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Abstract— This paper presents a highly sensitive differential soil moisture
sensor (DSMS) using a microstrip line loaded with triangular two-turn
resonator (T2-SR) and complementary of the rectangular two-turn spiral
resonator (CR2-SR), simultaneously. Volumetric Water Content (VWC) or
permittivity sensing is conducted by loading the T2-SR side with dielectric
samples. Two transmission notches are observed for identical loads relating to
T2-SR and CR2-SR. The CR2-SR notch at 4.39 GHz is used as a reference for
differential permittivity measurement method. Further, the resonance
frequency of T2-SR is measured relative to the reference value. Based on this
frequency difference, the permittivity of soil is calculated which is related to
the soil VWC. Triangular two-turn resonator (T2-SR) resonance frequency
changes from 4 to 2.38 GHz when VWC varies 0% to 30%. The sensor’s
operation principle is described through circuit model analysis and
simulations. To validate the differential sensing concept, prototype of the
designed 3-cell DSMS is fabricated and measured. The proposed sensor exhibits frequency shift of 110 MHz for 1%
change at the highest soil moisture content (30%) for sandy-type soil. This work proves the differential microwave
sensing concept for precision agriculture.
Index Terms— CSRR, differential soil moisture sensor (DSMS), frequency domain analysis, permittivity sensing, SRR.
I. Introduction
FFICIENT utilization of agricultural resources for improved
production and reduced environmental impact is the basis
of precision farming. In a conventional agricultural
measurement method, a network of sensor nodes distributed
over a wide area is used to model intra- and inter-field
variations. Each sensor transmits local features of the soil that
surrounds it. Using the Internet-of-Things (IoT), collected data
is sent to the base station that analyses data and takes
necessary steps, like irrigation and fertilization [1], [2].
Nowadays, a broad range of IoT devices is implemented in
numerous applications with the expansion of modern farming.
Therefore, lightweight, low-cost, high-precision and low
power consumption sensors are desirable for precision farming
[3], [4], [5]. Moreover, a great advantage of IoT technology is
enhancing the accuracy of sensors in the smart farming [6].
As a result of a large discrepancy between the relative
dielectric properties (real part) of liquid water (approximately
80 for less than 5GHz) and dry soil (2 to 5), soil moisture
content can be determined from the real part of the soil
dielectric constant measurements. Due to the Volumetric
Water Content (VWC), the imaginary portion of the soil
dielectric constant affects the insertion loss in the
measurement procedure [7].
Different methods have been proposed to estimate the soil
RF and Communication Technologies (RFCT) research laboratory,
University of Technology Sydney, Ultimo, NSW 2007, Australia, e-mail:
Rasool.Keshavarz@uts.edu.au;
permittivity based on the identified criteria; time-domain
reflectometry (TDR), capacitance, frequency domain
reflectometry (FDR), remote sensing, etc. [8], [9], [10]. FDR
estimates the soil moisture content based on frequency
variations of a signal due to the dielectric properties of soil. In
recent years, planar FDR microwave sensors have been
attracted many researchers due to their simple production, low
fabrication cost, high sensitivity, reliability, and design
versatility [7]. However, having a low-quality factor is one of
the drawbacks of planar microwave sensors that could limit
their applications. To address this, some techniques have been
presented to produce ultra-high-Q microwave sensors [11],
[12]. Another disadvantage of planar frequency domain
microwave sensors is their high sensitivity to slight
environmental variations such as temperature, soil
composition, etc. This requires differential solutions to take
such variables into account. Since environmental factors are
common-mode parameters, their effect will be removed in
differential measurements. In frequency domain sensors, the
differential property is achieved by considering two (or more)
resonance frequencies, where one of them is acting as the
reference [13], [14], [15].
Metamaterials structures [16], [17], especially split-ring
resonator (SRR) and its complement (CSRR) have been
widely used as sensing devices, due to their high-quality factor
and small size [18]. Their applications have been found in
biomolecule identification, concentration analysis, and
microfluidic characterization. Penetration of electromagnetic
Highly Sensitive Differential Microwave Sensor
for Soil Moisture Measurement
Rasool Keshavarz, Justin Lipman, IEEE Senior Member, Dominique Schreurs, IEEE Fellow
Member, and Negin Shariati, IEEE Member
E
6 IEEE SENSORS JOURNAL, VOL. XX, NO. XX, MONTH X, XXXX
waves into materials in the vicinity of a sensor lays the
groundwork for remote sensing [19], [20]. Recently, several
shapes of SRR and CSRR have been demonstrated where each
of them exhibits different benefits relative to each other [21].
