm. A higher value indicates higher power. LQI stands for link quality indicator. The LQI gives an estimate of how easily a received signal can be demodulated by accumulating the magnitude of the error between ideal constellations and the received signal over the 64 symbols immediately following the sync word.
Note that a lower value indicates a better link. The sniffer is adjacent to the FFD. The short addresses of the nodes are listed below. Even though the power levels are so far apart, the LQI signal quality levels are almost the same. This means that the CC was able to demodulate both packets easily since the packet quality was similar.
The LQI of a received packet will be bad higher number when there is lot of interference. Let us take two signals. One is a perfect sine waves with an amplitude of volts and the other is a perfect sine wave with an amplitude of say 10 milli-volts.
If a noise with average amplitude of say 50 volts is mixed with the first signal, you will agree that its quality has now dropped if you saw the mixed signal on a scope. So, even though the second signal has a far smaller amplitude, it has a higher quality compared to the the first signal now mixed with noise.
Suppose node A wants to second a packet to node F and there is no route on A for F. WiSense network layer on A will initiate route discovery to node F. The routing algorithm depends on a route cost metric when evaluating the best route between A and F. The route cost metric can be as simple as the number of hops between A and F. So if multiple routes are discovered during the route discovery process between A and F, the routing algorithm will choose the route with the least number of hops.
The routing cost metric can be more sophisticated if it takes into account the RSSI or LQI or some combination of both to assign each link a cost. The algorithm can then choose the route whose route cost calculated for example by a simple summation of link costs is the least. Why not depend on LQI alone? This means throwing away useful RSSI information.
Why not use both. This sounds like a good idea. Link cost metric is also used when an RFD tries to select a parent node at the time of joining the network.
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