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INDIAN INSTITUTE OF INFORMATION

TECHNOLOGY ALLAHABAD

(A Centre of Excellence in Information Technology Established by Govt. of India)

WSN for Environment Protection Climate Monitoring

A BACHELOR¶S THESIS

Submitted in fulfillment

of the requirements for the award of the degree

of

BACHELOR OF TECHNOLOGY

in

Electronics and communication

(B. Tech ECE)

Submitted by

Puneet Khanna

(IEC2007060)

Under the Guidance of:

Prof. G N Pandey

IIIT-Allahabad

MAY, 2011



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CANDIDATE¶S DECLARATION

I hereby declare that the work presented in this project entitled ³WSN for Environment

Protection ± Climate Monitoring´, submitted in the fulfillment of the degree of

Bachelor of Technology (B.Tech), in Electronics and Communication at Indian Institute

of Information Technology, Allahabad, is an authentic record of my original work carriedout under the guidance of Prof. G N Pandey. Due acknowledgements have been made in

the text of the project to all the other materials used. This project work was done in full

compliance with the requirements and constraints of the prescribed curriculum.

Place: Allahabad

Date: 15-05-11

Puneet Khanna

(IEC2007060)



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CERTIFICATE

This is to certify that the above statement made by the candidate is correct to the best of

my knowledge.

Prof. G N Pandey

Date: 15-05-11

Place: Allahabad

Committee on Final Examination for Evaluation of the project

_______________________

_______________________



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ACKNOWLEDGEMENTS

I would like to take this opportunity to express my deep gratitude to my guide Prof. G N

Pandey, under whose able guidance this work has been done. His valuable suggestions,

constant encouragement and inspiration were of immense help in preparation of the

project. I am also thankful to my colleagues for their feedbacks. Besides, comments and

suggestions of the examining board are welcome as well.

Place: Allahabad Puneet Khanna

(IEC2007060) Date: 15-05-11



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ABSTRACT

This project aims at use of wireless sensor networks for environment protection.

Climate monitoring using sensors gives a huge advantage over other existing methods

to date.

Reliable climate information can help countries plan for adverse and beneficialclimate events, allocate resources, and achieve development goals.

Advances in climate science, including forecasting on seasonal and sub-seasonal

timescales, decadal- scale climate change and variability, real-time climate

monitoring, and tailoring of climate information to specific user needs are creating

opportunities to improve climate risk management, especially in developing countries

where societal needs are greatest.

The use of cables makes the system bulkier, complicating the scalability issue andthus rendering the system costly.

The advantages of using wireless sensor networks include:

y Fully automated data monitoring 24 hours/day, 7 days/week

y Wireless connectivity eliminates the need of cabling

y Efficient even for outdoor use

y Low current consumption



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TABLE OF CONTENTS

1. INTRODUCTION...«««.««««««««««««««««««««7-15

2. LITERATURE REVIEW««««««.««««««««««««««..16-39

3. PLAN OFWORK...««««««««««««««««««««««...40-45

4. RESULT AND FINDINGS«..«««««««««««.«««««««46-57

5. CONCLUSION AND FUTURE PERSPECTIVE««««««««««««..58

6. BIBILOGRAPHY««««««««««««««««««.««««««..59

7. COMMENTS AND SUGGESTIONS«««««««««««««««««.60



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1. INTRODUCTION

1.1. OBJECTIVE

The objective of the project is to use wireless sensor networks for the

protection of the environment. This is achieved by monitoring the temperature and

humidity values using wireless sensors.

1.2. MOTIVATION

The motivation behind this project comes from the fact that existing systems

used for maintaining the temperature and humidity levels are bulky, costly and

create hassles from time-to-time. Also, societal needs have increased.

Thus, a technology which can provide efficient solutions without much cost

or hassle is always preferred.

Climate Monitoring is required in various fields today, so there is a demand

of this technology.

1.3. OVERVIEW

1.3.1. WIRELESS SENSOR NETWORKS

Wireless Sensor Networks (WSNs) 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 development of WSNs was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and

consumer application, such as industrial process monitoring and control, machine

health monitoring, environment and habitat monitoring, healthcare applications,

and traffic control.



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1.3.2. WHYWIRELESS SENSOR NETWORKS

Fundamental objectives of sensor networks are reliability, accuracy,

flexibility, cost effectiveness and ease of deployment.

Key characteristics and benefits of WSN (Wireless Sensor Networks) are

outlined below:

� Sensing accuracy

The utilization of a larger number and variety of sensor nodes provides

potential for greater accuracy in the information gathered as compared to that

obtained from a single sensor.

� Area coverage

This implies that fast and efficient sensor network could span a greater geographical area without adverse impact on the overall network cost.

� Fault tolerance

Device redundancy and consequently information redundancy can be

utilized to ensure a level of fault tolerance in individual sensors.

� Connectivity

Multiple sensor networks may be connected through sink nodes, along with

existing wired networks (e.g. Internet).

The clustering of networks enables each individual network to focus on

specific areas or events and share only relevant information.

� Minimal human interaction

Having minimum human interaction makes the possibility of having less

interruption of the system.

� Operability in harsh environments

Sensor nodes, consisting of robust sensor design, integrated with high levelsof fault tolerance can be deployed in harsh environments that make the sensor

networks more effective.



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1.3.3. CLIMATE MONITORING APPLICATIONS

For decades, museums have kept their thermostats at a steady 21 degrees

Celsius (70 degrees Fahrenheit), with a relative humidity of 50 percent.

Researchers have found that most museum objects can safely tolerate a wider range of both temperature and relative humidity.

In fact, according to the teams research, there can be as much as plus or

minus 15 percent fluctuation in relative humidity and as much as 10C (50 F)

difference in temperature.

Within that range the scientists say, any object ± whether it¶s Leonardo da

Vinci¶s painting ³Mona Lisa´ or an installation of Jeff Koons¶ vacuum cleaners ±

may be safely stored or placed in exhibit.

The researchers¶ insights could save museums, archives and libraries

millions of dollars in construction and energy costs necessary to maintain

environment controls. [10]

Thus, there is a need of monitoring climate changes to prevent such artifacts.

Moreover, climate monitoring is beneficial for the following fields:

y HOSPITAL / HEALTH

Monitoring temperature and humidity is essential in hospitals for drug storage,

vaccine storage, blood bank monitoring, tissue storage, refrigerator monitoring,

laboratory, surgical suites, etc.

y MEDICAL EQUIPMENTS

Monitoring temperature for ovens, refrigerators, packaging, sterilizers,

laboratories, storage, clean rooms, is essential for effectiveness and efficiency.

y FOOD

Ensuring that our food supply is safe is of utmost importance. Monitoring

temperature and humidity can ensure that the food is produced and stored

safely.



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y TRANSPORTATION

Proper storage in any part of the supply chain like temperature controlled

warehouses is important and thus arises a need to monitor temperature.

y MANUFACTURING

Monitoring the production facility, from warehouses to clean rooms, ensures

products are created in safe and controlled environments.

y CONSTRUCTION

Environmental monitoring of construction sites ensures building materials are

stored and utilized properly and safely.

y SCHOOLOn campuses, large or small, everything needs to be monitored from research

labs and building efficiency to student comfort in dormitories.

y AUTOMOBILES

From assembly line to showroom, climate monitoring can ensure proper

production and sale of the inventory.

y PRINTING/ PACKAGINGClimate Monitoring can help protect papers, inks, and other high quality

resources the customers demand.

Thus, climate monitoring finds a wide range of applications and proves to be

a good substitute to the old cable systems. Since the applications of climate

monitoring are vast and varied, the demand of this technology is also huge.