This paper proposes a new low-profile and high-Q
differential soil moisture sensor (DSMS) based on a microstrip
line which is loaded with two resonators simultaneously; a
triangular 2 turn spiral resonator (T2-SR) and a complement of
the rectangular spiral resonator (CR2-SR). In the proposed
structure, the CR2-SR acts as the reference resonator to
eliminate environmental conditions. Moreover, compared to
conventional SRRs, a T2-SR with the same electrical size
provides a higher Q and a stronger resonance which enhances
the sensitivity and accuracy of the proposed DSMS. Due to its
compactness, resolution, and low-cost properties, the proposed
sensor has a potential to be used as a soil moisture sensor in
precision farming.
Contributions of this paper are summarized as follows:
• As a result of combining two uncoupled resonators
(T2-SR and CR2-SR) in the sensor structure, the
proposed DSMS exhibits differential measurement
property to create a highly reliable measurement
procedure.
• The proposed highly sensitive sensor has been
presented for soil moisture measurement which is
related to the permittivity range of 3 to 16.5 (for
sandy soil). Further, this methodology is applicable
over a wide range of permittivity measurement
scenarios. The proposed technique can be adopted to
different material detection systems.
• From a design and economical perspective, utilizing
both sides of PCB (top and bottom layers) to realize
two types of resonators in each layer, results in
decreasing the total footprint. Therefore, the
proposed differential sensor is compact, low cost and
has a potential to be embedded into practical
applications.
• An accurate design guide procedure and equivalent
circuit model have been presented and equations
were derived.
The organization of this paper is as follows: Theory and
design principles of the proposed DSMS are presented in
section II. The DSMS performance is validated by simulation
and measurement results in section III. Finally, conclusions
are provided in section IV.
II. THEORY AND DESIGN PRINCIPLE OF THE PROPOSED
DSMS
The schematic (top and bottom layers) and 3D layers of the
proposed DSMS are presented in Fig. 1(a) and 1(b). This
sensor consists of three parts: microstrip line, triangular 2-turn
spiral resonator (T2-SR), and complementary rectangular 2-
turn spiral resonator (CR2-SR). The T2-SR includes 2-turn
concentric spiral metallic rings, printed on a substrate (top
layer) and is edge-coupled to the microstrip line, while the
CR2-SR is etched on the ground plane (bottom layer) (Fig.
1(b)). As the coupling mechanism of T2-SR and CR2-SR are
dominated by electrical and magnetic fields, respectively,
these two resonators are not coupled to each other and hence,
their resonance frequencies are isolated. From a practical
perspective, two distinct resonators are implemented to
calibrate the environmental impacts. Therefore, the extraneous
environmental effect is subtracted using a differential sensing
algorithm. Fig. 1(b) exhibits sensor layers in the measurement
setup; reference layer (air or foam) and material under test
(MUT) layer with permittivity of and , respectively.
Between these two layers, the proposed sensor is placed on a
microwave substrate with permittivity and thickness of and
h, respectively. The reason of etching T2-SR on the top layer
and CR2-SR on the bottom layer as the reference will be
explained later in this section.
Due to small electrical dimension of the T2-SR and CR2-
SR at resonance frequencies, microstrip loaded lines can be
described by equivalent circuits of lumped element. The
equivalent circuit model (unit cell) for the T2-SR and CR2-SR
loaded transmission line is shown in Fig. 1(c). L and C are
per-section inductance and capacitance of the microstrip line.
T2-SR is modeled as a resonant tank which is magnetically
coupled to the line through mutual inductance, M. This
produces inductance Ls and capacitance Cs after tank
transformation to horizontal branch in the equivalent circuit
model (Fig. 1(c)) [22]. Whereas, CR2-SR is mainly excited by
the electric field induced through the line. This coupling can
be modeled by connecting the series line capacitance to CR2-
SR, which is modeled as a parallel LC tank. According to this,
the proposed lumped element equivalent circuit model for the
CR2-SR loaded transmission line (Fig. 1.c) consists of Lc and
Cc as the CR2-SR. Due to the proposed sensor dimensions and
for simplicity, the equivalent circuit model is assumed
lossless. This assumption only affects Q-factor of the
resonances and not the resonance frequencies. Figure 1(d)
shows the E-field distribution of the unloaded DSMS at the
resonance frequencies for the top and bottom resonators.
