The need for humans to know the constituent surrounding their environment and how it affects their life; this brings the necessitation to study some phenomenon that constitutes to nature such as temperature, humidity, light intensity to mention but few. With this necessitation, this project work presents an embedded wireless sensor network (WSN) prototype system for weather condition monitoring. 

The designed system provides a user interface for user with the software design to access the current and past readings of the respective nodes. The network consists of a data gateway or server which wirelessly collects data from each WSN monitoring node in their respective locations. Each WSN node consists of an Atmega328p microcontroller, sensors and an Xbee wireless communication module based on the IEEE 802.15.4/ Zigbee and industrial, scientific and medical standards. Hence, the server unit allows data collection over Xbee radio frequency module and data access from the designed interface.

It is observed from the results obtained that the higher the temperature; the lower the humidity value and vice versa. The light intensity depends on the energy quality of the light ray while the smoke sensor operates in either logic low or high which represents absence or presence of smoke.

Having studied the literature, this project work design was achieved and implemented successfully using an enabling microcontroller to coordinate all the events and a star network topology was employed to enable communication via a single receiver medium.



TITLE PAGE          i

DEDICATION         ii

ABSTRACT         iii



TABLE OF CONTENTS                     vii

LIST OF TABLES                     xiii

LIST OF FIGURES                     xiv

CHAPTER ONE          1


1.1 Preamble 1

1.2 Background of the Study 3

1.2.1 Wireless Technology 3

1.2.2 Wireless Sensor Network 3

1.3 Statement of the Problem 4

1.4 Justification of the Study 5

1.5 Aim and Objectives 5

1.5.1 Aim 5

1.5.2 Objectives 5

1.6 Scope of the Study 6

1.7 Methods of the Study 6

CHAPTER TWO           7


2.1 General Background of Wireless Sensor Network 7

2.2 Concept of Wireless Sensor Network            10

2.3 Related Works            10

2.3.1 UCLA            10

2.3.2 UCB             11

2.4 Survey of Wireless Sensor Network Testbeds            11

2.4.1 MoteLab            11 Elements of MoteLab            11 Summary of MoteLab            14

2.4.2 Emulab 14 Different experimental environmental facilities in Emulab            15

2.4.3 Kansei            16 Objectives of the Kanseitestbed            16

2.4.4 SensorNet            17

2.4.5 Orbit                       19 Design objectives of the orbit testbed 19 The Orbit testbed management software components            20

2.4.6 PlanetLab           22 Design objectives of PlanetLab 22 The services offered by Planetlab 24 Experimental environments provided by Planetlab 25