1.3.4. HARDW

AREThe hardware used for monitoring temperature and humidity is TelosB mote.

The TelosB mote platform is an open source, low power wireless sensor module

designed to enable cutting edge experimentation for research community.



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1.3.5. SOFTWARE

The software for sensing is TinyOS. It is an open source component-based

operating system and platform targeting wireless sensor networks (WSNs). Its

applications are written in nesC, a dialect of the C language optimized for

memory limits of sensor networks.

1.3.6. TELOSB MOTE

The Telos module is a low power mote with integrated sensors, radio,

antenna, microcontroller, and programming capabilities.

Fig: CrossBow¶s TelosB mote with integrated temperature, humidity and light sensors [9]

TelosB mote may be powered by two AA batteries. AA cells may be used in

the operating range of 2.1 to 3.6V DC, however the voltage must be at least 2.7V

when programming the microcontroller flash or external flash.

If the TelosB mote is plugged into the USB port for programming or

communication, it will receive power from the host computer.

The mote operating voltage when attached to USB is 3V. If the TelosB mote

is always attached to the USB, no batteries are required.



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The input voltage should never be more than 3.6V or it may damage the

microcontroller, radio or other components.

Fig: TelosB mote

The humidity/temperature sensor is manufactured by Sensirion AG. The

SHT11 sensor is calibrated and produces a digital output. The calibration

parameters are stored in the sensor¶s onboard EEPROM.

For measuring the temperature and relative humidity, Sensirion SHT11 all-round temperature and humidity sensor will be used. SHT11 is Sensirion¶s family

of surface mountable relative humidity and temperature sensors.

The sensors integrate sensor elements plus signal processing on a tiny foot

print and provide a fully calibrated digital output. A unique capacitive sensor

element is used for measuring relative humidity while temperature is measured by

a band gap sensor.

The sensor is produced using a CMOS process and is coupled with a 14-bitA/D converter.

The low power humidity sensor is small in size and may be used for a

variety of applications.[16]



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Fig: Referred from [17]

Sensors measure physical data of the area to be monitored.

We have used a base station node which acts as a bridge between the radio

communication (the network in which we are sensing the reading) and serial

communication (the part in which sensor readings are being send to some PC).

Two other motes are deployed which constantly sense the temperature and

humidity and send the data to the base station.

Fig: Referred from [17]



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1.3.7. Features of TelosB mote [2]

� IEEE 802.15.4 compliant RF transceiver

� 2.4 to 2.4835 GHz, a globally compatible ISM band

� 250 kbps data rate

� Integrated onboard antenna� 8 MHz TI MSP430 microcontroller with 10kB RAM

� 1MB external flash for data logging

� Programming and data collection via USB

� Sensor suite including integrated light, temperature and humidity sensor

� Runs TinyOS 1.1.11 or higher

� Processor Performance - 16-bit RISC

� Program Flash Memory ± 48 Kbytes

� RAM ± 10 Kbytes

� EEPROM ± 16 Kbytes

� Analog to Digital Converter ± 12 bit ADC

� Digital to Analog Converter ± 12 bit DAC

� Current Draw ± 1.8 mA (Active mode), 5.1 uA (Sleep mode)

� Frequency band ± 2400 MHz to 2483.5 MHz

� Transmit Data Rate ± 250 kbps

� RF Power - -24dBm to 0 dBm

� Receive Sensitivity - -90 dBm (min), -94 dBm (typ)

� Outdoor Range ± 75 m to 100 m

� Indoor Range ± 20 m to 30 m

� Humidity Sensor Range ± 0 to 100% RH

� Resolution ± 0.03% RH

� Accuracy ± ±3.5% RH

� Temperature Sensor Range - -40 °C to 123.8 °C

� Resolution ± 0.01 °C

� Accuracy- ± 0.5 °C @ 25 °C

� Weight 0.8 grams� Power Source from USB or 2 AA batteries

1.3.8. APPLICATIONS OF TELOSB MOTE

� Platform for Low Power Research Development

� Wireless Sensor Network Experimentation



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1.3.9. TINYOS

TinyOS is a free and open-source component based operating system and

platform targeting wireless sensor networks.

It is an embedded operating system written in the nesC programming

language as a set of cooperating tasks and processes.

TinyOS is an operating environment designed to run on embedded devices

used in distributed Wireless Sensor Networks.

1.3.10. NESC

All TinyOS code is written in NesC.

NesC (network embedded systems C) is a component-based, event-drivenprogramming language used to build applications for the TinyOS platform.

NesC is a C language with additional components. It consists of one or

more components assembled to form an executable application.

The components in nesC include the following:

a) Modules - provide the implementations of interfaces.

b) Configurations - assemble other components together, connecting interfacesused by components.



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2. LITERATURE REVIEW

The field of wireless sensor networks is relatively new. Wireless sensors can be

used for a lot of applications. A lot of work has been done towards monitoring of

temperature and humidity using various techniques and for varied applications. Someof the research papers which include sensing of temperature and humidity are as

follows:

2.1. Smartening the environment using wireless sensor networks in

a developing country by Pathan, A.-S.K. ; Choong Seon Hong ;

Hyung-Woo Lee ; Dept. of Comput. Eng., Kyung Hee Univ.,

Seoul, 2006 [14]

2.1.1. ABSTRACT

The miniaturization process of various sensing devices has become a reality

by enormous research and advancements accomplished in micro electro-

mechanical systems (MEMS) and very large scale integration (VLSI)

lithography.

Regardless of such extensive efforts in optimizing the hardware, algorithm,

and protocols for networking, there still remains a lot of scope to explore

how these innovations can all be tied together to design wireless sensor networks (WSN) for smartening the surrounding environment for some

practical purposes.

In this paper the prospects of wireless sensor networks are explored and a

design level framework for developing a smart environment using WSNs is

proposed, which could be beneficial for a developing country like

Bangladesh or India.

2.1.2. INTRODUCTION

The notion of smart environment is becoming a reality with the

advancements of various smart technologies. Smart environments represent the

future evolutionary development step for the real world environment of present

time.



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A smart environment, like any conscious organism, relies first and foremost

on sensory data acquired from multiple sensors in distributed locations of real

world. It gathers information about its surroundings as well as about its internal

workings.

In the recent years, an exciting new type of networks has emerged, called

Wireless Sensor Networks (WSN). The deployment of such networks not only

effectively acquires the data from different locations and then distribute to the

management centers but also facilitates other applications for facing disasters and

other environmental issues.

In this paper, we explore the scope to deploy Wireless Sensor Networks for

developing a smart environment especially in Bangladesh to facilitate various

sophisticated systems to face disasters like flood, tsunami, and cyclones as well as

to enhance road traffic monitoring system.

In fact, the notion of smart environment has a great potential for a

developing country like Bangladesh which faces different types of natural

disasters each year.

While some other works focus on specific topics like smart homes, smart

classrooms etc. as a part of smart environment, we explore the promise of

wireless sensor networks for smartening the environment by up-gradation of

various monitoring and warning systems aided with wireless sensing technology.

2.1.3. SMART SENSORS AND WSN

Massive advancements in wireless communications, Micro-Electro-

Mechanical Systems (MEMS), and optics have opened the new chapter of

modern civilization, populated with small, low-power, cost-effective, autonomous

devices, termed sensor nodes, which would pervade our society redefining the way

it is at present.

Sensor nodes are of the combination of sensing and special-purposecomputing devices tied with wireless communications. When networked, such

sensor nodes would build up the part of larger systems, providing data, as well as

performing and controlling multitude of tasks and functions.