Effective permittivity of a microstrip line that is buried
under a MUT can be expressed as [23]:
(1)
Where is the average width of microstrip line and T is the
MUT thickness.
According to Fig. 1(c), transmission response of the
proposed DSMS exhibits two zeros (resonance frequencies) at:
(2)
Where and are resonance frequencies of the T2-SR and
CR2-SR, respectively.
Fig. 2 shows S-parameters results (full-wave and circuit
model) of the proposed 3-cell DSMS (). This figure
confirms accuracy of the proposed equivalent circuit model
and design procedure. Values of the equivalent circuit model
parameters are presented in Table I. These parameters have
been extracted from closed-form equations [23] and
optimization process using Advanced Design System (ADS).
Moreover, the geometrical dimensions of T2-SR, CR2-SR,
and transmission line are provided in Table II.
6 IEEE SENSORS JOURNAL, VOL. XX, NO. XX, MONTH X, XXXX
(a)
Reference (εr0)
(air, foam)
FR-4 (εr )
MUT (εm )
T2-SR
CR2-SR
T
h
(b)
L/2
2Cs
Lc
Cc
C
Ls/2 L/2
2Cs
Ls/2
T2-SR
CR2-SR
(c)
(d)
Fig. 1. Proposed DSMS unit cell a) DSMS schematic (top and bottom
layers), b) 3D Layers, c) Equivalent circuit model, d) E-field distribution
of the proposed DSMS for three cells.
In the proposed sensor, two resonance frequencies are
completely uncoupled; one is kept immune from variations
known as static/reference resonance (CR2-SR) and the other is
used for conventional sensing as a dynamic resonance (T2-
SR). The inductors in the sensor equivalent circuit model (Ls,
Lc) are not impacted by the MUT permittivity and they are
roughly constant in the measurement process. Therefore, key
components in the analysis of the DSMS resonance
frequencies are capacitances (C, Cc, Cs). The effect of MUT
permittivity on the capacitances values is investigated in this
paper.
The capacitance Cc in Fig. 1(c), corresponds to a metallic
rectangular sheet that is surrounded by a ground plane at a
distance g. An analytical and complicated expression for this
type of capacitance is derived and presented [23]. However, in
this paper, we used a numerical solution to find Cc equivalent
capacitance based on this expression. In contrast, finding Cs
and C is straightforward and can be calculated as in [23]:
Cs=Cpul×Pse,
(3)
Where Cpul is the per unit length capacitance along with the
slot between square rings, Pse is the effective average
perimeter of two triangular rings in the T2-SR structure, l and
are the length and characteristic impedance of the
microstrip transmission line, is the effective permittivity of
the structure and c denotes the light velocity.
Now, the sensitivity is defined as the variation of resonance
frequency () relative to the permittivity (or VWC) of
the MUT as:
(4)
where and are to calculate and
, respectively. Therefore, considering sensitivity of the
equivalent capacitance relative to permittivity (
),
is calculated. Finally, according to (1), (2) and (3) and
using ADS, the optimum values of the DSMS components are
obtained to maximize sensor sensitivity over a broad range of
permittivity at desired frequency bands.
(a)
(b)
Fig. 2. Full-wave and circuit model simulation results of the proposed
3-cell DSMS ( ), a) |S21|, b) unwrap phase(S21).
TABLE I. VALUES OF THE EQUIVALENT CIRCUIT MODEL.
()
()
()
()
()
()
1.73
4.6
3.85
1.11
4.33
1.84
TABLE II. DIMENSIONS OF THE PROPOSED DSMS IN (FIG. 1(A))
L1
L2
L3
L4
L5
W1
W2
W3
G1
G2
G3
6.2
1.9
16.2
2.1
3.3
0.2
0.4
0.2
0.2
0.2
0.2
|S21| (dB)
Frequency (GHz)
CR2-SR
T2-SR
Unwrap Phase (Degrees)
Frequency (GHz)
6 IEEE SENSORS JOURNAL, VOL. XX, NO. XX, MONTH X, XXXX
III. SIMULATION, MEASUREMENT, AND DISCUSSION
Regarding the number of cells in the proposed DSMS, there
is a tradeoff between the sensor resolution (bandwidth of the
notch frequencies) and |S21| value (null depth) at two notch
frequencies related to T2-SR and CR2-SR. As a case study,
Fig. 3(b) presents |S21| simulation result for different numbers
of unit cells at . According to this figure, by
increasing the number of cells from 1 to 5, notch bandwidths
and null depth increase. Therefore, considering a 3-cell DSMS
leads to a good balance between notch bandwidth and null
depth.
