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A SENSOR ARRAY BASED ON PLANAR ELECTROMAGNETIC SENSORS
FOR AGRO-ENVIRONMENTAL MONITORING
SYAHRUL HISHAM BIN MOHAMAD @ ABD. RAHMAN
A project report submitted in partial fulfilment
of the requirements for the award of the degree of
Master of Engineering (Electrical - Mechatronics and Automatic Control)
Faculty of Electrical Engineering
Universiti Teknologi Malaysia
JANUARY 2013
iii
Thanks to ALLAH S.W.T for giving me the strength to complete the project report
and my master, to my beloved mother and father who always pray for me, to my
wife lovely wife who stand by me and to my incoming child.
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ACKNOWLEDGEMENT
Praise to Allah S.W.T., the Most Gracious and the Most Merciful, whose blessing
and guidance have helped me to complete this project report. There is no
knowledge nor power without His permission, the Highest and the Greatest. Peace
and blessing of Allah be upon our Prophet Muhammad S.A.W. who has given light
to mankind.
I would like to express my deepest gratitude to my supervisors Dr
Mohd Amri Bin Md Yunos for his support and supervisions. Without his constant
invaluable guidance, help as well as constructive criticisms and opinions
throughout the research. This research would not have been completed.
Special thanks to my mother and father who their pray are always there for
me, my wife who stand with me, brothers, sisters and families for their wishes,
assistance, guidance, and patience whose sacrifices had made everything is
possible for me. I would like to express my sincere thanks to my classmates
for all of their support during the studies, my colleagues who provided guidance
and assistance during the research.
Last but not least, special thanks to the Ministry of Higher Education
(MOHE) of Malaysia and Universiti Teknikal Malaysia Melaka for providing me
with the financial support and granting leave to pursue my Master degree.
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ABSTRACT
Agriculture is one of the important sectors in the country however due to
lack of management and knowledge, farmers usually ended up overusing pesticide
and fertilizers which can cause negative effects to the environment. Based on this
situation monitoring of the agro-environment is important in order to maintain the
permanence of the soils. As to date, available methods for contaminations detection
in agriculture soils commonly require tedious operational procedures which usually
involve purchase expensive equipments. This project suggests an alternative method
for the detection of contamination by developing a sensor array with the
combination of planar meander and interdigital electromagnetic sensors for
monitoring the content in agricultural soils and contamination. The main objective is
to fabricate the sensor array using printed circuit board (PCB). For this project three
new configuration of planar electromagnetic placement re introduced which are
parallel, wye and delta. An experimental setup consists of frequency waveform
generator, signal oscilloscope and Agilent software as the controller was developed
to study on the output of the system. A set of experiments were conducted to
determine the relationship between the sensor’s output and the soil’s parameters.
The performance of the system was observed where the sensors were tested with
soil samples taken with different concentration of water percentage. Based on the
result, the sensor array can be expected to be used to measure the contamination in
the soils and the data accuracy is compared.
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ABSTRAK
Pertanian merupakan salah satu sektor yang memainkan peranan penting
dalam pembangunan negara kita, namun disebabkan oleh kekurangan pengetahuan
dan sikap sambil lewa, para petani selalunya menggunakan racun dan baja secara
berlebigan dimana ini boleh memberikan kesan negative kepada alam sekitar.
Berdasarkan kepada situasi ini, pengawasan terhadap alam sekitar adalah penting
untuk memastikan kelestarian sumber tanah. Ketika ini, terdapat kaedah yang
digunakan untuk mengesan pecemaran di sector pertanian kebiasaanya melibatkan
prosedur yang rumit dan memerlukan pembelian peralatan yang mahal. Projek ini
mencadangkan satu kaedah alternatif untuk mengesan pencemaran didalam tanah
dengan menghasilkan planar sensor yang menggabungkan meander sensor dan
interdigital sensor. Objektif utama projek ini adalah untuk menghasilkan sensor
dengan menggunakan papan litar tercetak. Dalam projek ini tiga konfigurasi baru
sensor telah dicadangkan iaitu selari, wye dan delta. Satu sistem eksperimen telah
dibina dengan menggunakan penjana gelombang berfrekuensi, osiloskop and
perisian Agilent sebagai pengawal utama untuk mengkaji keluaran sistem sensor
tersebut. Beberapa set eksperimen telah dijalankan untuk mengetahui hubungan di
antara keluaran sensor terhadap parameter-parameter tanah. Prestasi sensor diuji
dengan kandungan air berbeza didalam tanah. Berdasarkan hasil ujikaji, kumpulan
sensor ini dapat digunakan untuk mengukur pencemaran dalam tanah dah ketepatan
data tersebut dapat diuji.
