Wireless Communication: WSN, IoT Platforms in Agriculture Sector

This report explores the application of wireless sensor networks (WSNs) in agriculture, focusing on improving production and quality through precision agriculture management. It discusses the selection of the radio frequency band, particularly Long Range radio (LoRa) technology, for its low power consumption and long-distance transmission capabilities. The report calculates channel capacity for sensing devices and control centers, analyzes noise levels (thermal noise), and determines the required signal power to maintain a signal-to-noise ratio (SNR) of 63. It also evaluates the bandwidth requirements, impact of free space loss, and suggests cloud application functionalities for the agriculture sector. Furthermore, it explains how IoT platforms can aid in the implementation of WSNs by leveraging IP-based connectivity and managing sensor networks through the public internet. The report concludes by highlighting the innovative developments in WSN-related areas, including applications, energy management, maintenance, self-learning, and adaptability.

WIRELESS NETWORKS AND COMMUNICATION

Table of Contents
1. Frequency band for WSN.........................................................................................................2
2. Calculate the channel capacity.................................................................................................3
3. Calculate the noise levels.........................................................................................................3
4. Maintain SNR of 63 at the control centre for sensor signals....................................................4
5. Calculate the maximum free space loss...................................................................................5
6. Determine the required transmission signal strength...............................................................5
7. Agriculture sector and business suggest functionalities for the cloud application...................5
8. Suggest how IoT platforms can help the implementation of WSN..........................................6
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1. Frequency band for WSN
The wireless sensor networks can be used in agriculture and it used to provide farmers
with a large amount of information. Basically, the agriculture uses the precision agriculture
management strategy and it used to employs the information technology to improve the
production and quality. It utilizing the wireless sensor technologies and management tools and it
is leads to a highly effective and green agriculture. The wireless sensor network is comprised the
several sensors, radio frequency and processors module. Here, we will select the best frequency
band for wireless sensor network is radio frequency band. The radio frequency band is used to
monitoring the wide range of surroundings to obtain the precise information from the network. It
accordingly monitors the sensing, processing, storage and communication capability and these
are needs to increase. The radio frequency uses the various technologies but here we will use
Long Range radio (LoRa) because the LoRa technologies will take the place in agricultural
applications due to the low power consumption and preferably used when the agricultural
information are to be transmitted over the long distances. The LoRa is used to improving the
kiwi production based on a smart irrigation system and it monitoring of green areas by using the
smart garden system [1].
2. Calculate the channel capacity
The wireless sensor network uses the most promising techniques that can enhance the
channel capacity and reduce the transmission energy in wireless sensor networks. The most
adaptive method is MIMO singular value decomposition in order to enhance the channel
capacity of wireless sensor network. It is used to provide the efficient space time for network.
I. One sensing device to control centre channel
The channel capacity for one sensing device to control the centre channel is 100
bits/s.
II. Control centre to ISP channel
The channel capacity for control centre to ISP control is 90 bits/s [2].
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3. Calculate the noise levels
I. Thermal noise
The thermal noise is effectively white noise and it used to extend over a very wide
spectrum. It generally has the noise power and it proportional to the bandwidth.
II. Total noise experienced
The noise experienced is based on thermal noise. However, it is found that
thermal noise is only 5% of the total noise experienced by the wireless sensor
network channels [3].
4. Maintain SNR of 63 at the control centre for sensor signals.
I. Calculate the signal power received at control centre from one sensing device
The wireless sensor network uses the radio frequency bands for signal
transmission. The below equation is useful to calculating the signal power arriving at the
receiver and it provides the good approximation of the received signal power if the center
frequency is high enough.
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Here, we will use the LoRa receiver modules that are after used for wireless
sensor sensors. It has higher values mean higher received signal strength and it makes the
sense. It has maximum signal power is -40 to -50dBm [4].
II. Calculate the bandwidth of the sensing device to control centre channel.
Basically, the low power WSN are has the bandwidth of the radio frequency is
usually in the range of 100 kbit/s up to 1 Mbit/s and the sensors are requiring the
sampling rate higher than 10 Hertz and it can be considered as high bandwidth
sensing devices. The bandwidth is based on the amount of the data user take from
sensors. Basically, the wireless sensor would needs at least 250KBps [5].
III. What will be the bandwidth of the multiplexed channel if FDM scheme is
Used?
The bandwidth of the multiplexed channel use the FDM scheme because the
operations of frequency division multiplexing is based on sharing the available
bandwidth of a communication channel and its signals to be transmitted and
multiplexed will each modulated a separate carrier. It is used to allow a single
transmission medium like optical fiber or cable to be shared by multiple independent
signals.
5. Calculate the maximum free space loss
The free space path loss is calculated by requires the distance, frequency, transmitter gain
and receiver gain based on the sensors. It is used to help predict radio frequency strength in a
wireless sensor network.
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The free space loss for is 199 dBm and it is experienced by the signals sent from sensors.
6. Determine the required transmission signal strength
The required transmission signal strength for wireless sensor network is −10 dBm because
the signal impairments as attenuation and fading causes loss of 30% in signal power during the
propagation from sensors to the control centre.
7. Agriculture sector and business suggest functionalities for the cloud
application
The cloud application is needs to provide the effective data for agriculture sector. It provides
the various functionalities for agriculture. They are,
 Reduce the initial costs
 Resource allocation on demand without limit
 Upgrades and maintenance performed in the back end.
 Easy rapid development including the collaboration with other systems [6].
8. Suggest how IoT platforms can help the implementation of WSN
The wireless sensor network is merely a subset of the IoT platforms. The wireless sensor
network is only address the use of sensors and even more specifically and wirelessly connected
the sensor by using the IoT because the IoT is using the IP instead of proprietary protocols and
perhaps the connected to the public internet. The IoT effectively controlled and manage the
wireless sensor network by using the public internet. The IoT helps the implementation of WSN
based on innovative developments in areas related to WSNs including,
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 Applications (both new and enjoying new life)
 Energy (reliability, management)
 Maintenance (troubleshooting, recurrent costs)
 Self-learning (pattern discovery, prediction, auto-configuration)
 High-level methods and tools for node and application design
 Deployment (cost, error prevention, localization)
 Cost (of node, energy, development, deployment, maintenance)
 Communication (security, resilience, low energy)
 Adaptability (to environment, energy, faults)
 Data processing (on nodes, distributed, aggregation, discovery, big data)
References
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2018. [Online]. Available:
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http://www.radio-electronics.com/info/rf-technology-design/noise/thermal-calculations.php.
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[4]"Free Space Path Loss Calculator", Pasternack.com, 2018. [Online]. Available:
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[5]"Free Space Path Loss FSPL | Formula Calculator | Radio-Electronics.com", Radio-
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equation.php. [Accessed: 09- Jun- 2018].
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