In order to verify the proposed sensor functionality, the
designed 3-cell DSMS is fabricated on an FR4 substrate with a
thickness of 0.6 mm, relative permittivity 4.6, and loss tangent
0.01 (Fig. 4). Moreover, a foam box was placed around the
sensor to pour soil on the sensor easily and isolate its bottom
layer from the soil (Fig. 4(c)). The foam permittivity is around
1.2 which is close to air permittivity. According to
measurement results, a foam thickness of 5 mm
(0.1) is sufficient to eliminate the effect of soil
mass on the buried sensor bottom. Measurements were
performed using Vector Network Analyzer (VNA-ZVA40).
As mentioned in section II, the concept of permittivity (or
soil VWC) measurement of the proposed DSMS is based on
the resonance frequency variation, relative to the MUT
permittivity. Several relationships between soil moisture
content and soil dielectric constant have been proposed [24],
[25]. Table III presents real parts of the dielectric constant
values as a function of VWC (0-30%) in S-band (2-4 GHz).
The sandy soil is wet above VWC of 30%, and cannot be
considered as moist soil.
Fig. 3. a) |S21| simulation result for different numbers of unit cells at
.
(a)
(b)
(c)
Fig. 4. Prototype of the proposed 3-cell DSMS consisting of a
transmission line loaded with T2-SR and CR2-SR on FR4 substrate
with , thickness 1.6 mm, and loss tangent 0.01 a) top view, b)
bottom view, c) measurement setup.
According to Fig. 1(b), the CR2-SR is unloaded ( )
as a reference resonator in simulations and the T2-SR is
loaded by a 30 mm thick dielectric slab, where the dielectric
slab covers the whole resonator area. Permittivity of the
dielectric slab () is varied in each simulation based on the
values in Table III, and the corresponding transmission
response (|S21|) is monitored (Fig. 5(a)). Figure 5 shows two
transmission zeros for different VWC values, related to T2-SR
and CR2-SR resonators which are presented in (2). These two
frequencies are very close for VWC=0%, and with increasing
VWC to 30%, decreases where the reference transmission
zero () is constant for different values of (or VWC).
Hence, this property can be used in differential sensing.
Moreover, after validating the proposed sensor performance
in unloaded state, the structure has been embedded into the
sandy soil with different VWC. Different soil VWC levels
have been achieved based on [25] that has been released by
the Department of Sustainable Natural Resources NSW
Australia. Firstly, the sand has been put in the oven to dry it.
Then, the water has been added to provide sand with 10%,
20%, 25%, and 30% VWC levels as:
(5)
Where W1 and W2 are the weights of dried soil and added
water, respectively. Furthermore, we measured the
performance of proposed sensor in 5 trials for each VWC
value and then presented average values in Fig. 6(b).
According to Table III, for the soil moisture value range of 0%
to 30%,
varies from 3.7 to 16.7 and the measured
resonance frequency of T2-SR changes from 4 GHz to 2.38
GHz, while the resonance frequency of CR2-SR is almost
constant around 4.39 GHz in measurements (Fig. 5(b)). The
measurement result verifies that the T2-SR and CR2-SR are
uncoupled in the designed sensor.
TABLE III. DIELECTRIC CONSTANT FOR SAND AT S-BAND (2-4 GHZ) [25].
VWC (%)
0
5
10
15
20
25
30
3.7
4.01
5.29
7.22
9.78
13.4
16.7
Top view
50 mm
10 mm
Bottom view
Foam box
Dry soil
Moist soil
Measurement setup
|S21| (dB)
Frequency (GHz)
6 IEEE SENSORS JOURNAL, VOL. XX, NO. XX, MONTH X, XXXX
(a)
(b)
Fig. 5. |S21| results of the proposed DSMS for different VWC, a)
Simulation, b) Measurement.
