WIRELESS SENSOR NETWORKA wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location. The more modern networks are bi-directional, enabling also to control the activity of the sensors. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on.

FIG: Typical multi-hop wireless sensor network architecture.

The WSN is built of "nodes" – from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. Each such sensor network node has typically several parts: a radio transceiver with an internal antenna or connection to an external antenna, a microcontroller, an electronic circuit for interfacing with the sensors and an energy source, usually a battery or an embedded form of energy harvesting. A sensor node might vary in size from that of a shoebox down to the size of a grain of dust, although functioning "motes" of genuine microscopic dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few pennies, depending on the complexity of the individual sensor nodes. Size and cost constraints on sensor nodes result in corresponding constraints on resources such as energy, memory, computational speed and communications bandwidth.The topology of the WSNs can vary from a simple star network to an advanced multi-hop wireless mesh network. The propagation technique between the hops of the network can be routing or flooding.In computer science and telecommunications, wireless sensor networks are an active research area with numerous workshops and conferences arranged each year.

TYPES OF WIRELESS SENSOR NETWORKS:There are broadly speaking two types of wireless sensor networking; physical and environmental. They are used to track and monitor heat, pressure, temperature, vibratory movements, movement or pollution level, sound detection, etc.

ELECTRONIC COMPONENTS:A typical sensor network device comprises the following components some of which are optional: power supply, microcontroller, wireless communication, wired communication, sensor, local storage, and real time clock systems. The principal idea is that the sensors are connected to a tiny computer that coordinates the measurement, preprocesses, stores and delivers the information.

The list of electronic components commonly used in sensor network devices:

Microcontrollers Radio Transceivers Sensors Power/Batteries

CHARACTERISTICS: 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 Dynamic network topology Communication failures Heterogeneity of nodes Scalability to large scale of deployment Ability to withstand harsh environmental conditions Ease of use Unattended operation Power consumption

Sensor nodes can be imagined as small computers, extremely basic in terms of their interfaces and their components. They usually consist of a processing unit with limited computational power and limited memory, sensors or MEMS, a communication device, and a power source usually in the form of a battery. Other possible inclusions are energy harvesting modules, secondary ASICs, and possibly secondary communication devices (e.g. RS-232 or USB).

The base stations are one or more distinguished components of the WSN with much more computational, energy and communication resources. They act as a gateway between sensor nodes and the end user as they typically forward data from the WSN on to a server. Other special components in routing based networks are routers, designed to compute, calculate and distribute the routing tables. Many techniques are used to connect to the outside world including mobile phone networks, satellite phones, radio modems, high power WiFi links etc.

HARDWARE:The main challenge in a WSN is to produce low cost and tiny sensor nodes. There are an increasing number of small companies producing WSN hardware and the commercial situation can be compared to home computing in the 1970s. Many of the nodes are still in the research and development stage, particularly their software. Also inherent to sensor network adoption is the use very low power method for data acquisition.

SOFTWARE:Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs are meant to be deployed in large numbers in various environments, including remote and hostile regions, with ad-hoc communications as key. For this reason, algorithms and protocols need to address the following issues:

Lifetime maximization Robustness and fault tolerance Self-configuration

Some of the important topics in WSN software research are:

Operating systems Security Mobility Usability – human interface for deployment and management, debugging and end-user

control Middleware – the design of middle-level primitives between high level software and the

systems

OPERATING SYSTEMS:Operating systems for wireless sensor network nodes are typically less complex than general-purpose operating systems. They more strongly resemble embedded systems, for two reasons. First, wireless sensor networks are typically deployed with a particular application in mind, rather than as a general platform. Second, a need for low costs and low power leads most wireless sensor nodes to have low-power microcontrollers ensuring that mechanisms such as virtual memory are either unnecessary or too expensive to implement.

It is therefore possible to use embedded operating systems such as eCos or uC/OS for sensor networks. However, such operating systems are often designed with real-time properties.

