IoT and Blockchain based Smart Agriculture Monitoring and Intelligence Security System

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IoT and Blockchain based Smart Agriculture
Monitoring and Intelligence Security System
Md. Akkas Ali
School of Computing Science and
Engineering
Galgotias University
Greater Noida, U.P, India
akkas.gu@gmail.com
Dr. B. Balamurugan
Associate Dean-Student Engagement,
Shiv Nadar University
Delhi-National Capital Region (NCR),
India
kadavulai@gmail.com
Rajesh Kumar Dhanaraj
School of Computing Science and
Engineering
Galgotias University
Greater Noida, U.P, India
sangeraje@gmail.com
Dr. Vandana Sharma
Amity Institute of Information
Technology
Amity University
Noida, U.P, India
vandana.juyal@gmail.com
Abstract—Food security seems to be a more prevalent concern
for all countries throughout the world due to global population
growth, dwindling natural resources, agricultural land, and an
increase in unfavorable environmental circumstances. These
problems are the driving force behind agriculture industry's
migration towards modern agriculture through the use of IoT and
Blockchain technology for improving operations, productivity and
maintaining, monitoring agricultural farms and creating fewer
people involvement. We have demonstrated how IoT and
Blockchain systems may be linked with agriculture's intelligent
component to maximize benefits for farmers. Security essential not
only for the resources but also essential for agricultural products
need to be protected and protected in the first instance, as
protection from rodents and pests in the large agricultural field or
grain shops. As a result, these problems need to be addressed. So,
we designed an IoT and Blockchain based Smart Agriculture
monitoring and Blockchain oriented Intelligence Security systems
for Smart Agriculture Infrastructure.
Keywords—IoT, Blockchain, Decentralized Database, Smart
Agriculture, Data Analytics.
I. INTRODUCTION
Every life in the world depends on agriculture because of
coming the major food source from it. Basically, without
agriculture, we cannot think about human life. In case of the
country's economic growth and different public services,
agriculture plays an essential role. A lot of farmers in our
country apply traditional and old farming methods which
prevent them from producing higher yields and fruits. But
whenever automation was made and people were replaced by
automatic machines, the yield increased. So, science and
modern technology are needed in agricultural production in
order to increase yields. The majority of studies demonstrate the
usage of wireless sensor networks, which collect data from
various types of sensors and transmit it to a central server using
wireless protocols. The information gathered about numerous
environmental factors in white aids in the system's monitoring.
Environmental surveilling is not comprehensive, cost-effective,
or adaptable approach. Fertility is influenced by a variety of
other factors. These also including pesticides, which can be
prevented by spraying the crops with pesticides. Attacks on
animals and birds or on mature plants. When the plant is in the
harvesting stage, theft is also a possibility. Farmers frequently
experience difficulties in keeping their crops even after harvest.
As a result, in order to provide a solution to all of these issues,
an integrated system must be developed covering all
components related to production at all stages and; plowing,
harvesting, and post-harvest storage. IoT has become a next-
generation technology megatrend that can impact the entire
enterprise spectrum by increasing profits across devices. Smart
healthcare, transportation congestion control, security, smart
cities, retail, agriculture. And other applications benefit from
IoT technologies. IoT has brought significant changes in the
agricultural sector considering the many challenges and
challenges in agriculture. Nowadays, with the advancement of
technology it is expected that through the use of IoT scientists
and technicians are finding ways to solve problems faced by
farmers such as water scarcity, price regulation and agricultural
issues. All of this has been noticed by new IoT technologies,
which now provide ways to enhance production at a cheaper
cost. We can extract data from wireless network sensors and
deliver it to larger servers thanks to tests with wireless network
sensors. Sensor data gives information on various
environmental variables, allowing the entire system to be
accurately monitored. Environmental control or crop growth is
not only a matter of crop control but also that there are many
other factors that affect crop yields, for example, field
management, soil and crop management, unwanted
infestations, animal attacks of forest, and thief etc. IoT provides
a well-organized set of non-compliant features that make the
overall use of IoT more productive. The IoT agricultural
network uses wireless which allows real-time monitoring of
crops and animals. Two sensor devices, including Liberium
Smart Agriculture Xtreme IoT Vertical Kit as well as the Crop
/ Plant Monitoring Sensor Kit, measure soil moisture levels,
plant moisture, temperatures, humidity, fertilization, as well as
978-1-6654-5319-6/22/$31.00 ©2022
IEEE
3rd International Conf. on Computation, Automation and Knowledge Management (ICCAKM 2022)
2022 3rd International Conference on Computation, Automation and Knowledge Management (ICCAKM) | 978-1-6654-5319-6/22/$31.00 ©2022 IEEE | DOI: 10.1109/ICCAKM54721.2022.9990243
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airflow. The MooMonitor sensor, on the other hand, keeps track
of animal health, reproduction, feeding, crying, and rest. Farm
servers, gateways, and agricultural databases are essential for
keeping agricultural commentaries as well as supplying
authorized clients with on-demand agriculture products.