Small size and cost of individual sensor nodes would be the key ingredient

for a large number of applications both in ordinary as well as harsh



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environments. Given the utility of sensor networks in environmental data

collection, surveillance, and target tracking, they can aid numerous applications as

their requirements vary along with the time-space-context continuum.

Sensor networks can be used in support of preparation and prevention during

various phases of pre-event, rapid response during the event, and post recovery

along with analysis after the event.

To benefit the environment, in practical, these large number of miniaturized

commodity sensor nodes could be installed, for example in buildings, on roads, in

vehicles, at the riverbanks, or at coastal areas etc.

Deployment of new sensor nodes may take place on demand at any time at

designated locations, referred to as area of interest (AOI) or at random in

specified areas.

Fig: Basic Sensor Architecture [14]

A smart sensor node is a combination of sensing, processing and

communication technologies. The above figure shows the basic architectural

components of a sensor node.

The sensing unit senses the change of parameters, signal conditioning

circuitry prepares the electrical signals to convert to the digital domain, thesensed analog signal is converted and is used as the input to the application

algorithms or processing unit, the memory helps processing of tasks and the

transceiver is used for communicating with other sensors or the base stations

or sinks inWSN.



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Sensors can monitor temperature, pressure, humidity, soil makeup, vehicular

movement, noise levels, lighting conditions, the presence or absence of

certain kinds of objects or substances, mechanical stress levels on attached

objects, and other properties. Their mechanism may be seismic, magnetic,

thermal, visual, infrared, acoustic, or radar.

A smart sensor is also capable of self-identification and self-diagnosis. The

mechanisms of smart sensors work in one of three ways: by a line of sight to

the target (such as visual sensors), by proximity to target (such as seismic

sensors), and by propagation like a wave with possible bending (such as

acoustic sensors).

Sensor networks are predominantly data-centric rather than address-centric.

In such a network, queries are directed to a region containing a cluster of sensor

nodes rather than specific sensor addresses. Given the similarity in the dataobtained by sensors in a dense cluster, aggregation of the data is performed locally.

That is, a summary or analysis of the local data is prepared by an aggregator node

within the cluster, thus reducing the communication bandwidth requirements.

Aggregation of data increases the level of accuracy and incorporates data

redundancy to compensate node failures. A network hierarchy and clustering

of sensor nodes allows for network scalability, robustness, efficient resource

utilization and lower power consumption which are some of the key issues in

WSN.

2.1.4. APPLICATION OFWSN TOWARDS BANGLADESH

By the geographical location in the globe, Bangladesh is very susceptible to

many environmental calamities like, flood, cyclone, tsunami etc.

Good warning systems could effectively help to mitigate the damages

caused by these natural disasters. Hence, the development of wireless sensor

networks to assist meteorologists has a great deal of national importance in

Bangladesh.

Sensor networks provide the ability to gather accurate and reliable

information, to enable early warnings and rapid coordinated responses to

potential threats. This encompasses the ability to save lives throug

environmental monitoring of natural disasters.



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Only proper infrastructure through long term research and implementation of

these technologies can make huge difference in a country like Bangladesh.

Environmental sustainability is of great importance in such geographical

locations in the world, where it could be improved through sensor monitoring, by

protecting valuable resources, and collecting valuable information previously

considered too difficult and too costly.

y Flood andWater Level Monitoring System

y Traffic Monitoring and Controlling

y Environmental monitoring

y Future Steps: Effective Localization scheme and Cost Effectiveness of the

System

2.1.5. CONCLUSION

As technology emerges over the decades, WSN has come to the spotlight for

its unattained potential and significance. Consequently, billions of dollars are being

committed to the research and development of sensor networks in order to address

the operational challenges that are still associated with the large-scale

implementation of sensor networks.

Without having the proper blueprint, no construction manager could put up

any building according to architect¶s intention. Similar approach appliesalmost in everywhere for developing any new system in the society.

This paper is mainly focused on the design level issues provided with a

framework for WSN to be applied on various systems. In case of Bangladesh,

flood and water level monitoring, traffic monitoring, and environmental

monitoring are among the systems having much potential to be aided with WSN,

which would lead the development of a smart environment.

Various smart applications and sophisticated systems could share the same

sensor nodes, deployed around the particular area of interest (AOI) for

performing the job simultaneously.

WSN, the emerging technology makes the possibility of recognizing present

and predicting future in a way not possible in past. A smart environment is to be

regarded as indispensable stage of a real time system for sensing and prevention of

any undesirable occurrence.



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2.2. Don¶t Sweat Your Privacy - Using Humidity to Detect Human

Presence by Jun Han, Abhishek Shah, Mark Luk, Adrian

Perrig, 2007 [11]

2.2.1. ABSTRACT

Sensor nodes are increasingly deployed in many environments. Most of

these nodes feature on-board sensor chips to measure environmental data such

as humidity, temperature and light.

In this paper, it is shown that seemingly innocuous and non-sensitive data

such as humidity measurements can disclose private information such as

human presence.

2.2.2. INTRODUCTION

Sensor networks are generally deployed to measure some characteristics

about a particular environment of interest. The data they gather can then be

analyzed to extract important information regarding the occurrence of events

in that environment.

Some well-known applications of sensor networks include surveillance of

critical infrastructure, tracking of environmental pollutants, measurement of

traffic flows, and climate sensing and control in office buildings and homes.

Sensor networks are tools for collecting information, and an adversary can

gain access to sensitive information either by accessing stored sensor data or

by querying or eavesdropping on the network.

Since sensor networks communicate over a wireless medium, even a remote

adversary can eavesdrop and gain access to the data collected by the network.

The need for privacy of data is evident in applications where sensor networksare deployed to collect personally identifiable information, such as sensing the

location of people in buildings for disaster preparedness.

However, in some environments, an adversary can use seemingly innocuous

data to derive sensitive information other than the data monitored.



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In this paper, one such instance of this problem is discussed. Specifically, it is

shown how seemingly innocuous data such as humidity measurements can be

used to determine human presence or absence in a room. This is shown

because humidity data is not considered to be privacy-sensitive today. Hence,

to reduce cost, the sensor networks monitoring humidity data will likely to be

unprotected, and the data collected throughout such system might be shared

freely without regard to privacy concerns.

The present work, however, overturns this conventional wisdom by

demonstrating that humidity data, is in fact, privacy-sensitive, since it yields

information about human presence. Several experiments using Moteiv Telos

motes running TinyOS are conducted and the results from these experiments

justify the claims.

It may be argued that an adversary could collect such personal informationdirectly through site surveillance. However, as prior work points out, the main

privacy problem posed by sensor networks is not that they facilitate the

collection of information that would otherwise be impossible, but that sensor

networks aggravate the privacy problem by making important information

easily available through remote access.

Hence, an adversary can gather information in a low risk, anonymous manner

without being physically present to maintain surveillance. As the results from

the experiments in this paper indicate, given a room with a setup of sensor nodes that measure humidity, a remote adversary can determine human

presence or absence in that room by only using the humidity readings from the

sensor nodes deployed in that room.

It is noted that this system is not a substitute for a human activity/motion

detector system. Rather, it serves as a demonstration for inferring privacy-

sensitive personal information such as human presence by only using humidity

measurements.

2.2.3. SYSTEM DESCRIPTION

Before we explain the details of our system, we first give a brief overview to

summarize the main ideas in our approach.



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In our system, we deploy a sensor node in proximity to a user in a room.

This sensor node performs humidity measurements and reports the readings

to a data collection server.