The measured difference between two zero transmissions
( ) versus VWC (or relative permittivity) of the
loaded sample (MUT) are plotted in Fig. 6(a). According to
this figure, changes from 0.401 to 2.02 GHz for VWC
range of 0% to 30%. By measuring between two resonance
frequencies, the VWC value is calculated. In this regard, the
measured values of are used to develop a mathematical
model for the proposed sensor. To address this, a
mathematical equasion is derived relating the frequency shift
to VWC of the sandy soil moisture. The nonlinear least square
curve fitting in MATLAB is used to derive two equations (5th
and 7th degrees polynomial curve fitting method), describing
the relation between variations as a function of VWC.
Moreover, the error estimation of this mathematical modeling
is approximately less than 18 MHz which is presented in Fig.
6(b).
Figure 7 demonstrates the sensitivity of resonance
frequencies versus VWC for both resonators ().
According to this figure, and
at VWC equal to 30% which verifies the DSMS
performance as a differential sensor. This means, increasing
the soil VWC pulls down frequency, whereas the other
resonance frequency, , is approximately fixed.
Figure 8 shows the effect of MUT thickness on the
simulated resonance frequencies for . As can be
seen, by increasing the MUT thickness to more than 30 mm
(0.6), the resonance frequencies remain nearly
constant. Hence, the sensor operation is independent of MUT
thickness. This test can be easily performed by burying the
sensor under a mass of soil.
Further, recently reported permittivity measurement
sensors, [13]-[15], [26]-[31], are thoroughly compared in
Table IV. These references are frequency domain techniques
that mostly used SRR or CSRR configurations as the
resonators in their structures. In Table IV, to compare given
sensors at different operating frequencies, the fractional
sensitivity is defined as:
Fractional Sensitivity (%) =
(6)
Where is the frequency shift for in the worst-
case scenario (highest permittivity value of MUT), and is
resonance frequency of unloaded sensor.
According to the results and Table IV, the proposed DSMS
exhibits desirable sensitivity in a broad range of permittivity
(1 to 16.5) in comparison with other works. For instance,
although [26] and [27] achieved 130 MHz and 536 MHz
frequency shifts in the permittivity measurement, their
maximum permittivity values are 8 and 5 which are less than
our sensor (16.5). Moreover, there are three differential
sensors in Table IV while their maximum measurable
permittivity is less than our proposed sensor. This comparison
proves the usefulness of our proposed differential sensor
technique for precision farming applications.
(a)
(b)
Fig. 6. a) Measured difference frequency ), b) error estimation of
the mathematical modeling, vs VWC for 5 trails.
Fig. 7. Derivative of vs VWC in the proposed DSMS (sensor
sensitivity).
CT2-SR
Resonances
|S21| (dB)
Frequency (GHz)
|S21| (dB)
Frequency (GHz)
6 IEEE SENSORS JOURNAL, VOL. XX, NO. XX, MONTH X, XXXX
(a)
(b)
Fig. 8. Simulated S21 of the sensor for different thicknesses (T) of the
sample dielectric slab (1 cm<T<5 cm), a) T2-SR, b) CR2-SR.
IV. CONCLUSION
In this paper, a new sensing device using uncoupled
resonators is presented to realize a differential soil moisture
sensor (DSMS). The proposed DSMS consists of a
conventional microstrip line which is loaded with two
resonators: T2-SR and CR2-SR. Simulated and measured
DSMS exhibit sharp resonances which significantly improves
the sensor sensitivity. The length and width of the proposed
structure are approximately 10 mm and 50 mm, respectively.
The low cost and miniaturized size of the proposed DSMS are
the result of utilizing both sides of PCB (top and bottom
layers) to realized resonators. Based on the theoretical
analysis, simulation and achieved measurement results, this
work proves the differential microwave sensing concept for
precision agriculture. Moreover, the proposed technique can
be used in the permittivity measurement of materials for other
applications.
TABLE IV. COMPARISON TABLE
Ref.
