Analysis of Wireless Sensor Networks in Agriculture

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MITS5003
Wireless Networks and
Communication
Case study 1
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Contents
A).....................................................................................................................................................2
B).....................................................................................................................................................2
C).....................................................................................................................................................3
D).....................................................................................................................................................4
E)......................................................................................................................................................5
F)......................................................................................................................................................5
G).....................................................................................................................................................6
H).....................................................................................................................................................7
References........................................................................................................................................9
List of Figures
Figure 1: Cloud application.............................................................................................................6
1

A)
In current times, there are many different organizations that are practising the usage of wireless
networks. Most of the organization currently use either Internet of Things (IoT) or wireless
networks. This technology is being worked on various platforms while performing over a
machine to any other machine, for example, ZigBee, IEEE 802.15.4. Whenever a radio signal
transmits the signals will gradually be lost depending upon the time period and the distance
covered. If there is a considerable distance between the transmitter and the receiver, in that case,
these signals would not be able to communicate. In a case when the higher frequency of a lower
signal would be 2.4 GigaHertz or less, then only the transmitter and receiver would have the
ability to communicate with each other. Also, the propagation of the radio signals will be very
poor along with tree walls or another obstacle, in case of the frequency over 2.4 GHz (Lin,
2016).
B)
Given: Rate of production of data: 5 Kilobytes/ Minutes
Converting the unit of the rate=
For unit of time= 5kb/minute = 5/60 kb/ second
For unit of bytes= 5*103/60 bytes/second
5000/60 = 250/3
= 83.33 Bytes/ Second
We know that, 1 byte = 8 bits
Hence
83.33 Bytes/Second = 83.33*8 Bits/ Second
Hence, the channel capacity of the device = 666.6 Bits/ Second
According to the question, Total no. of obstacles of the sensor: 2500
Traffic over the control unit =
2

667*2500 =
167500 Bits per Second =>
= 1.66 Mega Bits per second
C)
Thermal Noise=
No= k*T*B
Given: Farm temperature (T) = 200 C
= 293.15K
Here, k is Boltzmann’s Constant= 1.3803 * 10-23Joul/ Kelvin
B/W = 20 MHz
No= 293.15*20*10*1.3803*10-23
= 8092.698 * 10-17 Watt/Hz
Converting the unit to dbW
10log10(8092.698 * 10-17)
=-130.9
Converting in db
= -130.9 + 30
= - 130.9 +30
100.92 dB
The total amount of noise=
According to question, the thermal noise in 5% of the total, therefore
No/.005
= 100.92/.005
3

= 2018.4db
D)
On the basis of the formulae,
The S*N*Rdb will be= 10log10= (Psignal/Pnoise)
= S*N*R = Psignal -Pnoise
We know that,
Noise = 100.92
S/N in db = 10log10(S/N)
We know that
S/N = 63
Hence,
10log10(63) = 18
Putting the value of S/Ndb
Psignal-Pnoise = 18
Psignal = -100.92+ 18
Signal Power = 82.92db
We know that
Channel capacity (C) = B log2(1+S/N)
667 = B log2(63+1)
667 = B log2(2)6
667 = B(6)
Obstacle’s Bandwidth (B) = 111.54Hz
For multiplex B/W
4

B/W= 111.54*2500
B/W= 112*2500 Hz
B/W= 280 * 103 Hz
B/W = 280 KHz
E)
For the loss of free space, (Chaudhary, et. al., 2016)
20*log10(d) + 20*log10(f) - 147.56db
Where d = distance between 2 antennas
F= frequency
d= 0.5 * Diagonal Distance
d= .5 * √9+9
= .5 * √18
=.5 * 4.243
= 2.12 Kilo Meters
Required bandwidth for the sensing obstacle= 112Hz
Hence, frequency = 886000056Hz
Space Loss= 20*(log10(886000056)) + 20(log10(2.12))- 147.56
= 20(2.94743) + 20(0.32634) + 147.56
= 58.95 + 6.5627- 147.56
= Loss of free space = 82.083db
F)
For Tramission Power Tstrength
We know that,
5