The humidity readings are then processed at the server, and based on the

dynamics of the humidity data we are able to detect human presence and

absence.

Our system consists of the following three phases:

(a) data acquisition,

(b) data calibration, and

(c) detection algorithm.

We now proceed to the detailed description of each of these phases.

(a) Data Acquisition

For our experiments, we use the Sensirion SHT15 humidity sensor mounted

on a Moteiv Telos mote that is placed within a distance of one meter from the

subject.

The Moteiv Telos is a popular mote architecture in the sensor network

research community. It features the 8MHz TI MSP

430 micro-controller, a 16-bitRISC processor with 10 Kbytes of SRAM, a 48Kbytes flash ROM, and a 12-bit

Analog/Digital Converter with multiple input channels.

It also carries a variety of sensors that include the Hamamatsu light sensors

and Sensirion temperature and humidity sensors. Telos motes run TinyOS,

a real time operating system that is light weight and is specially designed for

sensor nodes that have limited resources.

Sensirion SHT 15 is a high precision humidity sensor that uses the CMOS

process and outputs digital values using its internal 12-bit A/D converter. It has atypical resolution of 0.03% Relative Humidity (RH), and its humidity and

temperature accuracies are 2.0 (%RH), and 0.3 (at 25 Celsius).

We use a small TinyOS application written in nesC (the programming

language for TinyOS) to obtain the sensor readings and transmit them to the PC.



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The application samples humidity and temperature data every 500

milliseconds from the SHT15. The readings are then transferred to the UART,

which is MSP430¶s universal synchronous/asynchronous receiver/transmitter

(USART) set in an asynchronous mode. This allows us to transfer the data from the

Telos mote to the server via a USB connection.

The data transferred from the Telos mote is read at the serial port on the

server. To process this data, we implement a real-time analysis script written

in MATLAB. When an event is triggered at the serial port, the script executes a

callback function to process and graph the raw data in real time.

(b) Data Calibration

In order to process the received data, it must first be calibrated to the standardunits: Relative Humidity ( RH ) for humidity and degree Celsius for temperature.

We use well-known standard techniques to perform data calibration for humidity

and temperature.

For the sake of completeness, we briefly discuss them here. We use Equation 1 to

calibrate the raw temperature readings obtained from the sensor node.

C = D1+ D2 t (1)

In the above equation, D1 and D2 are temperature conversion coefficients

equivalent to í39.6 and 0.01 respectively, and t is the raw temperature reading

from the sensor. To calibrate the raw humidity readings, we use Equation 2 given

below.

RH = (C í25) (T 1+T 2 s) + h (2)

In the above equation, C is the calibrated temperature in degrees Celsius, T 1 and

T 2 are the temperature compensation coefficients equivalent to 0.01 and 0.00008

respectively, s is the raw humidity reading from the sensor, and h is the

temperature-uncompensated humidity value given by:

h = K 1+ K 2 s + K 3 s2 (3)



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where K 1, K 2, and K 3 are the humidity conversion coefficients equivalent to í4,

0.0405, and í2.8×10í6 respectively.

(c) Data Algorithm

First, we apply a high pass filter to the calibrated humidity data obtained in the

second phase of Data Calibration, which is equivalent to the first order discrete

derivative of the input data. This will detect the changes in the original data.

Next, we set a threshold value T over the filtered humidity data.

Finally, we set a sliding window of size n for the data samples from the high pass

filtered data. At any point of time, we evaluate the samples in the current sliding

window to check if at least m of these samples exceeds the threshold value T . If the

check succeeds, then the system infers that a human is present.

This decision holds true until some point of time, when the above check fails. At

this point, the system decides that the human is absent.

Definition 1 Event E1 is the case where the system is able to successfully detect

human presence for a given sample when the human is present. We define

Detection Rate as the ratio of the total number of samples when event E1 occurs to

the total number of samples when the subject is present.

Definition 2 Event E2 is the case where the system detects human presence for a

given sample when the human is absent. We define False Positive Rate as the ratio

of the total number of samples when event E2 occurs to the total number of

samples when the subject is absent.

2.2.4. EXPERIMENTAL RESULTS

Experiment Detection Rate False Positive Rate

A 95.59 2.67

B 92.25 28.33C 91.80 29.70

Fig: This table summarizes the results from three different experiments.

Experiment B gives the trade-off value between Detection Rate and False Positive

Rate.



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2.3. Wireless Sensor Networks for Living Environment Monitoring

by Wu Zhengzhong ; Liu Zilin ; Liu Jun ; Huang Xiaowei ;

Dept. of Inf. Eng., Logistical Eng. Univ., Chongqing, China,

2009[15]

2.3.1. ABSTRACT

Wireless sensor networks (WSN) greatly extend our ability to monitor and

control the physical world. It can collaborate and aggregate a huge amount

of sensed data to provide continuous and spatially dense observation of

environment.

The control and monitoring of indoor atmosphere conditions represents an

important task with the aim of ensuring suitable working and living spaces

to people.

However, the comprehensive air quality, which includes monitoring of

humidity, temperature, gas concentrations, etc., is not so easy to be

monitored and controlled. In this paper a WSN monitoring system was

developed for living environment.

In the system several sensors were built in a RF transceiver board for

monitoring living conditions. The indoor environmental monitoring

parameters can be transmitted by wireless to database server and then

viewed throw PC or PDA accessed to the local area networks by

administrators.

The system, which was also field-tested and showed a reliable and robust

characteristic, is significant and valuable to people.

2.3.2. INTRODUCTION

The ability to monitor essential environmental factors can prove helpful and

very valuable to commercial or residential building owners.

To monitor factors such as temperature, humidity, and light coverage and

noise can help those building administrators improve local environmental

settings for human comfort levels or for the purpose of keeping certain goods in a

warehouse in a controlled temperature and humidity.



P a g e | 27

The main issue to solve is gathering this data in an organized fashion and

viewing in human readable forms. Thanks for information technology nowadays

all electronic appliances in a home will be currently networked: PCs, telephones,

stereos, refrigerators, washing machines, even heating and air conditioning, and so

on.

But hard wiring up a monitoring system to perform the desired sensing

operations in each room is not very economical, in terms of wires to run and time

to take to complete the job.

There is also the issue of central data collection from each individual room

in building. The data collected from each room in every building location would

need to be stored in a central database server for remote viewing by the building

administrators.

With the constraints in mind, the desired system to perform sensing

operations must be small, easy to install, require very little maintenance, and

be out of reach from unauthorized people.

Recent advances in micro-electronics and micro electro-mechanical systems

(MEMS) and wireless communication technologies, have enabled the

development of low-cost, low-power, multifunctional sensor nodes that are small

in size and communicate wirelessly in short distances.

Environment monitoring system based on wireless sensor networks have

become more and more important in the field of protection and control of natural

and man-made environments, providing vast arrays of real-time, remote interaction

with the physical world.

Smart, wireless networked sensors system can collect and process an

enormous amount of data, from monitoring and control of air quality, traffic

conditions, to weather. A sensor network monitors not only just a few isolated

sensors, but also actually hundreds of intelligent sensor nodes providing local

measurements as well as overall patterns of change.

The promising technology of WSN helps to run factories, optimize widely

spread processes, monitor the weather, detect the spread of toxic gases in chemical

industries and even provide precious extra time in advance of earthquakes.



P a g e | 28

Widespread use of WSN powered with the concept of distributed sensing

and computing of indoor and outdoor environment promises to revolutionize the

present state of environmental protection and control.

