Friday, July 17, 2015

Monitoring Natural and Built Environments Using Wireless Sensor Networks for DRR


Profile of the writer: Dr. Lawrence Materum

Wireless communication technologies that never fail and can withstand any disaster are infeasible to deploy and impractical to design. Instead of making such systems for disaster risk reduction, the desired approach is to design wireless communication systems with acceptable performance levels that have mechanisms that are: (1) proactive—by preventing risks that can cause disasters; and (2) reactive in two ways: (2.1) by recovering from disaster impacts during and after a disaster—this is referred to as resilience; and (2.2) by adapting to different disaster scenarios.

A wireless sensor network (WSN) is a communication system composed of a base station (a.k.a. access point, gateway, collector, aggregator) which collects data from nodes wirelessly.  This WSN is shown in Fig. 1.  The nodes and/or the collector could be fixed or mobile. Each node has at least 1 sensor—sensor node.  A sensor node is a WSN component.  It is a radio transceiving device with at least one sensor. Fig. 2 illustrates hardware implementations of sensor nodes.   

Examples of types of sensors that can be placed in sensor nodes are the following.
1.     Acoustic, sound, vibration
2.     Automotive, transportation
3.     Chemical
4.     Electric current, electric potential, magnetic, radio
5.     Flow, fluid velocity
6.     Force, density, level
7.     Ionizing radiation, subatomic particles
8.     Navigation instruments
9.     Optical, light, imaging
10.  Position, angle, displacement, distance, speed, acceleration
11.  Pressure
12.  Proximity, presence
13.  Thermal, heat, temperature

Examples of position sensors are as follows.

1.     Capacitive sensing
2.     Free fall sensor
3.     Gravimeter
4.     Gyroscopic sensor
5.     Impact sensor
6.     Inclinometer
7.     Inclinometers
8.     LIDAR
9.     Odometer
10.  Photoelectric sensor
11.  Piezoelectric accelerometer
12.  Position sensor
13.  Rangefinder
14.  Rate sensor
15.  Shock data logger
16.  Shock detector
17.  Stretch sensor
18.  Surface velocimeter
19.  Tachometer
20.  Tilt sensor
21.  Ultrasonic thickness gauge
22.  Variable reluctance sensor
23.  Velocity receiver

On the other hand a collector is another WSN component.  It could also serve as a sensor node, but it functions as the gateway for coordinating data transmission/reception in the network.  Potential sensor node locations are in the following. 
In natural environments:
1.     Bodies of water—for sensing: flood, tsunami, …
2.     Soils—for sensing: landslides, quakes, …
3.     Air—for sensing: pollution, airborne microbes, …

In built environments
1.     Water supply—for sensing: quality, leaks, …
2.     Energy grid—for sensing: damages, supply,
3.    Bridges, roads, dams, plants, hazardous scenes., etc.—for sensing: safety, compliance, traffic, fires, gas leaks, …

There are three important requirements for WSNs being deployed for disaster scenarios.These are: (1) long-range—the collector must receive data from the farthest 
sensor node at a reasonable time; (2) low power—sensor nodes must consume very
minimal amount of power such that its battery should last at least ten years; (3) sufficient
 —sensor nodes must be placed sufficiently to obtain appropriate data. The long-range
 feature is usually handled at the antenna and at the setting of the maximum allowable
 transmit power (to avoid interference).  The low-power requirement depends on the
 amount of processing and the environment where the sensor node is placed.  For the
 requirement for sufficiency, it remains as one large open problem since it could be 
scenario-specific. So generalizing such scenarios may not be straightforward.

Challenges to researchers: Here problems that have been left unaddressed as to the authors’ knowledge are presented as follows.

1.     In natural and built environments, how do you position the nodes in order to have sufficient data for each of the following mechanisms?
a.     Prevention of disaster risks
b.     Recovery from disasters
c.     Adaptation to different disaster scenarios

2.     If a fraction of the nodes are broken during a disaster, what node data sampling process would lead to an accurate assessment of the desired mechanisms ?



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