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TABLE OF CONTENTS
CHAPTER
TITLE PAGE
DECLARATION ii
DEDICATION iii
ACKNOWLEDGEMENTS iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xi
LIST OF SYMBOLS xvi
1 INTRODUCTION
1.1 Introduction to sensor 1
1.2 Environmental Sensor 3
1.3 Background of Problem 5
1.4 Objective of Study 7
1.5 Scope of Study 7
2 LITERATURE REVIEW
2.1 An Overview of Non-destructive Testing 9
2.2 Soils Contamination Detection Method 11
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2.2.1 Soils Contamination Detection using
Chromatography technique
12
2.2.2 Soils Contamination Detection using
Surface Plasmon Resonance (SPR)
14
2.2.3 Soils Contamination Detection using
Enzyme linked Immunosorbent Assay
(ELISA)
15
2.3 Planar Electromagnetic Sensor 16
2.3.1 Planar Meander, Mesh and Interdigital
Electromagnetic Sensor
16
2.4 Applicat ion and Development in
Planar Electromagnetic Sensor
20
3 RESEARCH METHODOLOGY
3.1 Introduction 24
3.2 Literature Review 25
3.3 Sensor Design And Fabrication 26
3.3.1 Sensor Design 26
3.3.2 Sensor Fabrication 33
3.4 Experimental setup 34
3.4.1 Hardware Development 35
3.4.2 Software Development 38
3.5 Experimental Work 43
3.5.1 Work Sensor Characteristic on Open Air
Experiment:
44
3.5.2 Sensor Characteristic on Soils and Water
Concentration on Soils Experiment:
44
3.6 Data Analysis and Verification 46
3.7 Report Writing 49
4 EXPERIMENTAL RESULTS AND
DISCUSSIONS
4.1 Introduction 50
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4.2 Description of the Selected Sensors 50
4.3 Characterization of the Sensors via Experiment 51
4.3.1 Characterization of the Sensors via
Open Air Experiment
52
4.3.2 Characterization Of The Sensors via
Water concentration in Soils experiment
55
4.3.3 Characterization of the Parallel
Configuration Sensors via water
concentration in soils experiment
56
4.3.4 Characterization of the Wye
Configuration Sensors via water
concentration in soils experiment
64
4.3.5 Characterization of the Delta
Configuration Sensors via water
concentration in soils experiment
72
4.4 Sensitivity studies of the soils 80
5 CONCLUSIONS AND FUTURE WORK
5.1 Conclusions 83
5.2 Future Works 85
REFERENCES 87
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LIST OF TABLES
TABLE NO.
TITLE PAGE
4.1 R2
Regression value for parallel sensor 57
4.2 R2
Regression value for wye sensor 65
4.3 R2
Regression value for delta sensor 73
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LIST OF FIGURES
FIGURE NO.