TinyOS is perhaps the first operating system specifically designed for wireless sensor networks. TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed of event handlers and tasks with run-to-completion semantics.

When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS signals the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later.

LiteOS is a newly developed OS for wireless sensor networks, which provides UNIX-like abstraction and support for the C programming language. Contiki is an OS which uses a simpler programming style in C while providing advances such as 6LoWPAN and proto-threads.

PLATFORMS: Standards and specifications:

Several standards are currently either ratified or under development for wireless sensor networks. There are a number of standardization bodies in the field of WSNs. The IEEE focuses on the physical and MAC layers; the Internet Engineering Task Force works on layers 3 and above. In addition to these, bodies such as the International Society of Automation provide vertical solutions, covering all protocol layer. Finally, there are also several non-standard, proprietary mechanisms and specifications.

Standards are used far less in WSNs than in other computing systems. However predominant standards commonly used in WSN communications include:

WirelessHART ISA100 IEEE 1451 ZigBee / 802.15.4 IEEE 802.11

1.WirelessHART: WirelessHART is a wireless sensor networking technology based on the Highway Addressable Remote Transducer Protocol (HART).

Description:The protocol utilizes a time synchronized, self-organizing, and self-healing mesh architecture. The protocol supports operation in the 2.4 GHz ISM band using IEEE 802.15.4 standard radios. Developed as a multi-vendor, interoperable wireless standard, WirelessHART was defined for the requirements of process field device networks.

The standard was initiated in early 2004 and developed by 37 HART Communications Foundation (HCF) companies that included ABB, Emerson, Endress+Hauser, Pepperl+Fuchs, Siemens and others. The underlying wireless technology is based on the work of Dust Networks' TSMP technology.

WirelessHART was approved by a vote of the 210 member general HCF membership, ratified by the HCF Board of Directors, and introduced to the market in September 2007. On September 27, 2007, the Fieldbus Foundation, Profibus Nutzerorganisation, and HCF announced a wireless cooperation team to develop a specification for a common interface to a wireless gateway, further protecting users' investments in technology and work practices for leveraging these industry-pervasive networks. Following its completed work on the WirelessHART standard in September 2007, the HCF offered ISA an unrestricted, royalty-free copyright license, allowing the ISA100 committee access to the WirelessHART standard.

Backward compatibility with the HART “user layer” allows transparent adaptation of HART compatible control systems and configuration tools to integrate new wireless networks and their devices, as well as continued use of proven configuration and system-integration work practices. It on the estimated 25 million HART field devices installed, and approximately 3 million new wired HART devices shipping each year. In September 2008, Emerson became the first process automation supplier to begin production shipments for its WirelessHART enabled products.

During the summer of 2009 NAMUR, an international user association in the chemical and pharmaceutical processing industries, conducted a field test of WirelessHART to verify alignment with the NAMUR requirements for wireless automation in process applications.

In April 2010, WirelessHart was approved by the International Electrotechnical Commission (IEC) unanimously, making it first wireless international standard as IEC 62591.

2.Isa100.11a: ISA100.11a is an open wireless networking technology standard developed by the International Society of Automation (ISA). The official description is "Wireless Systems for Industrial Automation: Process Control and Related Applications".

The ISA100 committee is part of ISA and was formed in 2005 to establish standards and related information that will define procedures for implementing wireless systems in the automation and control environment with a focus on the field level. The committee is made up of over 400 automation professionals from nearly 250 companies worldwide.

The committee also represents end users, wireless suppliers, system integrators, research firms, consultants, government agencies, and industry consortia. Committee members lend their expertise to the advancement of the ISA100 series of standards.

In 2009, the ISA Automation Standards Compliance Institute established the ISA100 Wireless Compliance Institute also known as the WCI. The ISA100 Wireless Compliance Institute owns the 'ISA100 COMPLIANT' certification scheme and provides independent testing of ISA100 based products to ensure that they conform to the ISA100 standard .

