DEVELOPMENT OF WIRELESS SENSOR NETWORK TESTBED
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.
TABLE OF CONTENTS
TITLE PAGE i
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
LITERATURE REVIEW 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
188.8.131.52 Elements of MoteLab 11
184.108.40.206 Summary of MoteLab 14
2.4.2 Emulab 14
220.127.116.11 Different experimental environmental facilities in Emulab 15
2.4.3 Kansei 16
18.104.22.168 Objectives of the Kanseitestbed 16
2.4.4 SensorNet 17
2.4.5 Orbit 19
22.214.171.124 Design objectives of the orbit testbed 19
126.96.36.199 The Orbit testbed management software components 20
2.4.6 PlanetLab 22
188.8.131.52 Design objectives of PlanetLab 22
184.108.40.206 The services offered by Planetlab 24
220.127.116.11 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
18.104.22.168 Air pollution monitoring 36
22.214.171.124 Greenhouse monitoring 36
126.96.36.199 Landslide detection 37
2.7.2 Industrial monitoring 37
188.8.131.52 Machine health monitoring 37
184.108.40.206 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
CHAPTER THREE 44
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
CHAPTER FOUR 79
RESULTS AND DISCUSSION 79
4.1 Results 79
4.2 Discussion 79
CHAPTER FIVE 85
CONCLUSION AND RECOMMENDATION 85
5.1 Conclusion 85
5.2 Recommendation 86
APPENDIX I 90
APPENDIX II 92
LIST OF TABLES
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
LIST OF FIGURES
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
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
This project work is aimed at developing a wireless sensor network (WSN) testbed for realization of an environmental condition monitoring system.
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..