Rather than transmitting large amounts of raw data, the sensor nodes can

perform signal analysis and processes, communicating only the processed results.

Now intelligent sensor nodes can monitor control networks to establish an activity

easily when a sample is taken or even to determine when to sample, because

reducing the cost of obtaining and processing data reduces overall cost, and

improves system performance.

WSN are dense wireless networks of small, low cost unattended micro-

sensors that collect and disseminate environmental data indoor and outdoor. These

microsensors are equipped with a sensor module, e.g. acoustic, light, temperature,

magnetic, image sensor, capable of sensing a parameter or a quantity regarding theenvironment, a digital processor for processing the signals from the sensors and for

performing operating system applications and network functions, a radio module

for communication and finally a battery to provide energy for operation.

Each sensor senses the environment and sends monitoring data to an

internetworking access point, then transmits the data to a web server, from which

an end-user can get required data.

Wireless sensor networks facilitate monitoring and controlling of a varietyof inhospitable physical environments from remote locations with better accuracy.

They have applications in a variety of fields such as home security, machine-

failure diagnosis, chemical or biological detection, medical and wild habitat

monitoring as well as secure military purposes.

Sensor nodes have various energy and computational constraints because of

their inexpensive nature and ad hoc method of deployment. WSN applications

require reliable, accurate, fault-proof and possibly real-time monitoring.

Meanwhile, the low energy and processing capacities of the nodes requireefficient and energy-aware operation when it is very difficult to distribute the main

supply.

However, due to the large number of nodes, a suitable multiple access

scheme is also required to coordinate the transmissions so that multiple user

interferences can be minimized.



P a g e | 29

The improvement for currently available wireless sensor networks is

apparently quite important for utilizing WSN for sensing and reporting

applications especially in the living environmental monitoring and controlling.

In wireless networks, there are two different types of networks: Data

Communication Networks and Wireless Sensor Networks, which are used in

communicating with pieces of information among wireless nodes.

SENSING UNIT PROCESSING UNIT ANTENNA

Fig: Components of a Wireless Sensor Node [15]

2.3.3. MONITORING SOFTWARE

The monitoring software system is implemented using C#.net under the

Windows environment. It carries out the following tasks: data collection and

processing such as temperature, humidity, concentrations of CO and H2

illumination, of each wireless node, and transmitting the data to database server.

The system consists of sensing data source and view part, which are

distributed among a client program and a server program. The main programming

techniques employed in the system include: serial port communication in C#,

multiple threads, distributed objects, and sensing data displaying.

Receiving of real time environmental parameters of wireless nodes from a

RF transceiver is a part of the system. It is implemented in a client program. The

client program receives the wireless node sensing data from a transceiver through aserial port and transmits to database server for other terminal to access.

Microsoft DOTNET does not offer built-in class for the serial

communications, so a class called SerialPort to implement the serial port

communications using the Win32 API is developed, it can provide the low level

SENSOR ADC

PROCESSOR

STORAGE

TRANSCEIVER

POWER UNIT



P a g e | 30

functions that can be used to open, close, and manipulate serial ports, transmit and

receive data, and manage connections.

The Win32 serial communication function is unmanaged code that runs

outside the CLR. P/Invoke is used to wrap the API functions, constants, and

structure definitions as static members of the managed SerialPort class.

The database server uses Oracle8i. Since the data that the wireless nodes

send don¶t arrive at a regular time interval, a monitor function is needed to listen to

the serial port continuously. The monitor function is executed in an independent

thread. Therefore, the client program is designed as a multiple threads application.

In the client GUI, users can set the parameters of connections between a

client and a server, such as server¶s IP address, port number and communication

channel type (TCP/HTTP), and set the parameters of a serial port communication,such as serial port number and baud rate. Users can also connect/disconnect

to/from a server, start data collection and stop data collection through this GUI.

The other thread is a serial port monitor thread that is responsible for serial

port communication between a transceiver and a client program.

Fig: Monitor Interface of WSN System[15]



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2.3.4. SYSTEM TEST AND CONCLUSION

In a living apartment the WSN monitoring system had been experimented

for 3 weeks.

The radio transmitter and receiver pair can transfer their data in a maximal

data rate of 165 kbit/s when the distances between the wireless sensor nodes and

the access point up to 75m in building and 320m open ground.

The experiment result of data rate and RF communication distances can

meet requirements of indoor environmental monitor system.

Wireless sensor nodes could be attached on the walls of room or at

convenient place, added to the campus or home networking system.

For a warehouse or a living house environment, temperature, humidity,

illumination and concentrations of CO and H2, and other toxic gases are very

important, then the WSN indoor monitoring system can provide the physical

environmental parameters at low cost conveniently.

TheWSN realtime monitoring system has three advantages:

(1) The independence of roles between sensing nodes,

(2) The automated system by self-communication function,

(3) The user-friendly monitoring system to access the environment information

and to process the urgent situation more easily.



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2.4. Design guidelines for building a wireless sensor network for

environmental monitoring by Nikos Giannopoulos, Christos

Goumopoulos, Achilles Kameas, 2009 [12]

2.4.1. ABSTRACT

Environmental monitoring is a critical process that demands accuracy,

reliability and stability at the operation level.

Monitoring variables such as temperature, humidity, barometric pressure, soil

moisture and ambient light facilitates research in fields such as precision

agriculture, habitat monitoring, weather monitoring etc.

The use of wireless sensor networks (W

SNs) provides a technology solution for dynamic and unattended environmental monitoring, under the condition that

requirements such as efficient power management and system robustness are

satisfied.

This paper presents the design and implementation of a WSN for monitoring

environmental variables and evaluates its effectiveness.

2.4.2. INTRODUCTION

Recent advances in the technology of electronic circuits gave theopportunity for minimizing the size and reducing the cost of circuits¶ productions.

This rapid development led to the implementation of autonomous compact nodes

(motes) that are capable to run complicate operations consuming very little energy

using plain batteries. These nodes have approximately the size of a box of matches.

Such nodes communicate wirelessly and use sensors that are capable to

measure physical variables such as temperature, moisture, light level etc. The most

important thing is that they do not need the human presence in order to operate.

This gives the advantage of using them in remote places that may be alsohazardous for the human life as for example in volcanoes.

These nodes consist of a wireless communication unit, a microprocessor, a

data acquisition unit and a memory unit. The existence of both microprocessor and

memory unit give the ability the nodes to be programmed in order to perform



P a g e | 33

specific measurements taken either at fixed time intervals or based on an event

driven model.

Also they can be programmed in such ways in order to follow specific

routing protocols. WSNs allow the coverage of wide geographical areas. The range

of the area depends on several factors such as the number of nodes, the way that

have been placed and the range of the wireless units.

Researchers have proposed placements in a structure aiming for power

efficiency and data reliability. This paper presents the design and implementation

of a WSN for monitoring environmental variables and evaluates its effectiveness

using laboratory tests.

In order to develop the monitoring applications we used on the hardware

side the Mica2 motes by Crossbow, embedded and external sensors; on the

software side we have used TinyOS, an open source operating system developed by the University of Berkeley and NesC, a component-based and event driven

programming language.

2.4.3. SYSTEM DESCRIPTION

a) Hardware Tools

o implement our WSN, we used the following hardware:

� Three MPR2400 MICAz modules.� The MIB520CA base station module.

� One MDA100CA data acquisition board.

It provides a precision thermistor, a light sensor/photocell and general

prototyping area.

� One MDA300 data acquisition board which includes an onboard

temperature and humidity sensor.