Honeywell Process Solutions offer ISA100.11a compliant starter kits and complete systems. Yokogawa has introduced world's first wireless solution based on ISA100.11a standards including wireless Gateway with pressure and temperature transmitter.

3.IEEE 1451: IEEE 1451 is a set of smart transducer interface standards developed by the Institute of Electrical and Electronics Engineers (IEEE) Instrumentation and Measurement Society’s Sensor Technology Technical Committee that describe a set of open, common, network-independent communication interfaces for connecting transducers (sensors or actuators) to microprocessors, instrumentation systems, and control/field networks. One of the key elements of these standards is the definition of transducer electronic data sheets (TEDS) for each transducer. The TEDS is a memory device attached to the transducer, which stores transducer identification, calibration, correction data, and manufacturer-related information. The goal of the IEEE 1451 family of standards is to allow the access of transducer data through a common set of interfaces whether the transducers are connected to systems or networks via a wired or wireless means.

The 1451 family of standards includes:

1451.0-2007 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Common Functions, Communication Protocols, and Transducer Electronic Data Sheet (TEDS) Formats.

1451.1-1999 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Network Capable Application Processor Information Model.

1451.2-1997 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Transducer to Microprocessor Communication Protocols & TEDS Formats.

1451.3-2003 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Digital Communication & TEDS Formats for Distributed Multidrop Systems.

1451.4-2004 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Mixed-Mode Communication Protocols & TEDS Formats.

1451.5-2007 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Wireless Communication Protocols & Transducer Electronic Data Sheet (TEDS) Formats.

1451.7-2010 IEEE Standard for a Smart Transducer Interface for Sensors and Actuators – Transducers to Radio Frequency Identification (RFID) Systems Communication Protocols and Transducer Electronic Data Sheet Formats.

4. ZigBee:

ZigBee is a specification for a suite of high level communication protocols using small, low-power digital radios based on an IEEE 802 standard for personal area networks. Applications include wireless light switches, electrical meters with in-home-displays, and other consumer and industrial equipment that requires short-range wireless transfer of data at relatively low rates. The technology defined by the ZigBee specification is intended to be simpler and less expensive than other WPANs, such as Bluetooth. ZigBee is targeted at radio-frequency (RF) applications that require a low data rate, long battery life, and secure networking. ZigBee has a defined rate of 250 kbps best suited for periodic or intermittent data or a single signal transmission from a sensor or input device.

Technical overview: ZigBee is a low-cost, low-power, wireless mesh network standard. The low cost allows

the technology to be widely deployed in wireless control and monitoring applications. Low power-usage allows longer life with smaller batteries. Mesh networking provides high reliability and more extensive range. The technology is intended to be simpler and less expensive than other WPANs such as Bluetooth. ZigBee chip vendors typically sell integrated radios and microcontrollers with between 60 KB and 256 KB flash memory.

ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and Australia, and 2.4 GHz in most jurisdictions worldwide. Data transmission rates vary from 20 to 250 kilobits/second.

The ZigBee network layer natively supports both star and tree typical networks, and generic mesh networks. Every network must have one coordinator device, tasked with its creation, the control of its parameters and basic maintenance. Within star networks, the coordinator must be the central node. Both trees and meshes allows the use of ZigBee routers to extend communication at the network level.

ZigBee protocol stack ZigBee builds upon the physical layer and medium access control defined in IEEE

standard 802.15.4 (2003 version) for low-rate WPAN's. The specification goes on to complete the standard by adding four main components: network layer, application layer, ZigBee device objects (ZDO's) and manufacturer-defined application objects which allow for customization and favor total

Besides adding two high-level network layers to the underlying structure, the most significant improvement is the introduction of ZDO's. These are responsible for a number of tasks, which include keeping of device roles, management of requests to join a network, device discovery and security.

ZigBee is not intended to support powerline networking but to interface with it at least for smart metering and smart appliance purposes.