2.5 Parameter Comparison of Different Testbeds           25

2.5.1 Physical           25

2.5.2 Design           26

2.6 Features of a Wireless Sensor Network           29

2.6.1 Power           29

2.6.2  Flexibility           30

2.6.3  Robustness            30

2.6.4  Security 31

2.6.5  Communication            32

2.6.6  Computation            32

2.6.7  Time Synchronization            33

2.6.8 Size and Cost            33

2.6.9 Localization  33

2.6.10 Mobility 34

2.7 Wireless Sensor Network Application Classes 34

2.7.1 Area monitoring 36 Air pollution monitoring 36 Greenhouse monitoring 36 Landslide detection 37

2.7.2 Industrial monitoring 37 Machine health monitoring 37 Industrial sense and control WSN applications  37

2.7.3 Structural monitoring 38

2.7.4 Agriculture 38

2.7.5 Home Automation 38

2.8 Transmission media 39

2.8.1 Bluetooth  40

2.8.2 Wireless Fidelity (Wi-Fi)  40

2.8.3 GSM/GPRS Module  41

2.8.4 Radio Frequency Module  41

2.9 Deployed WSNs and their sensing elements 42

2.10 Summary 43



3.1 Design Overview  43

3.2 Sensors 45

3.2.1 Light Intensity Sensor (LDR) Circuit  45

3.2.2 Temperature and Humidity Sensor 48

3.2.3 Gas/ Smoke Sensor (MQ-6) 50

3.3 Analogue to Digital Conversion 52

3.4 A/D Acquisition Requirements 52

3.4.1 ADCON0 Register 53

3.5 Control Unit (Microcontroller, Atmega328p)  55

3.6 Microcontroller Core Features 56

3.7 Wireless Transmission 58

3.8    Serial Communication  64

3.9 Power supply 64

3.10 Design Topology  66

3.11 Principle of Operation  67

3.11.1 Transmitting Unit 67

3.11.2 Receiving unit 67

3.11.3 Display Unit 67

3.12 Flowcharts  68

3.12.1 Testbed Node Flowchart 70

3.12.2 Receiver Unit Flowchart 71

3.13 Implementation and Deployments 72

3.13.1 Material Gathering  72

3.13.2 Hardware Assemblage 72

3.13.3 Software design 76

3.13.4 Testing and Implementation 76



4.1 Results  79

4.2 Discussion 79



5.1 Conclusion 85

5.2 Recommendation 86






Table 2.1: Physical parameter comparison of different testbeds           27

Table 2.2: Design parameter comparison of different testbeds           28

Table 2.3: WSN testbeds and the attached sensors           42

Table 3.1: Atmega328p Features           56

Table 3.2: Xbee RF module specification           60

Table 4.1: The average values of data collected in days of the two testbed nodes 83



Figure 2.1: A Typical WSN Structure 9

Figure 2.2: MoteLab System Architecture 13

Figure 2.3: WSN Applications 35

Figure 3.1: The block diagram of test bed node 44

Figure 3.2a: Light dependent resistor circuit symbol 47

Figure 3.2b:Light dependent resistor component symbol 47

Figure 3.3: Temperature and Humidity sensor DHT11 49

Figure 3.4: Gas sensor (MQ-6) 51

Figure 3.5: Orientation of the ADCON0 registers 54

Figure 3.6a: Microcontroller (Atmega328p) with crystal oscillator 57

Figure 3.6b: Atmega328p 57

Figure 3.7:  Xbee RF module series 1 59

Figure 3.8: The block diagram of Receiver unit 61

Figure 3.9: Overall implemented design 62

Figure 3.10: Circuit Diagram 63

Figure 3.11: Solar panel (3W) 65

Figure 3.12: Star topology of the design 69

Figure 3.13: Transmission flow 70

Figure 3.14: Receiving flow 71

Figure 3.15: Soldered transmitting node on PCB 74

Figure 3.16: Receiver with Xbee module and its adapter 75

Figure 3.17: The main interface before data collection 78

Figure 4.1: GUI for node 1 80

Figure 4.2: GUI for node 2 81

Figure 4.3: Result display of the two testbed nodes 82

Figure 4.4: Graph of Node one over a period of six days 83

Figure 4.5: Graph of Node two over a period of six days 84 



1.1 Preamble

The emerging fields of wireless sensor networks combines sensing, computation, and communication into a single tiny device. While the capabilities of any single device are minimal, the composition of hundreds of devices offers radical new technological possibilities. The power of wireless sensor networks lies in the ability to deploy large numbers of tiny nodes that assemble and configure themselves. Usage scenarios for these devices range from real-time tracking, to monitoring of environmental conditions, to ubiquitous computing environments, to in-situ monitoring of the health of structures or equipment. While often referred to as wireless sensor networks, they can also control actuators that extend control from cyberspace into the physical world. The most straightforward application of wireless sensor network technology is to monitor remote environments for low frequency data trends. For example, a chemical plant could be easily monitored for leaks by hundreds of sensors that automatically form a wireless interconnection network and immediately report the detection of any chemical leaks. Unlike traditional wired systems, deployment costs would be minimal. Instead of having to deploy thousands of feet of wire routed through protective conduit, installerssimply have to place quarter-sized device at eachsensing point (Jason, 2003).

The network could be incrementally extended by simply adding moredevices or complex configuration. In addition to drastically reducing the installation costs, wireless sensor networks have the ability to dynamically adapt to changing environments. Adaptation mechanisms can respond to changes in network topologies or can cause the network to shift between drastically different modes of operation. For example, the same embedded network performing leak monitoring in a chemical factory might be reconfigured into a network designed to localize the source of a leak and track the diffusion of poisonous gases. The network could then direct workers to the safest path for emergency evacuation.

Current wireless systems only scratch the surface of possibilities emerging from the integration of low-power communication, sensing, energy storage, and computation.

Recent developments and market trends towards portable computing and communication devices imply an increasingly important role for wireless access in the next generation internet. The research of wireless sensor networks has become prosperous in recent years because of their potential applications in many areas, such as environmental monitoring, surveillance, disaster search and rescue. The short range wireless sensor networks are of prime importance to drive the deployment of large-scale embedded computing devices. Wireless, mobile and sensor network scenarios are expected to grow rapidly at the edge of internet. These devices will be used increasingly in “pervasive computing” applications in which the internet enables monitoring and interaction with every aspect of the physical world. Over past few years, the internet has evolved into a global network supporting a variety of computing and telecommunication applications. In future, the internet must respond to many emerging requirements like increased scale, improved security, and support for mobile, wireless devices and embedded applications (Divya, 2008).