TITLE PAGE
1.1 Transducer Used In Measurement Block Diagram 1
1.2 Percentage of Sensor According To Industries 2
1.3 Global Environmental Sensor And Monitoring Business By
Market Category
4
2.1 Configuration Of Planar Electromagnetic Sensors; (A)
Mesh-Type Sensor (B) Meander-Type Sensor
17
2.2 Electric Field Lines Of Parallel Plate Capacitors 18
2.3 Conventional Interdigital Sensor 19
2.4 Electric Field Formed Between Positive And Negative
Electrodes For Different Pitch Lengths, (l1, l2and l3)
19
3.1 Project research methodology flow chart 25
3.2 The planar electromagnetic sensor design a) Top side b)
Bottom side
26
3.3a Planar Electromagnetic Sensor Parallel Placement
(Overall Design)
28
3.3b Planar Electromagnetic Sensor Parallel Placement (Top
Side Design)
28
3.3c Planar Electromagnetic Sensor Parallel Placement
(Bottom Side Design)
28
3.4a Planar Electromagnetic Sensor Wye Placement (Overall 29
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Design)
3.4b Planar Electromagnetic Sensor Wye Placement (Top
Design)
30
3.4c Planar Electromagnetic Sensor Wye Placement (Bottom
Design)
30
3.5a Planar Electromagnetic Sensor Delta Placement (Overall
Design)
31
3.5b Planar Electromagnetic Sensor Delta Placement (Top
Design)
32
3.5c Planar Electromagnetic Sensor Parallel Placement
(Bottom Design)
32
3.6a Planar Electromagnetic Sensor Parallel Placement 33
3.6b Planar Electromagnetic Sensor Wye Placement 34
3.6c Planar Electromagnetic Sensor Delta Placement 34
3.7 Overall Experiment Setup 35
3.8 Agilent U2781A USB modular Chassis 36
3.9 Agilent U2761A USB modular function generator. 36
3.10 Agilent U2701A USB modular oscilloscope. 37
3.11 Overall Modular Experimental Setup. 38
3.12 Cyclic Frequency Increment Sub Program 40
3.13a Function Generator Initialize Setup 41
3.13b Function Generator Output Setup 41
3.14a Oscilloscope Initialization Setup 42
3.14b Oscilloscope Output Configuration Setup 42
3.15 Agilent VEE Modular Control Program. 43
3.16 Water concentration into soils experiment flow. 45
3.17 Soils are filled and weighted. 45
3.18 Sensor is attached to the polystyrene bag. 46
3.19 Equivalent Circuit of planar meander and interdigital
sensor.
48
4.1 Parallel configuration sensor characteristic via open air
experiment
53
4.2 Wye configuration sensor characteristic via open air 53
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experiment
4.3 Delta configuration sensor characteristic via open air
experiment
54
4.4a Linear Parallel configuration sensor regression at 100
kHz
58
4.4b Linear Parallel configuration sensor regression at 200
kHz
58
4.4c Linear Parallel configuration sensor regression at 300
kHz
58
4.4d Linear Parallel configuration sensor regression at 400
kHz
59
4.4e Linear Parallel configuration sensor regression at 500
kHz
59
4.4f Linear Parallel configuration sensor regression at 600
kHz
59
4.4g Linear Parallel configuration sensor regression at 700
kHz
60
4.4h Linear Parallel configuration sensor regression at 800
kHz
60
4.4i Linear Parallel configuration sensor regression at 900
kHz
60
4.4j Linear Parallel configuration sensor regression at 1 MHz 61
4.5a Polynomial Parallel configuration sensor regression at
100 kHz
61
4.5b Polynomial Parallel configuration sensor regression at
200 kHz
61
4.5c Polynomial Parallel configuration sensor regression at
300 kHz
62
4.5d Polynomial Parallel configuration sensor regression at
400 kHz
62
4.5e Polynomial Parallel configuration sensor regression at
500 kHz
62
4.5f Polynomial Parallel configuration sensor regression at 63
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600 kHz
4.5g Polynomial Parallel configuration sensor regression at
700 kHz
63
4.5h Polynomial Parallel configuration sensor regression at
800 kHz
63
4.5i Polynomial Parallel configuration sensor regression at
900 kHz
64
4.5j Polynomial Parallel configuration sensor regression at 1
MHz
64
4.6a Linear Wye configuration sensor regression at 100 kHz 66
4.6b Linear Wye configuration sensor regression at 200 kHz 66
4.6c Linear Wye configuration sensor regression at 300 kHz 66
4.6d Linear Wye configuration sensor regression at 400 kHz 67
4.6e Linear Wye configuration sensor regression at 500 kHz 67
4.6f Linear Wye configuration sensor regression at 600 kHz 67
4.6g Linear Wye configuration sensor regression at 700 kHz 68
4.6h Linear Wye configuration sensor regression at 800 kHz 68
4.6i Linear Wye configuration sensor regression at 900 kHz 68
4.6j Linear Wye configuration sensor regression at 1 MHz 69