The summarization of our works as we have developed an
IoT and Blockchain based Smart Agriculture Monitoring and
Intelligence Security System, because we have adopted a
maximum-security policy, for the farmers to receive the best
irrigation and culture in order to produce the most harvests. We
have explained a novel architecture of smart agriculture system
including physical structure of database, farmer’s devices,
control units and also gateways, IoT data capture systems, Data
processing, data analytics systems and communication protocols
and its topology and sensors those are needed to implement our
smart agriculture system are mentioned. We have defined the
security threats that frequently faced by agriculture system and
mitigated these security threats by using the Blockchain based
different approaches. We have enhanced the security system
here properly. We have taken into account general security
factors, such as those that arise during data collecting,
processing, monitoring, and preservation for decentralized
Blockchain-based systems. We are unique in these cases.
II. B
ACKGROUND
New low water conditions, drying up of rivers and
reservoirs, unstable terrain give rise to urgent need for efficient
water use. Monitoring the use of this temperature and humidity
sensor in the required areas of crop monitoring is done
internally [1]. The algorithm adapted to the threshold value of
temperature and humidity can be programmed to operate a
microcontroller-based gate to regulate the flow of water [2].
Technologically advances in Wireless Sensor Networks have
enabled applications in greenhouse parameter monitoring and
control in real fields [3]. Researchers discovered that crop
yields were decreasing with each day after doing agricultural
study. As a result, agricultural technology plays an essential
role in both improving production and lowering human
resource resources [4]. Further research is aimed at empowering
farmers that provide systems that use technologies that help
increase agricultural productivity. A distributed wireless sensor
network is used in the irrigation system remote sensing and
control system that aims to vary the irrigation rate, in real time
in the sensor field, real-time site-time line system control to
increase productivity and reduce consumption of water [5]. The
system explained in detail about the production and irrigation
rate, wireless and real-time sensor network in the listening and
control domain with the application of suitable software. Five
fields were used to create the full system data acquisition and
transmission systems using global positioning system (GPS)
while taking steps to control irrigation according to the existing
database and system [6]. The technology provides guaranteed
low-cost wireless solutions as well as irrigation control from a
distance. Researchers used a network of wireless sensors to
assess soil-related characteristics like temperature and humidity
in a study [7]. Underground sensors communicate with the relay
node using an efficient communication protocol that has a low
duty cycle and hence improves the ground monitoring system's
lifespan. While transmission was one hour sampling and
buffered data, transmission and monitoring of text messages,
the system was configured using a microcontroller, universal
asynchronous transceiver interface (UART), and sensors[8].
The system's low cost and subsurface motion sensor, which
resulted in lower radio frequency (RF) transmissions, were
disadvantages.
III. O
BJECTIVES
A
ND
S
PECIFIC
A
IMS
Our main objectives and specific aims as following:
• To design IoT and Blockchain based Smart Agriculture
Monitoring System.
• To implement an Intelligence Security System for a
Smart Agriculture Monitoring System.
• To encrypt the agriculture data using SHA and stored
decentralized Blockchain database for ensuring
security, availability, Integrity etc.
• To help the farmer for their cultivation.
• To contribute the highest production of crops.
IV. A
RCHITECTURE
O
F
S
MART
A
GRICULTURE
S
YSTEM
IoT and Blockchain based on Smart Agriculture Monitoring
and Intelligence Security System has five main features as
shown in “Fig. 1” [9] and “Fig. 2” which is physical structure,
data capture, processing, analytics and Communication
Technology. We have encrypted agriculture data by using
Secure Hash Algorithm and stored into decentralized
Blockchain database as byte stream for ensuring security,
availability, and integrity.
Figure 1. Environment of IoT and Blockchain based Smart Agriculture
Monitoring System
A. Physical Structure
Growing large enough to prevent anything from happening
is dependent on physical structure. Every system is built to
control sensors, actuators, database, gateway, computer, labtop,
smart phone, controller and many other devices in some way as
shown in “fig. 1”[9] and “fig. 2”. The sensor can detect soil
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sensitivity, temperature, weather, light, and humidity, among
other things. Similarly, machines perform many administrative
functions such as, availability of nodes, device recognition and
service names. Any microcontroller-controlled device or sensor
can perform all of these duties. This control can be done on any
computer or remote-controlled device that is linked to the
internet.
Figure 2. IoT and Blockchain based Smart Agriculture Monitoring System.