In order to help building the next generation internet which will include wireless and sensor network devices, researchers need a vehicle to drive their next ideas. Researchers are investigating next generation network architecture and protocols but they need a facility to evaluate them. The evaluation can be done using Analytical modelling, simulation or High-fidelity environments (measurements).

Analytical modelling provides best insight into the effects of various parameters and their interactions. In spite of being flexible to use at any stage, analytical modelling is less used compared to simulation or measurements because of its complexity. Another disadvantage of analytical modelling is its simplified mathematical modelling tools which do not capture the irregularity of sensor networks.

1.2 Background of the Study

1.2.1 Wireless Technology

There are situations when it is desirable to make measurements in locations where the use of cabled sensors is challenging. Protecting cable, is by running them through conduit or burying them in channels is time consuming, labour intensive and sometimes not even possible. In some applications, measurements need to be made at distances where long cable decreases the quality of the measurement or are too costly. At times, when there is increase in the measurement being made but the datalogger does not have enough available channels left for attaching additional sensor cables. Each of these instances can be resolved with a wireless sensor network. WSN provides a reliable, low maintenance, low power method for making measurements in applications where cabled sensors are impractical or otherwise undesirable.

1.2.2 Wireless Sensor Network

This is a network that uses wireless connected sensor devices to monitor and communicate specific conditions. It gathers concerned information such as voltage, pressure, motion, sound etc. in different locations, especially some place that people cannot be competent e.g. in nuclear power plants.

A WSN can be formed by multi sensor nodes with different topologies such as star, tree, ring and mesh structures. Different multi-hop routing protocols are applied in these WSN to broaden the communication range. The ideal wireless sensor is networked and scalable, consumes very little power, issmart and software programmable, capable of fast data acquisition, reliable and accurateover the long term, cheap, easy to install, and requires virtually no real maintenance.

1.3 Statement of the Problem

With the effect of environmental quantities on nature and human being, it is our goal is to build an environmental physical quantity monitoring system for intelligent planning, and maintenance of the environment. This system should work under varied physical conditions. It should be cost effective, easy to deploy (no need to dig or build overhead structures) and it shouldrequire minimal maintenance. We want to build a physical quantity monitoring system that is able to remove or reduce the error in human readings. Thus, our efforts are based on reporting temperature, light intensity, humidity and gases (i.e. smoke).

The testbed will be controlled by PC-end with different commands which can collect data from all sensor nodes easily and report failure or abnormity to users in time. 

1.4 Justification of the Study

Wireless sensor networks are mainly designed for habitat and environmental monitoring where many sensor nodes gather data that is sent towards one or more sink nodes. Since all this nodes are scattered over a wide area in most cases, they cannot communicate with the sink directly. Due to this fact, we plan on designing two prototypes that will communicate through a receiver means that has to be designed for effective environmental monitoring and analysis.

1.5 Aim and Objectives

1.5.1 Aim

This project work is aimed at developing a wireless sensor network (WSN) testbed for realization of an environmental condition monitoring system.

1.5.2 Objectives

i. To review the existing WSN testbeds with their respective goals.

ii. To identify the components to be used for the design of the sensory nodes.

iii. To design a WSN based environmental monitoring system.

iv. To implement the designed sensory node that measures different environmental quantities selected.

1.6 Scope of the Study

The proposed solution of this project is limited to two nodes and a server. The two nodes can communicate with the server by sending signal to the server as well as receiving processed signal from the server. The transmitter can only transmit through a distance ranging from 90m to 110m. The two nodes are arranged using star topology network in which the signal sent from each node is being transmitted straight to the server and reply from the server can be received from the node from which the signal is received. The design is to be modelled and simulated for measuring physical environmental quantities using WSN. 

1.7 Methods of the Study

The methods employed in the study are:

i. Library: - This entails the use of several textbooks, journals, past projects that have discussed previously the subject matters and have shed light to the subject.

ii. Internet browsing: - This requires surfing through various websites to get latest information and insight into the project work.

iii. Field survey: - This includes preliminary and reconnaissance survey of the research area to get basic information about the area for data collection.

iv. Laboratory works: - This has to do with circuitry design, storage, querying and system analysis.

v. Test: This involves the implementation of the design and testing it for data collection.



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