4.7a Polynomial Wye configuration sensor regression at 100
kHz
69
4.7b Polynomial Wye configuration sensor regression at 200
kHz
69
4.7c Polynomial Wye configuration sensor regression at 300
kHz
70
4.7d Polynomial Wye configuration sensor regression at 400
kHz
70
4.7e Polynomial Wye configuration sensor regression at 500
kHz
70
4.7f Polynomial Wye configuration sensor regression at 600
kHz
71
4.7g Polynomial Wye configuration sensor regression at 700
kHz
71
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4.7h Polynomial Wye configuration sensor regression at 800
kHz
71
4.7i Polynomial Wye configuration sensor regression at 900
kHz
72
4.7j Polynomial Wye configuration sensor regression at 1
MHz
72
4.8a Linear Delta configuration sensor regression at 100 kHz 74
4.8b Linear Delta configuration sensor regression at 200 kHz 74
4.8c Linear Delta configuration sensor regression at 300 kHz 74
4.8d Linear Delta configuration sensor regression at 400 kHz 75
4.8e Linear Delta configuration sensor regression at 500 kHz 75
4.8f Linear Delta configuration sensor regression at 600 kHz 75
4.8g Linear Delta configuration sensor regression at 700 kHz 76
4.8h Linear Delta configuration sensor regression at 800 kHz 76
4.8i Linear Delta configuration sensor regression at 900 kHz 76
4.8j Linear Delta configuration sensor regression at 1 MHz 77
4.9a Polynomial Delta configuration sensor regression at 100
kHz
77
4.9b Polynomial Delta configuration sensor regression at 200
kHz
77
4.9c Polynomial Delta configuration sensor regression at 300
kHz
78
4.9d Polynomial Delta configuration sensor regression at 400
kHz
78
4.9e Polynomial Delta configuration sensor regression at 500
kHz
78
4.9f Polynomial Delta configuration sensor regression at 600
kHz
79
4.9g Polynomial Delta configuration sensor regression at 700
kHz
79
4.9h Polynomial Delta configuration sensor regression at 800
kHz
79
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4.9i Polynomial Delta configuration sensor regression at 900
kHz
80
4.9j Polynomial Delta configuration sensor regression at 1
MHz
80
4.10 Sensitivity of real part for different water concentration
in soils at 100 kHz
82
4.11 Sensitivity of imaginary part for different water
concentration in soils at 100 kHz
82
xvii
LIST OF SYMBOLS
C - Capacitance
I - Current
L - Inductor
PCB - Printed Circuit Board
R - Resistance
V - Voltage
X - Reactance
Z - Impedance
Ω - Ohm
∅ - Angle
CHAPTER 1
INTRODUCTION
1.1 Introduction to Sensor
Sensor is a device that detects the parameter of show the quantity of the
measured parameter. Example of sensor is such thermocouples that detect and
sense the changes in the temperature. A transducer is a device that converts non
electrical parameters into electrical signal such as voltage and current that are
proportional to the physical value parameters that are being measured. Usually a
transducer involve a sensor and signal conditioning circuit or instruments in order
to translate or to read the value of the measurement. Figure 1.1 shows the block
diagram of transducer used in measurement.
Figure 1. 1: Transducer Used In Measurement Block Diagram
2
Sensor and transducer development is a rapid need as both of the
equipments are used in most all of the sectors and industry globally. The
implementation of sensor in most of the industries can been see with the
unprecedented growth of utilization of sensors in product and services, where
sensors play an important role in gaining important information for monitoring and
measuring process. A research done [1] show that the sensor influence of the
industrial sector globally. Figure 1.2 shows how the sensors influence within the
industries and market sector. The market sector which has most heavily used
sensors in their process is the health care sector where consist of 20% of the overall
sector. The second and third highest sector that influenced by the usage of sensor
within the industries are food processing sector which consist of 12% and the
environment sector which consist of 11% of overall market. Others area that
implemented the sensor in their sector is such as agriculture (8%), chemical
engineering (8%), domestic and other appliances (7%), security and defence (7%),
transport (6%), and energy (6%). Less development or application of sensor is used
or made in sectors such as construction/housing (3%), wood and textile (3%),
IT/communication (4%), and metal and plastic processing (5%) [1].