B. IoT Data Capture
Advanced Message Queue Protocol (AMQP), Web Socket,
Constrained Application Protocol (CoAP), Message Queue
Telemetry Transport (MQTT), HTTP, Data Distribution Service
(DDS), and Node are seven protocols that make up the data
capturing component of IoT. Many protocols can be utilized for
smart agriculture applications depending on the requirements
and characteristics.
C. Data Processing
As depicted in “Fig. 2”, data processing entails various
images with audio, video or image, recording of the data, choices
the support of system, and extraction of the data. Any feasible
addition can do the same to give various services, depending on
the system parameters.
D. Data Analytics
Monitoring and controlling are the two main monitors in
data analytics. Livestock monitoring, field monitoring, and
greenhouse monitoring are the three main agricultural processes
that are monitored. Farmers can use the IoT to keep track on their
crops, livestock through a number of sensors used to detect
various animal diseases such as temperature, heart rate, and
digestion. But field research centers aim to predict different field
conditions such as soil fertility, temperature, humidity, gas,
compression (wind and water pressure), and to diagnose crop
disease. The smart greenhouse design eliminates manual
interference and measures different weather and intelligent IoT
tools and sensors based on crop requirements.
E. Communication Technology
Communication technologies should gradually improve the
evolution of IoT devices in order to integrate IoT into the smart
agriculture industry. They have a significant impact on the
development of IoT systems. Protocol, spectrum, and topology
are the three types of existing communication systems.
1) Protocols: For the smart agriculture sector, numerous
wireless communication protocols have been developed.
Devices in an intelligent agricultural system can communicate,
exchange information, and make choices based on these
protocols to boost yields and production efficiency by
monitoring and controlling site conditions.
2) Spectrum: Every communications equipment
communicates using specific frequency ranges. Unlicensed
spectrum bands have been specified by the Federal
Communications Commission (FCC) for unlicensed purposes
in science, business, and medicine. As just a result, any number
of fundamental smart agriculture technologies, such as wireless
machine control in UAVs and communications technology
including Wi-Fi as well as Bluetooth, are now freely available.
The spectrum's bands using unlicensed spectrums has a number
of drawbacks, including quality of service guarantees,
foundation at the start expense, conflict produced with
increasing a high proportion of embedded applications. Mobile
networks are frequently given licensed spectrum.
3) Topology: A development of the IoT communication
subcarriers and protocol tools are in line with the nature of
sending IoT tools for smart farming. The most prevalent types
of nodes in network intelligent agricultural systems are sensing
and transport node. Short communication distances, low data
rates, and extremely powerful functioning are the most typical
characteristics of IoT sensor nodes. IoT backhaul nodes, on the
other hand, usually demand longer transmission distances,
higher output, and a data center. In order to save energy and
money, these nodes are unable to communicate with other
RFDs. In addition to serving as IoT sensor nodes, IoT backhaul
nodes also serve as intermediate nodes, receiving data
originating from different IoT connection, then transmitting
toward the management. Internet of Things broadband node
is frequently constructed as FFD nodes attached with FDD as
well as RFD equipment.
F. Sensors use in Smart Agriculture
1) Optical sensors: Optical sensor measures soil elements
with light from various sources. These sensors, which are
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installed on vehicles or drones, collect and adjust data on soil
visibility and planting color. Soil, organic matter, and soil
moisture can all be detected using optical sensors.
2) Electrochemical sensors: Electrochemical sensors aid
in the collection of chemical data from the soil. Electrochemical
sensors detect soil nutrients and offer information. Soil samples
are sent to a lab for analysis. An ion-selective electrode is used
for precise measurements, especially pH determination.
Specific ions, such as nitrates, potassium, or hydrogen, are
detected using these electrodes. Electrochemical gas sensors,
also known as electrochemical analyzers or electrochemical
dangerous gas detectors, are used to monitor the reaction of a
genuine gas (such as oxygen or carbon monoxide) in the
presence of other gases.
3) Mechanical soil sensors: Mechanical soil sensors use
a cutting method that records the energy sensed by pressure
gauges or load cells as it passes through the ground. The
gripping force caused by cutting, breaking, and removing soil
is recorded when the sensor cuts through the ground. In the
force field, soil mechanical resistance is defined as the ratio of
the force necessary to penetrate deep into the ground to the front
of the ground-held vessel.
4) Dielectric soil moisture sensors: The moisture content
of the land is measured using dielectric soil moisture sensors.
Water monitoring sensors and moisture sensors are employed
around the farm. If the vegetation level is low, this enables for
the observation of soil moisture.
5) Location sensors: The size, distance, and length of
any position within the required area are determined by location
sensors. They do this with the support of a GPS satellite.