(GHz)
Measurement Technique
Frequency Shift (Δf) for
at
(MHz)
Fractional Sensitivity (
)
(%)
Max. Measured
Permittivity
[28]
1.7
SRR (Differential)
33.3
1.9
10.2
[27]
6.1
Stepped Impedance Resonators
(Differential)
536
8.8
5.7
[15]
2.4
Coupled resonators
13.4
0.56
30
[13]
2.1
SRR (Differential)
31
1.5
10.7
[14]
1.91
SIR
40
2.1
80
[29]
2.7
CSRR
---
---
10.2
[30]
4.5
CSRR
60
1.33
NA
[26]
4.5
SRR
130
2.8
8
[31]
5.5
CSRR
3.34
0.1
30
This work
4.5
T2-SR and CR2-SR (Differential)
110.8 MHz @
(VWC: 30%)
2.5
16.7
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Frequency (GHz)
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Rasool Keshavarz was born in Shiraz, Iran in
1986. He received the PhD degree in
telecommunications engineering from the
Amirkabir University of Technology, Tehran, Iran in
2017 and is currently working as Postdoctoral
Research Associate in RFCT Lab at the University
of Technology, Sydney, Australia. His main
research interests are RF and microwave circuit
and system design, sensors, antenna, digital
Metamaterials, wireless power transfer (WPT) and
RF energy harvesting (EH).
Justin Lipman (S’94, M’04, SM’12) received a
PhD in Telecommunications Engineering from
University of Wollongong, Australia in 2004. He
is an Industry Associate Professor at the
University of Technology Sydney (UTS) and a
visiting Associate Professor at Hokkaido
University's Graduate School of Engineering.
Dr. Lipman is the Director of the RF
Communications Technologies (RFCT) Lab, where he leads industry
engagement in RF technologies, Internet of Things, Tactile Internet,
Software Defined Communication and Agriculture 4.0. He serves as
committee member in Standards Australia contributing to International
IoT standards. Prior to joining UTS, Dr. Lipman was based in
Shanghai, China and held a number of senior management and
technical leadership roles at Intel and Alcatel driving research and
innovation, product development, architecture and IP generation. He is
an IEEE Senior Member. His research interests are in all “things”
adaptive, connected, distributed and ubiquitous.
Dominique M. M.-P. Schreurs (Fellow, IEEE)
received the M.Sc. degree in electronic
engineering and the Ph.D. degree from the
University of Leuven (KU Leuven), Leuven,
Belgium, in 1992 and 1997, respectively. She has
been a Visiting Scientist with Agilent
Technologies, Santa Rosa, CA, USA, ETH
Zürich, Zürich, Switzerland, and the National
Institute of Standards and Technology, Boulder,
CO, USA. She is currently a Full Professor with KU Leuven, where she
is also the Chair of the Leuven ICT (the Leuven Centre on Information
and Communication Technology). Her current research interests
include the microwave and millimeter-wave characterization and
modeling of transistors, nonlinear circuits, and bioliquids, and system
design for wireless communications and biomedical applications. Prof.
Schreurs served as the President of the IEEE Microwave Theory and
Techniques Society from 2018 to 2019. She was an IEEE MTT-S
Distinguished Microwave Lecturer. She has also served as the General
Chair for the Spring Automatic RF Techniques Group (ARFTG)
conferences in 2007, 2012, and 2018, and the President of the ARFTG
organization from 2018 to 2019. She currently serves as the TPC Chair
for the European Microwave Conference and also the Conference Co-
Chair for the IEEE International Microwave Biomedical Conference.
She was the Editor-in-Chief of the IEEE Transactions on Microwave
Theory and Techniques.
Negin Shariati is a Senior Lecturer in the
School of Electrical and Data Engineering,
Faculty of Engineering and IT, University of
Technology Sydney (UTS), Australia. She
established the state-of-the-art RF and
Communication Technologies (RFCT)
research laboratory at UTS in 2018, where she
is currently the Co-Director and leads research
and development in RF-Electronics,
Sustainable Sensing, Low-power Internet of
Things, and Energy Harvesting. She leads the Sensing Innovations
Constellation at Food Agility CRC (Corporative Research Centre),
enabling new innovations in agriculture technologies by focusing on
three key interrelated streams; Energy, Sensing and Connectivity.
Since 2018, she has held a joint appointment as a Senior Lecturer at
Hokkaido University, externally engaging with research and teaching
activities in Japan.
She attracted over $650K worth of research funding over the past 3
years and across a number of CRC and industry projects, where she
has taken the lead CI role and also contributed as a member of the CI
team.
Negin Shariati completed her PhD in Electrical-Electronic and
Communication Technologies at Royal Melbourne Institute of
Technology (RMIT), Australia, in 2016. She worked in industry as an
Electrical-Electronic Engineer from 2009-2012. Her research interests
are in Microwave Circuits and Systems, RF Energy Harvesting, low-
power IoT, Simultaneous Wireless Information and Power Transfer,
AgTech, and Renewable Energy Systems.