CHAPTER ONE
INTRODUCTION TO WIRELESS SENSOR NETWORK
A Wireless Sensor Network (WSN) can be defined as a group of independent nodes, communicating wirelessly over limited frequency and bandwidth [1]. The novelty of WSNs in comparison to traditional sensor network is that they depend on dense deployment and coordination to execute their task successfully.WSNconsists of spatially distributed autonomoussensors to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, humidity, motion or pollutants and to cooperatively pass their data through the network to a main location[2]. The more modern networks are bi-directional, also enabling control of sensor activity. Generally, a WSN is composed of a large number of sensor nodes that are deployed outdoor at random (e.g., by dropping them from an aircraft) in a field [3]. Reports transmitted by these sensors are collected by base stations. It is essential to know the node location in many applications of WSN such as target tracking, event location reporting, geographic routing and directional querying. Determining the physical locations of sensor nodes after they have been deployedis known as the problem of localization [5].
1.1 Characteristics of wireless sensor network
The main characteristics of a WSN include
Power consumption constrains for nodes using batteries or energy harvesting
Ability to cope with node failures
Mobility of nodes
Communication failures
Heterogeneity of nodes
Scalability to large scale of deployment
Ability to withstand harsh environmental conditions
Ease of use
Power consumption
The basis of this research is location of node of sensors in a wireless sensor network.The location refers to coordinates which describe each node in the network as shown in figure 1.
Figure 1: Node in a wireless sensor network
These location coordinates to be estimated may be either physical location or data location:
• Physical Location: The sensor’s physical coordinates, that is, where it exists in space, are estimated.
• Data Location: Non-physical coordinates for the sensor’s measured data are estimated.
These coordinates describes where, in a particular space, the measured data vector lies.
Estimating a sensor’s physical coordinates is intuitively important: when sensor data is reported, it should be accompanied with an indication of where in space that data was recorded. Data location coordinates are made necessary by the bandwidth and energy limitations of a network. In such sensor networks, large quantities of sensor data are recorded and are available, but typically are not sent through the network, due to the communication constraints. Instead, summary statistics may be typically communicated, and occasionally when the situation requires it, full data is sent. Data coordinates are a summary statistic, a lower-dimensional representation of the full data available, which preserve information about the relationships between sensors’ data. Automatic estimation of physical location of the sensors in these wireless networks is a key enabling technology. The overwhelming reason is that a sensor’s location must be known for its data to be meaningful. If a system is set up to respond locally to changes in sensor data, then it must know where those changes are occurring. Inmany cases, location itself is the data that needs to be sensed. Localization can be the driving need for wireless sensor networks in applications such as warehousing and manufacturing logistics, in which radio tagged parts and equipment must be able to be accurately located at all times. Also, sensor location information, if it is accurate enough, can be extremely useful for scalable, ‘geographic’ routing algorithms.
To make these applications viable with possibly vast numbers of sensors, device costs will need to be low, sensors will need to last for years or even decades without battery replacement, and the network will need to organize without significant human moderation. Traditional physical localization techniques such as Global Positioning System (GPS) and Local Positioning System (LPS) are not well suited for this requirement, GPS is the most popular localization system with relatively high accuracy, but it may not be realistic to equip each node in a WSN with GPS due to cost, form factor, energy consumption, and some other restrictive conditions [6]. So, several other localization schemes, classified into two categories, which are:
range-based and
range-free
GPS on each device is cost and energy prohibitive for many applications, not sufficiently robust to jamming for military applications, and limited to outdoor applications. Local positioning systems (LPS) rely on high-capability base stations being deployed in each coverage area, an expensive burden for most low configuration wireless sensor networks.
In this research, I assumed that the monitored area is planar, i.e. the elevation difference among the nodes can be ignored thus the nodes distance from the control node is measured in two dimensions (2D). The technique of localization used in this research for node location computation technique is called the Modified Linear Intersection (MLI) for quick localization in a localization scheme based on local distance measurement. MLI is a routine method used for control point densification in surveying engineering. It is applied in localization for WSN and some experiments to estimate its usability are given.
1.2 APPLICATIONS OF WIRELESS SENSOR NETWORKS
Some of the exciting characteristics of WSN are given as below:
1.2.1 Area monitoring
Area monitoring is a common application of WSNs. In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored. A military example is the use of sensors to detect enemy intrusion; a civilian example is the geo-fencing of gas or oil pipelines.
When the sensors detect the event being monitored (heat, pressure), the event is reported to one of the base stations, which then takes appropriate action (e.g., send a message on the internet or to a satellite). Similarly, wireless sensor networks can use a range of sensors to detect the presence of vehicles ranging from motorcycles to train cars.
1.2.2 Forest fire detection
A network of Sensor Nodes can be installed in a forest to detect when a fire has started. The nodes can be equipped with sensors to measure temperature, humidity and gases which are produced by fire in the trees or vegetation. The early detection is crucial for a successful action of the firefighters; thanks to Wireless Sensor Networks, the fire brigade will be able to know when a fire is started and how it is spreading.
1.2.3 Air pollution monitoring
Wireless sensor networks have been deployed in several cities (Stockholm, London or Brisbane) to monitor the concentration of dangerous gases for citizens. These can take advantage of the ad-hoc wireless links rather than wired installations, which also make them more mobile for testing readings in different areas. There are various architectures that can be used for such applications as well as different kinds of data analysis and data mining that can be conducted.(8)
1.2.4Landslide detection
A landslide detection systemmakes use of a wireless sensor network to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. And through the data gathered it may be possible to know the occurrence of landslides long before it actually happens. This can help in avoiding the disasters caused by earthquakes, hurricanes, etc.
1.2.5 Industrial monitoring
In this section, some of the applications of WSN to the industries are outlined.
1.2.5.1 Machine health monitoring
Wireless sensor networks have been developed for machinery condition-based maintenance (CBM) as they offer significant cost savings and enable new functionalities. In wired systems, the installation of enough sensors is often limited by the cost of wiring. Previously inaccessible locations, rotating machinery, hazardous or restricted areas, and mobile assets can now be reached with wireless sensors.
1.2.5.2 Data Logging
Wireless sensor networks are also used for the collection of data for monitoring of environmental information this can be as simple as the monitoring of the temperature in a fridge to the level of water in overflow tanks in nuclear power plants. The statistical information can then be used to show how systems have been working. The advantage of WSNs over conventional loggers is the "live" data feed that is possible.
1.2.5.3 Industrial sense and control applications
In recent research a vast number of wireless sensor network communication protocols have been developed. While previous research was primarily focused on power awareness, more recent research have begun to consider a wider range of aspects, such as wireless link reliability, real-time capabilities, or quality-of-service. These new aspects are considered as an enabler for future applications in industrial and related wireless sense and control applications, and partially replacing or enhancing conventional wire-based networks by WSN techniques [12].
1.2.5.4 Water/wastewater monitoring
There are many opportunities for using wireless sensor networks within the water/wastewater industries. Facilities not wired for power or data transmission can be monitored using industrial wireless I/O devices and sensors powered using solar panels or battery packs and also used in pollution control board.
1.2.5.5 Agriculture
Using wireless sensor networks within the agricultural industry is increasingly common; using a wireless network frees the farmer from the maintenance of wiring in a difficult environment. Gravity feed water systems can be monitored using pressure transmitters to monitor water tank levels, pumps can be controlled using wireless I/O devices and water use can be measured and