Finally, we used the moisture probe Echo-10 by Decagon, which was

plugged on MDA300 acquisition board.

b) Software Tools

For the needs of our project we used a variety of programming

environments. For the implementation of the applications which run on the

motes we used the nesC programming language and the MoteWorks

environment.



P a g e | 34

We used Java to implement the application for the communication

between the MIB520CA and the database.

For the web based application we used the Microsoft Visual Studio .Net

2003 and the .aspx technology.

For the graphs we used the Dundas Chart for asp .net 2003. Finally, we

used the Microsoft SQL Server 2000 to develop the database in which the data

will be logged.

2.4.4. DESIGN AND IMPLEMENTATION

The nature of the hardware of WSNs imposes many constraints that must be

considered when establishing the design goals and trade-offs of the applications.

These constraints are mainly attributed to the limited resources of the motes:

processing power, memory, communication bandwidth/range and power supply.

Therefore, developers need to take into account energy requirements during the

design phase.

Regarding the engineering approach we followed, given that no prior

experience existed, we had to be ready to confront several new challenges and to

overcome many difficulties.

For that reason a risk management analysis had to be done before starting

the implementation. During that phase, we identified the potential risks that would

jeopardize the project.

The risks were classified into the following categories: sensitive equipment

usage, integration of heterogeneous systems and technologies, open source,

insufficient tool documentation, limited number of nodes, measurement accuracy

and network reliability.

After creating the list of the risks, a risk analysis was performed evaluating

the issues depending on the severity and the impact of each of them on the project.

A major issue that we had to confront related to the combination of TinyOS with

Crossbow software.



P a g e | 35

Although the use of open source software has many advantages like no cost

and customizability, it may also come with a few holes. The most important in our

case were related with the inadequate documentation and the existence of not well

tested code. As a consequence of the constraints discussed above we have followed

an incremental development model with risk analysis and assessment which can be

seen as a light spiral model.

The basic functional requirements of the project were specified in the

previous section. Furthermore, two critical non functional requirements specified

are data reliability and power efficiency.

2.4.5. DISCUSSION

The testing of our system took place in the lab. We have tested that the

embedded and the external sensors can make accurate measurements, the motescan store measured values, the transmission of values and associated ID data

trough the wireless link and the transmission of data from the BS to the database.

For the measurements of the soil moisture we used a plant. The WSN was

able to operate without interruption for 15 days with a sampling rate of 3 seconds.

From the lab tests, there is sufficient evidence that the system performs the

basic functionality specified. The experiments serve as a feasibility study of our

prototype and the design goals made. Using the TOSSIM simulator we tested our network in order to ensure that is functional for more than two nodes.

2.4.6. CONCLUSION

We presented the design and implementation of a WSN for monitoring

environmental variables and evaluated its effectiveness. Based on the acquired

experience we described how we have confronted certain problems and we

provided certain design guidelines for building such a system.

Future work will focus on addressing the limitations of the current prototypeand building a larger network with additional sensors such as a photosynthetic

solar radiation meter.

We plan also to deploy the network to an open field for agricultural

monitoring.



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2.5. A practical deployment of Intelligent Building Wireless Sensor

Network for environmental monitoring and air-conditioning

control by Tao Zheng, Yajuan Qin, Deyun Gao, Junqi Duan,

Hongke Zhang, 2010 [13]

2.5.1. ABSTRACT

Wireless Sensor Networks (WSNs) is the core support technology in the

framework of the internet of things. Environmental monitoring and devices control

of intelligent building based on WSN is considered as one of the most crucial

applications.

It can perceive several environmental parameters and feedback controlinformation to devices to provide more comfortable environment for people.

However, it is difficult to ensure performance of WSNs deployed in the

buildings, because there usually are several serious disturbances from coexistence

wireless systems and human actions.

In this paper, an intelligent WSN is deployed that satisfies the need of the

proposed applications for environmental monitoring and air-conditioning control.

2.5.2. INTRODUCTION

The Internet of Things (IoTs) is a technological revolution that integrates

technologies such as wireless sensor network, radio frequency identification and

networked embedded devices with existing Internet aiming to exchange

information and communicate between objects through different information

sensing devises.

As the core support technology in the framework of IoTs, wireless sensor network (WSN) is receiving sustained attentions in the application scenarios.

Particularly, the environmental monitoring and device control in the buildings is a

crucial application to ensure a comfortable environment.

WSN can provide real-time and remote interaction to multiply devices and

are very suitable for such tasks. Even though there are many advantages of WSN,



P a g e | 37

it is not easy to deploy WSN in the buildings because the radio environment

suffers from serious frequency conflicts and human action disturbances within the

intelligent buildings.

For example, there are other coexistent wireless networks operating in the

same 2.4GHz industrial, scientific and medical (ISM) band with WSN.

References show that interferences do exist between the coexistent wireless

networks in the 2.4GHz-ISM band and the presence of interferences in the same

frequency band may even lead to disruptive effects in the transmission of data

packets.

In this paper, we analyze actual spectrum characteristics, Link Quality

Indicator (LQI), Received Signal Strength Indicator (RSSI) and Package Loss Rate

(PLR) of sensor nodes deployed in our laboratory building.

And we focus on the practical application of intelligent building wireless

sensor network defined as IBWSN for temperature, humidity monitoring and air-

conditioning control.

Performance evaluation demonstrates that the proposed IBWSN satisfies the

needs of such applications.

2.5.3. P

LATFORM SETUP

We conduct our platform in the National Engineering Laboratory Building

located at Beijing Jiaotong University.

We install some nodes with temperature and humidity sensors along the

corridor of size 50m 1.87m 2.6m for monitoring real-time building environmental

information.

For data visualization we put a gateway and data server in the testing room

nearby the corridor.

The environmental parameters of the building are transmitted via the data

communication networks and monitored from data server or mobile phones.



P a g e | 38

Fig: WSN devices[13]

2.5.4. USER INTERFACE

The user interface consists of two parts: theWSN server and the mobile

phone client. The server manages the network events, while the mobile client

monitors the network status and feeds back control command remotely.

Fig: Network User Interface of the system [13]



P a g e | 39

2.5.5. PERFORMANCE EVALUATION

In order to evaluate the performance of our platform, several measurements

have been made. Our testing mainly focuses on monitoring temperature and

humidity of the seventh floor corridor.

Fig: Snapshot of collected data [13]

The horizontal axes are time samples from 12:00 noon to 9:00 pm, while

vertical axes are values of temperature and humidity, respectively.

The red line represents the changing trends. These testing results illustrate

that the system meets our requirements.

2.5.6. CONCLUSION

In this paper, we practically measure the channel power of the system in a

realist, complex radio environment. Based on the analysis of spectrum

characteristics, LQI, RSSI and PLR, we deploy a practical Intelligent Building

Wireless Sensor Network in our laboratory building.

This system is used for environmental monitoring and air conditioning

control. The performance evaluation illustrates that this system can ensure the

effectiveness under the interferences of the coexisting WLAN and human actions,

and this real platform satisfies the needs of the proposed control applications.

From the literature survey that has been carried out, we see that this

technology has huge implications and thereby it can be used for environment

protection. Combining the various results from the research papers mentioned

above, we can use the sensors for environmental protection using the wireless

sensor network.



P a g e | 40

3. PLAN OF WORK

3.1. METHODOLOGY

Various applications are used to take the temperature and humidity readingsfrom the mote. The applications used are:

3.1.1. SENSE APPLICATION

Sense application is used to sense the temperature and humidity. It

periodically samples the default sensor and displays the bottom bits of the readings

on the LEDs.