Figure 1. 2: Percentage of Sensor According To Industries
0
5
10
15
20
25
Percentage Of Sensor Used In Industries
Percentage
3
1.2 Environmental Sensor.
Environmental awareness has become one of the principal in technology and
industries development within these recent years. The future growth for environment
related sensor and environmental monitoring technologies are pre-ordained due to the
awareness within the global economies player on their responsibilities of environmental
impact or they may cause negative impact on themselves. This has made environmental
sensor become a substantially high technologies business. Two major trends can be
seen in influence of the environmental sensing and monitoring business, the first is that
the design and engineering of sensor components and engineering are going for a
technological revolution. Most of the individual sensors are moving forward toward
miniaturization process. The advantages of development of smaller sensor are that by
producing smaller sensor it lowers the material cost and also making the sensor to
become more energy efficient, it also large distributed networks possible. And
simultaneously environmental friendly aspect and clean-up are is more or less being
imbedded into the policy-making agenda, the advance progress in nanotechnology,
semiconductor and communication are supporting and facilitate the implementation and
development of sensors product.
Environmental sensors factually come in thousands of types, design and forms.
The sensors are usually base on a wide range of chemical and physical principles with
variable types of outputs for monitoring process. The field applications of
environmental sensors also tremendously varied. The areas of that has become the focus
for environmental sensor include vehicles emissions, fossil fuels combustion,
agricultural contamination, waste disposal for industrial and mine, ocean spilling and
dumping, extreme change in climate and weather monitoring.
The second influential factor is the rapid development of environmental sensor
and monitoring networks themselves. There is an outburst in the extent, capacity and
numbers for the mention networks, where the figure show in 2010 where the value of
global environmental sensor and is at $11.1 billion. Based on the current trendsetting
4
and forecast of future demand the environmental sensor market is expected to
reach $11.3 billion in 2011 and $15.3 billion in 2016. Where it can be say that there
will be a compound annual growth rate of 6.5% between 2011 and 2016. Shown in
Figure 1.3, which the range of expenditure for sensor can be divided into terrestrial
monitoring, atmospheric monitoring, oceanic monitoring, radon, GPS, remote sensing
and new technology.
Sensor networks allow real-time data visualization and analysis, distributed
sensing capacity, remote sensing data streams and integration of adjacent networks. The
main factor that contributed to the development of the networks are the availability of
computational capacity, the progress of massive data storage, the evolution of internet
and the reduction in size of electronics components. At this point the establishment of
environmental sensor network has been firm and large new network currently in
development process where the new environmental network rage from continental
monitoring scope until to those which only monitor on local situations. In terms of
monitoring variables are including CO2 combustion up to decadal shift in the
temperatures. The current sensor also can monitor biological and physical activities, as
well capable of measuring nutrient dynamics and groundwater fluxes. Due to these, the
development of environmental sensor is seen to be more crucial from time to time.
Figure 1. 3: Global Environmental Sensor and Monitoring Business by Market Category
5
1.3 Background of the problem
Soil is a valuable key natural source, where the 29 % of the world is cover by
land while the other 71 % of the world is primarily ocean. In the world ecosystem, soil
play an important role, which is to supports life and is a major requirement for maintain
a sustainable development in terrestrial environments. The possibility of degradation in
the aspect of quality for the topsoil layer play a particular interest as due to the topsoil
layer are exposed to natural geochemical processes, anthropogenic activities and
atmospheric deposition. Anthropogenic activities, especially in regions where
agriculture, mining land and industrial uses are practiced have significantly altered
natural background concentrations of the soils.