Signal Power = Tstrength - (Attenuationloss) – Free Space Loss
82.92 = Tstrength – 30%* Tstrength – 82.083
Tstrength = .837/.7
= 1.2 dB
Transmission Power =1.3mWatt
G)
Following can be the basic functionalities of cloud computing application for the effective use of
the sensor data in agriculture (Khalil, et. al., 2016).
1. Storage of all the information that is related to the agriculture on the cloud which can be
made available every user at a single point of time.
2. Managing all the land-related data, location related data, area related data and soil related
data via the central support system for making decisions.
3. High information for agricultural sharing and integration
4. Elimination of technical knowledge of the farmer (Chen, 2015)
Figure 1: Cloud application
6

One of the approaches to this concept is that the animal would be collecting and categorizing the
goods based upon the age and type, which will lead to having control and monitoring over every
animal based on their particular characteristics.
This method also has the ability to deliver knowledge based on agriculture and also managing of
resource and knowledgeable features for customers in rural areas like in continuous markets even
as well as in an urban sector. It can change the complete consuming chain, which is generally in
the hand of reputed and well-known organization, but soon may become even more in terms of
direction, development of shorter end. Cloud tech, also have an application on the enhancement
of the growth of agriculture sector.
H)
The Internet is gradually travelling from an Internet of fellows to an Internet of Things. As per
the Cisco, 40 billion objects have a high probability of being to the Internet by the year 2020,
hence predicting the data developed by people. This process has been restricted due to the birth
rate: In 2020, the expected global population is more than 7.9 Billion. The things that are to be
cabled to the Internet are very much different in terms of their features. These devices can be
small and static but also can be large and mobile such as a car. The Wireless Sensor Networks
(WSNs) are cabling the objects to the Internet via a gateway that connects the WSN to Internet.
Not similar to other networks, WSNs have a specific feature of cumulating sensed data such as
fire detection, motion, temperature etc. and moving it forward to the gateway via a single way
communication protocol. Although generally WSN protocols are not created for two-way
communications, they should also be having the ability of reception of information and transfer it
to the sensors, and respond on behalf of the client (Khalil, et al., 2016). A Wireless Sensor
Network contains various nodes of sensors that have their usage in various situations with
respect to applications like agricultural, energy etc. A Wireless Sensor Network might contain
various nodes of the sensors that are responsible for performing their respective tasks sent to the
focused region. Although nowadays, the culture of usage of Internet Protocol-based networking
solution for the networks of sensors allows the Wireless Sensor Network to be cabled to the
World Wide Web. Hence, it has the ability to control various tasks from the Internet connection
that eventually is the idea of IoT. It allows the physically working items that can be assembled
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with sensor and connection of networks, in order to perform operations on data (Bera, et al.,
2016).
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References
Bera, S., Mishra, S., Roy, S., and Obiat, M., S., 2016, Soft-WSN: Software-Defined WSN
Management System for IoT Applications. Institute of Electrical and Electronics Engineers. 1(1).
Pp. 1-8
Chaudhary, S., K., Jadoun, R., S. and Mandoria, H., L., 2016, Role of Cloud Computing
Technology in Agriculture Fields. Computer Engineering and Intelligent Systems. Volume 7(3).
Pp. 1-7.
Chen, M., Zhang, Y., Li, Y., Mao, S. and Leung, V.C., 2015. EMC: Emotion-aware mobile
cloud computing in 5G. IEEE Network, 29(2), pp.32-38.
Khalil, L., Abid, M., R., Benhaddou, D. and Grendt, M., 2016, Wireless Sensor Network for
Internet of Things. Technical University of Munich. 7(1). Pp. 1-7
Lin, S., Miao, F., Zhang, J., Zhou, G., Gu, L., He, T., Stankovic, J.A., Son, S. and Pappas, G.J.,
2016. ATPC: adaptive transmission power control for wireless sensor networks. ACM
Transactions on Sensor Networks (TOSN), 12(1), p.6.
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