Because ZigBee nodes can go from sleep to active mode in 30 msec or less, the latency can be low and devices can be responsive, particularly compared to Bluetooth wake-up delays, which are typically around three seconds. Because ZigBee nodes can sleep most of the time, average power consumption can be low, resulting in long battery life.

5.IEEE 802.11: IEEE 802.11 is a set of standards for implementing wireless local area network (WLAN) computer communication in the 2.4, 3.6 and 5 GHz frequency bands. They are created and maintained by the IEEE LAN/MAN Standards Committee (IEEE 802). The base version of the standard IEEE 802.11-2007 has had subsequent amendments. These standards provide the basis for wireless network products using the Wi-Fi brand name.

SIMULATION OF WSNS:In general, there are two ways to develop simulations of WSNs. Either use a custom platform to develop the simulation. And the second option is to develop one's own simulation:

Simulators:

As such, at present Agent-based Modeling and Simulation is the only paradigm which allows the simulation of even complex behavior in the environments of Wireless sensors (such as flocking).

Network Simulators like QualNet, NetSim, and NS2 can be used to simulate Wireless Sensor Network. Some AVR-specific simulators, such as Avrora, can also be used to simulate applications written for AVR based platforms, such as MicaZ. Cooja, which is distributed as part of Contiki, can simulate a network of different node types (e.g. Sky (MSP430) or MicaZ (AVR)).

Agent-based simulation of WSN:

Agent-based simulation of wireless sensor and ad-hoc networks is a relatively newer paradigm. Agent-based modelling was originally based on social simulation. A recent article on agent-based simulation published in the IEEE Communications magazine gives examples and tutorials on how to develop custom agent-based simulation models for wireless sensors, mobile robots and P2P networks in a short period of time. A formal agent-based simulation framework using formal specification using Z notation demonstrating the use of agent-based modeling to represent simulation of complex behavior in the environment of sensors is given in. Agent-based simulation has also been shown to be useful for modeling and simulation for quantifying emergent behavior in the vicinity of WSN nodes .

HOW WIRELESS SENSOR NETWORKS WORK??Wireless Sensor Network mechanism is quite simple and applicable to a variety of fields. It is based on Smaller nodes, controller, radio transceiver, and battery. The key to stimulate the sensor networking is the algorithm sponsor multi-router phenomenon. The system is totally dependent on the nodes and the harmony established between them through proper frequency. These nodes are of different sizes according to the function they perform.

To activate the monitoring / tracking function of these nodes a radio transmitter is attached to forward the information in the form of waves. They are controlled by the microcontroller according to the function and device in which they are used. All the system remains in working condition with the help of energy supply which is in the form of battery.  The wireless sensor networks perform function concurrently where nodes are autonomous bodies incorporated in the field spatially for the accurate results. The information transmits through proper channel taking the information collecting it in the form of data and send to the base.

USES OF WIRELSS SENSOR NETWORKS:According to their types they are used by different organizations and fields to monitor a specific task. Wireless sensor networks are incorporated at different point to monitor a specific area a common known example is that of military communication either land or water. Major issues which are becoming a possible threat to life are environmental and industrial issues. Wireless sensor networks are doing great job in the relevant fields to sense to temperature for greenhouse gasses and similarly earthquake detectors are implanted to detect the land sliding phenomenon for precautionary measurements.

Pollution is the major problem of today so is the waste of natural resources. There is great danger of finishing the natural reservoirs. Wireless sensor networks are successfully devised to monitor the water and electricity use. They are used to monitor the waste water in the landfill for cleaning process through landfills and water level detection in the domestic and industrial tanks. Similarly they are used to sense the light and help to consume the daylight properly till the evening and detecting the dim light it automatically switches on the light.  This is permissible at homes,

offices and factories. Machinery health is an important issue to keep the machines in running conditions for a long time. It helps to reduce the need of large labor and cost.

Check and Balance:

The checkers who are tracking and monitoring the wireless sensor network can efficiently monitor the circumstance and can take quick action to balance the situation. In this way they protect the system from being destruction.