The SenseAppC.nc file contains the following code:

configuration SenseAppC

{

}

implementation {

components SenseC, MainC, LedsC, new TimerMilliC(), new DemoSensorC() as Sensor;

SenseC.Boot -> MainC;

SenseC.Leds -> LedsC;

SenseC.Timer -> TimerMilliC;

SenseC.Read -> Sensor;

}

3.1.2. OSCILLOSCOPE APPLICATION

Oscilloscope is an application that let's you visualize sensor readings on the

PC. Every node that has Oscilloscope installed periodically samples the default



P a g e | 41

sensor via (SensirionSht11C) and broadcasts a message with 10 accumulated

readings over the radio.

We implemented a Oscilloscope application that let us visualize sensor

readings on the PC. A node that has Oscilloscope installed periodically samplesthe sensor via (SensirionSht11C) component in OscilloscopeAppC.nc and

broadcasts a message with 10 accumulated readings over the radio.

A node running the BaseStation application will forward these messages to

the PC using the serial communication.

To run Oscilloscope therefore we need at least two nodes: one node attached

to your PC running the BaseStation application and one or more nodes runningthe Oscilloscope application.

The OscilloscopeAppc.nc file contains the following code:

configuration OscilloscopeAppC { }

implementation

{

components OscilloscopeC, MainC, ActiveMessageC, LedsC,

new TimerMilliC(), new SensirionSht11C() as Sensor,

new AMSenderC(AM_OSCILLOSCOPE), new AMReceiverC(AM_OSCILLOSCOPE);

OscilloscopeC.Boot -> MainC;

OscilloscopeC.RadioControl -> ActiveMessageC;

OscilloscopeC.AMSend -> AMSenderC;

OscilloscopeC.Receive -> AMReceiverC;

OscilloscopeC.Timer -> TimerMilliC;

OscilloscopeC.Read -> Sensor;

OscilloscopeC.Leds -> LedsC;

}



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The Oscilloscope.nc file contains the following code:

module OscilloscopeC

{

uses {

interface Boot;

interface SplitControl as RadioControl;

interface AMSend;

interface Receive;

interface Timer<TMilli>;

interface Read<uint16_t>;

interface Leds;

}

}

When it has gathered 10 sensor readings OscilloscopeC puts them into a

message and broadcasts that message via the AMS end interface.

OscilloscopeC uses the Receive interface for synchronization purposes and

the SplitControl interface, to switch the radio on.

A node running Oscilloscope will toggle its second LED for every message

it has sent and it will toggle its third LED when it has received

an Oscilloscope message from another node: incoming messages are used for

sequence number synchronization to let nodes catch up when they are switched on

later than the others; they are also used for changing the sample rate that defines

how often sensor values are read. In case of a problem with the radio connectionthe first LED will toggle.

Similarly we will install BaseStation on another node and connect it to our

PC. As usual, on the BaseStation node we will should see the second LED toggle

for every message bridged from radio to serial.



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3.1.3. BASESTATION APPLICATION

BaseStation is a basic TinyOS utility application. It acts as a bridge between

the serial port and radio network.

When it receives a packet from the serial port, it transmits it on the radio;

when it receives a packets over the radio, it transmits it to the serial port.

The BaseStationC.nc file contains the following code:

configuration BaseStationC {

}

implementation {

components MainC, BaseStationP, LedsC;

components ActiveMessageC as Radio, SerialActiveMessageC as Serial;

MainC.Boot <- BaseStationP;

BaseStationP.RadioControl -> Radio;

BaseStationP.SerialControl -> Serial;

BaseStationP.UartSend -> Serial;

BaseStationP.UartReceive -> Serial;

BaseStationP.UartPacket -> Serial;

BaseStationP.UartAMPacket -> Serial;

BaseStationP.RadioSend -> Radio;

BaseStationP.RadioReceive -> Radio.Receive;



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BaseStationP.RadioSnoop -> Radio.Snoop;

BaseStationP.RadioPacket -> Radio;

BaseStationP.RadioAMPacket -> Radio;

BaseStationP.Leds -> LedsC;

}

The Oscilloscope code is compiled on the motes for taking the readings from

the environment. Once the Oscilloscope is installed on the motes, the Base Stationcode is run on the third mote.

The motes on which Oscilloscope is installed sense temperature andhumidity values through their sensors and send the data to the Base Station mote.

The Base Station mote gathers data from the various deployed motes anddisplays their readings on the Oscilloscope.

3.1.4. SENSIRIONSHT11 APPLICATION

The SensirionSht11.nc file consists of the following code for measuring

temperature and humidity:interface SensirionSht11 {

/**

* Resets the sensor.*

* @return SUCCESS if the sensor will be reset*/

command error_t reset();

/*** Signals that the sensor has been reset.

** @param result SUCCESS if the reset succeeded

*/event void resetDone( error_t result );

/**

* Starts a temperature measurement.



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*

* @return SUCCESS if the measurement will be made*/

command error_t measureTemperature();

/*** Presents the result of a temperature measurement.

** @param result SUCCESS if the measurement was successful

* @param val the temperature reading*/

event void measureTemperatureDone( error_t result, uint16_t val );

/*** Starts a humidity measurement.

*

* @return SUCCESS if the measurement will be made*/command error_t measureHumidity();

/**

* Presents the result of a humidity measurement.*

* @param result SUCCESS if the measurement was successful* @param val the humidity reading

*/event void measureHumidityDone( error_t result, uint16_t val );

/**

* Reads the current contents of the SHT11 status and control* register. See the datasheet for interpretation of this register.

** @return SUCCESS if the read will be performed

*/command error_t readStatusReg();

/**

* Presents the value of the status register.

** @param result SUCCESS if the read succeeded* @param val the value of the register

*/event void readStatusRegDone( error_t result, uint8_t val );

/**

* Writes a new value to the SHT11 status and control register.



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*

* @param val the new value to be written*

* @return SUCCESS if the write will be performed*/

command error_t writeStatusReg( uint8_t val );

/*** Signals the completion of the status register write.

** @param result SUCCESS if the write was successful

*/event void writeStatusRegDone( error_t result );

}

This code enables the sensor SHT11 present on the mote to sense the values of

temperature and humidity.



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4. RESULT AND FINDINGS

4.1. SERIAL FOR WARDER

Serial Forwarder is a program that opens a packet source and lets many

applications connect to it over a TCP/IP stream in order to use that source. It is basically a communication medium.

Figure referred from [1]

We visualize the sensor reading by using the JAVA GUI which connects to theserial forwarder and retrieves packet data, passes the sensor readings from packet and

display them on the graph.

We can start the GUI by typing ./run (in tinyos-2.x/apps/Oscilloscope/java)

We can sense other sensors by changing the DemoSensorC component to other

component which comes with TelosB platform.

The Serial Forwarder tool is a simple way to remove these two limitations ±

� Directly using serial port due to which only one program can connect with mote

� Requires to run the application on the PC which is physically connected to the

mote.



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4.2. COMMANDS USED

The commands that are used for sensing data are as follows:

$ make telosb

Compiles Application and prepares Mote

$ motelist

Displays a list of motes connected

$ make telosb reinstall bsl,Devicepath

This command is used for installing BaseStation and Oscilloscope applications

on mote.

$ Java net.tinyos.sf.SerialForwarder ±comm serial@Devicepath:telosb

Runs the serial forwarder

$ make

Runs the make command

$ ./run

Runs the Oscilloscope Java application.

4.3. CALIBRATION

4.3.1. Calibration of temperature

import java.util.*;

/* Hold all data received from motes */

class Data {/* The mote data is stored in a flat array indexed by a mote's identifier.