Soil contamination are a greater risk to the of individual who live in less
industrialize and less populated rural are compared to those whose live in the heavily
urbanized or industrialize area are due to the exposure of the contamination are higher
in time aspect of quantity and time for the rural area [2]. The contamination of urban
and agricultural soils by potentially toxic metals is also causing concern due to the
possible adverse effects on the ecosystem. Due to this matter, an improved monitoring
and understanding of the concentration of contamination in the soils in order to ensure a
long-term sustainability of food production. It is essentials to study the major, minor and
trace elements in the soils in order to understand the factor of nutrient deficiency,
bioavailability, pollution and the possible effect that can occurred to food chains and
geological eco-system. Therefore it is very important to have an ambient background
concentration data such as development of sites , toxicity and bioavailability for
potential uses [3].
The in order to safeguard human, animal and plant, there is need for
assessment, prevention, control and development of contaminated land through
regulatory organizations, which required continuous information on the soil condition.
Thus, it is important for the regulators to set guideline/standard values as a component
of environmental legislation for specific sites or wider geographical regions. One of the
6
most important objectives of background environmental monitoring is the identification
of any anomalies and anthropogenically introduced contaminants in any environmental
assessment program [4]. In Malaysia, there are currently no comprehensive soil
reference values available in order to assess levels of potentially contamination of
anomaly for various land uses such as industrial, recreational land, agriculture and
development. Based on this there is need for technology to assess the contamination
level of natural soil resources due to the process of industrialization, agriculture and
urbanization of soils in Malaysia.
Agriculture sector plays the role as one of the most significant economy
contributor in Malaysia where based on World Bank Indicator shows that around 24%
of Malaysia soil is used for agriculture. Correspond to the volume of the soils that are
used for agriculture, agro-environment monitoring is an important process in order to
maintain the permanence of the soils. However, the contaminations in the soils have
become a common thing in the agriculture soils due to the lack of knowledge within the
farmers. Overused of pesticides and fertilizers in the soil can cause negative effect to the
soil itself.
Although there are detection methods in assessing the contamination, there are
few drawbacks. The detection usually involved laborious measuring step, this will cause
the overall detection process consumes lots of time. Most of the detection process need
to be done within the laboratory and in order to extract the contain of contamination
within the soil and the process itself required controlled working condition and
preparation of extra reagent or chemical, this cause the detection result cannot be obtain
immediately. The detection process also are often expensive, this due to many
components are required in order to develops the experimental process for finding out
the soils contamination level and sometimes this process will required special
equipment which are specially designed. These requirements will become the
drawbacks as all the equipment are quite costly and are hard to be set up. Although all
the detection method is can give good results, most of the equipment are quite bulky
and the detection cannot be done on the site.
7
Based on the following drawbacks and hindrance of current detection method,
there is need to develop a sensor which can be integrated as a low cost, convenient,
and suitable for in-situ measurement system for soils quality monitoring,
particularly pesticide and fertilizer effect on soils contaminations.
1.4 Objective of the study
Looking at important of soil monitoring for the permanence of the environmental,
this research aims to achieve the following objectives:
1. To design and fabricate new planar sensor based on the combination of meander
and interdigital sensor.
2. To investigate the characteristic of the new planar sensor array based on
meander and interdigital sensor.
3. To conduct experimental work to determine relationship between the sensor
output and soils parameter.
1.5 Scope of the study
In order to achieve the objectives of the project, that is to investigate the soil
contaminations level due to pesticide and fertilizer used by the farmers for agriculture
process based on planar electromagnetic sensor development. The scopes of the project
need to be identified and implemented to make sure the aim is achieved. The scope of the
project is as follows:
8
1. Designing the sensor array using printed circuit board (PCB) designer software and
fabricating the sensor using printed circuit board (PCB). The scopes involve the
study of sensor sensitivity by three different placements of the sensor array where
the placements are parallel configuration, delta configuration and Y configuration.
2. Developing the experiment setup consists of frequency waveform generator as the
input signal, signal oscilloscope to detect the output of the sensor and to develop
output component analysis software by using Lab View to study on the
characteristic of the sensor.
3. Carry out set of experiments that will be conducted to determine the relationship
between the sensor’s output and the soil’s parameters, the suggested experiments is
on the soils permittivity versus moisture, soils permittivity versus pesticide and soils
permittivity versus fertilizer.
87
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