User Friendly…Target Killer:

Wireless sensor networks are a source of profit at one place while loss on the other side. Like from the source point of view they provide data information about the location and places and movements while the information taken about agencies suffers. It means they are quite user friendly and helps to kill the victim.

OTHER CONCEPTS IN WSN s : Distributed sensor network:

If a centralised architecture is used in a sensor network and the central node fails, then the entire network will collapse, however the reliability of the sensor network can be increased by using distributed architecture.

Distributed architecture is used in WSNs for the following reasons:

1. Sensor nodes are prone to failure.2. For better collection of data.3. To provide nodes with backup in case of failure of the central node.

Data visualization:

The data gathered from wireless sensor networks is usually saved in the form of numerical data in a central base station. Additionally, the Open Geospatial Consortium (OGC) is specifying standards for interoperability interfaces and metadata encodings that enable real time integration of heterogeneous sensor webs into the Internet, allowing any individual to monitor or control Wireless Sensor Networks through a Web Browser.

Information fusion:

In wireless sensor networks, information fusion, also called data fusion, has been developed for processing sensor data by filtering, aggregating, and making inferences about the gathered data. Information fusion deals with the combination of multiple sources to obtain improved information: cheaper, greater quality or greater relevance. Within the wireless sensor networks

domain, simple aggregation techniques such as maximum, minimum, and average, have been developed for reducing the overall data traffic to save energy.

APPLICATIONS:

The applications for wireless sensor networks are broad. Commercial and industrial applications include monitoring equipment to which it is difficult to attach wired sensors, or in older buildings where it is difficult to retrofit a wired network. Environmental monitoring (e.g., coastal monitoring) applications abound due to the ease of deployment, and the minimal impact on the environment. Sensor networks not only eliminate the need for wires, but also do not typically require large power supplies. Common applications for sensor networks include: environmental monitoring, habitat monitoring, acoustic detection, seismic detection, military surveillance, inventory tracking, medical monitoring, smart space, etc. See e.g. Monitoring biodiversity in dunes, beaches and salt marshes, Instruments and sensors to measure environmental parameters.

FIG: Battlefield Surveillance Chemical, Biological Weapons.

FIG:Habitat exploration of animals.

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.

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.

Forest fires detection:

A network of Sensor Nodes can be installed in a forest to control when a fire has started. The nodes will be equipped with sensors to control 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.

Greenhouse monitoring:

Wireless sensor networks are also used to control the temperature and humidity levels inside commercial greenhouses. When the temperature and humidity drops below specific levels, the greenhouse manager must be notified via e-mail or cell phone text message, or host systems can trigger misting systems, open vents, turn on fans, or control a wide variety of system responses.

Landslide detection:

A landslide detection system, makes 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.

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.

Industrial monitoring 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.

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 wirelessly transmitted back to a central control center for billing. Irrigation automation enables more efficient water use and reduces waste.

Structural monitoring :

Wireless sensors can be used to monitor the movement within buildings and infrastructure such as bridges, flyovers, embankments, tunnels etc... enabling Engineering practices to monitor assets remotely with out the need for costly site visits, as well as having the advantage of daily data, whereas traditionally this data was collected weekly or monthly, using physical site visits, involving either road or rail closure in some cases. it is also far more accurate than any visual inspection that would be carried out.

CONCLUSION:

The flexibility, fault tolerance, high sensing fidelity, low-cost and rapid deployment characteristics of sensor networks create many new and exciting application areas for remote sensing. In the future, this wide range of application areas will make sensor networks an integral part of our lives. However, realization of sensor networks needs to satisfy the constraints

introduced by factors such as fault tolerance, scalability, cost, hardware, topology change, environment and power consumption. Since these constraints are highly stringent and specific for sensor networks, new wireless ad hoc networking techniques are required. Many researchers are currently engaged in developing the technologies needed for different layers of the sensor networks protocol stack.