A null value indicates no mote with that identifier. */ private Node[] nodes = new Node[256];

private Oscilloscope parent;

Data(Oscilloscope parent) {this.parent = parent;



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}

/* Data received from mote nodeId containing NREADINGS samples from

messageId * NREADINGS onwards. Tell parent if this is a new node. */void update(int nodeId, int messageId, int readings[]) {

if (nodeId >= nodes.length) {

int newLength = nodes.length * 2;if (nodeId >= newLength) {

newLength = nodeId + 1;}

Node newNodes[] = new Node[newLength];

System.arraycopy(nodes, 0, newNodes, 0, nodes.length);nodes = newNodes;

}

Node node = nodes[nodeId];if (node == null) {

nodes[nodeId] = node = new Node(nodeId);

parent.newNode(nodeId);}

node.update(messageId, readings);}

/* Return value of sample x for mote nodeId, or -1 for missing data */

int getData(int nodeId, int x) {if (nodeId >= nodes.length || nodes[nodeId] == null)

return -1;return (int) (nodes[nodeId].getData(x)*0.01-39.6);

}

/* Return number of last known sample on mote nodeId. Returns 0 for unknown motes. */

int maxX(int nodeId) {if (nodeId >= nodes.length || nodes[nodeId] == null)

return 0;return nodes[nodeId].maxX();

}

/* Return number of largest known sample on all motes (0 if there are no motes) */int maxX() {

int max = 0;

for (int i = 0; i < nodes.length; i++) {if (nodes[i] != null) {

int nmax = nodes[i].maxX();



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if (nmax > max)max = nmax;

}}

return max;

}}

4.3.2. Calibration of humidity

import java.util.*;

/* Hold all data received from motes */

class Data {/* The mote data is stored in a flat array indexed by a mote's identifier.

A null value indicates no mote with that identifier. */ private Node[] nodes = new Node[256];

private Oscilloscope parent;

Data(Oscilloscope parent) {this.parent = parent;

}

/* Data received from mote nodeId containing NREADINGS samples from

messageId * NREADINGS onwards. Tell parent if this is a new node. */void update(int nodeId, int messageId, int readings[]) {if (nodeId >= nodes.length) {

int newLength = nodes.length * 2;

if (nodeId >= newLength) {newLength = nodeId + 1;

}

Node newNodes[] = new Node[newLength];System.arraycopy(nodes, 0, newNodes, 0, nodes.length);

nodes = newNodes;}

Node node = nodes[nodeId];if (node == null) {

nodes[nodeId] = node = new Node(nodeId); parent.newNode(nodeId);

}node.update(messageId, readings);



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}

/* Return value of sample x for mote nodeId, or -1 for missing data */

int getData(int nodeId, int x) {if (nodeId >= nodes.length || nodes[nodeId] == null)

return -1;return (int) (nodes[nodeId].getData(x)*0.00367-2.0468);

}

/* Return number of last known sample on mote nodeId. Returns 0 for unknown motes. */

int maxX(int nodeId) {if (nodeId >= nodes.length || nodes[nodeId] == null)

return 0;return nodes[nodeId].maxX();

}

/* Return number of largest known sample on all motes (0 if there are nomotes) */

int maxX() {int max = 0;

for (int i = 0; i < nodes.length; i++) {

if (nodes[i] != null) {int nmax = nodes[i].maxX();

if (nmax > max)

max = nmax;}

}

return max;}

}

4.4. GRAPHS

The following graphs are obtained by data sensed from motes running theOscilloscope application, which are sent to the BaseStation.

The BaseStation receives data and this data is calibrated to measure either

temperature in degrees Celsius or humidity in %RH.



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4.4.1. Graphs depicting change in temperature with two connected motes

The value of temperature changes suddenly when brought close to a heat source.



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4.4.2. Graphs depicting change in temperature with one connected mote



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4.4.3. Graphs depicting constant temperature

The graphs show constant temperature reading for a period of time.



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4.4.4. Graph depicting loss of data (temperature)

4.4.5. Graph depicting humidity values



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4.4.6. Graph depicting loss of data (humidity)

4.4.7. Graph depicting fixed humidity reading



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4.4.8. Graph depicting change in humidity reading

The above graphs show results of data taken from the sensors which run theOscilloscope application and the Base Station application.

The Java Graphical User Interface displays graphs where the y-axis shows

the value of the parameter sensed (temperature/humidity) and the x-axis shows thetime.



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5. CONCLUSION AND FUTURE PERSPECTIVE

Monitoring of climate parameters like temperature and humidity through

wireless sensor networks leads to a wide variety of applications in the field on

environment protection.

Efficient deployment of this technology increases effectiveness and reduces

cost.

Reliable climate information can help countries plan for adverse and

beneficial climate events, allocate resources, and achieve development goals.

Moreover, wireless networks reduce the use of bulkier cable systems.

Efficient climate monitoring helps in preventing artifacts by controlling the

thermostat levels according to the data acquired from the sensors.

The application of wireless networks is not only limited to indoors but it can

be deployed for outdoor purposes also.

The project aimed at measuring temperature and humidity using wireless

sensor networks for environment protection.

The measurements of temperature and humidity were carried out effectively

with the graphs depicting calibrated values.

These graphs show how, through wireless communication, data can be

transmitted from one mote to another in a hassle-free manner.

The results justify that wireless sensor networks can be efficiently deployed

in an environment to monitor the climate giving its temperature and humidity

information.

More work can be done in this field of research. Calibration of sensed values

can be carried out on a much more accurate scale. Graphs depicting temperature

and humidity can be integrated to show the result in one graph.



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6. BIBILOGRAPHY

Following is the list of the references and citations made during this project.

1. http://portal.iri.columbia.edu/portal/server.pt?open=512&objID=768

&mode=2&cached=true 2. www.willow.co.uk/TelosB_Datasheet.pdf

3. http://docs.tinyos.net/index.php/TinyOS_Tutorials

4. http://docs.tinyos.net/index.php/Getting_started_using_Ubuntu_9.10_

and_TelosB_motes

5. http://en.wikipedia.org/wiki/Wireless_sensor_networks

6. http://blog.memsic.com/telosb/

7. http://www.tempsensor.net/

8. http://www.nutronicsindia.com/humidity-instruments/humidity-sensors.html

9. http://delivery.acm.org/10.1145/1840000/1838010/a7-

murad.pdf?key1=1838010&key2=9204248921&coll=DL&dl=ACM&

ip=210.212.48.3&CFID=9801281&CFTOKEN=87214889

10. http://eldridgeappraisals.com/appraisal-information/effects-of-

humidity-and-temperature/

11. http://sparrow.ece.cmu.edu/group/pub/han_jain_luk_perrig_privacy.p

df

12. http://www.computer.org/portal/web/csdl/doi/10.1109/PCI.2009.17

13. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5657858&tag=1

14. http://ieeexplore.ieee.org/search/srchabstract.jsp?tp=&arnumber=1625

668&queryText%3Dwireless+sensor+network+for+environment%26

openedRefinements%3D*%26searchField%3DSearch+All

15. http://ieeexplore.ieee.org/search/srchabstract.jsp?tp=&arnumber=5319

379&queryText%3Dtelosb+mote+for+temperature+and+humidity+se

nsing%26openedRefinements%3D*%26searchField%3DSearch+All

16. TelosB manual

17. ´Sensor Node´ ,August 2009 [Online] .Available

http://en.wikipedia.org/wiki/File:Sensornode.svg



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7. COMMENTS AND SUGGESTION S OF THE EXAMINING BOARD

endsem report

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