6) Electronic sensors: Electronic sensors are used to
monitor the operation of tractors and other agricultural
equipment. The message is then promptly relayed to computers
or e-mailed to the general public via telephone and satellite
technologies. The field service supervisor can look at the data
on the device.
7) Airflow sensors: Airflow Sensors measurements can
be made elsewhere while on the go. The needed output is the
amount of compression needed to shove the desired at a certain
depth, the quantity of air that enters the soils. Distinct soils
types create different signatures, which include fat, form, soil
type, and quantity.
8) Agriculture sensors IoT: Agriculture Sensors IoT
predetermined intervals are used to monitor and record soil
temperature , air temperature at various, rainfall, depths, leaf
moisture, air flow, chlorophyll, dew temperature, humidity,
wind direction, air pressure, and solar temperature.
9) Other sensors: Monitor Climate Conditions,
Greenhouse Automation (humidity sensors, soil moisture
sensors, temperature sensors, Light sensors, Air quality sensors,
Soil PH sensor, Carbon dioxide sensor), Sound detection
sensor, ultrasonic sensors, transceivers, or transducers, Crop
Management, Cattle Management and Monitoring, Smart
Precision Based Agriculture using Sensors, Agricultural
Drones.
V. SECURITY THREATS FOR IOT BASED SMART
AGRICULTURE
An IoT-enabled smart agriculture can be vulnerable to
many possible attacks.
A. Privacy Breach attacks
Such sort of attack uses agricultural sensing layers to
analyze the actual location and privacy for the IoT device in
attempt to acquire personal data and breach privacy over time.
Intelligent IoT tools meters and multimedia agricultural sensors
collect large amounts of data in environmentally friendly Smart
farming several times per hour for information-capturing
information on crop conditions and improving food performance
response. Carefully analyzing this IoT data can easily reveal the
experiences of farmers as well as the food available to them. For
example, in the case of pH, high pH indicates that the farmer will
increase ammonium, while lower pH means that the farmer will
decrease ammonium. Such data can be used by an offender to
execute the body assault for altering the pH level. Illegal access
to the confidential information should be avoided.
B. Authentication – related attacks
To get access to IoT fields, such form of assault
impersonates sanctioned endpoints.
1) Man in the middle attack: A man in the middle attack
is used to perform a replay attack these objectives for IoT-based
agricultural seem to be to intercept data packets to an IoT device
with or without an entry point towards the agricultural sensors
surface, thereafter transmit these intact to respective locations.
To protect IoT networks from replay attacks, authentication
protocols use three techniques: coupling-based encryption,
hashing, and timestamps in cypher text.
2) Masquerade attack: The masquerade attack attempts
to enter the server at the agricultural fields by impersonating a
valid node (i.e., entering the fog node).
C. Confidentiality – related attacks
Such sort of attack tries to monitor internet traffic an IoT
device with or without an entry point towards the agricultural
sensors surface in order to fool the IoT planting into interfering
with privacy and making error decisions. For example, an
adversary may use listening-based attacks such as exploration,
brutal violence, and known-key attacks to infringe on
confidential information.
1) Violent attack: A violent attack is aimed at creating
multiple Internet passwords for items on the agricultural
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sensors layer, and then removing this for a while until the
appropriate password is found.
2) Known-key attacks: Known-key attacks aim to make
the selected part of the certificates from the previous damaged
certificates.
D. Availability – related attacks
Denial of Service (DoS) attacks fall into this category. Its
goals are just beginning to make activities in IoT-related fields
that are not socially connected (e.g., authorizations for IoT
devices) impossible by (1) overwhelming servers with a large
volume of information to start making them more concerned
with not being able to provide customer support to the IoT
devices they use; (2) upgrade to misleading information.
E. Integrity – related attacks
Such type of assault necessitates an unauthorized actor
gaining access to or altering confidential data. This category
includes fake attacks, biological pattern attacks, and Adware
attacks. To counter this issue, data collecting solutions according
to asymmetric cryptography and hashing algorithms should be
developed.
VI. MITIGATION OF SECURITY THREATS USING BLOCKCHAIN
Almost all IoT sectors, especially IoT-based agriculture,
can benefit from blockchain technology. The use of blockchain
technology in IoT is used to ensure anonymity. Blockchain, in
particular, can be used to distribute cipher texts. The Blockchain
technology makes duplicated as well as preserved in many
places. We categorize blockchain-based approaches for the IoT-
based agricultural across five types based on the quality of each
blockchain-based privacy method.
A. Blockchain-based machine learning approach
The Secure SVM method captures the confidentiality of
data in an account teaching vector support (SVM) with
blockchain-based encrypted IoT data[10]. The secure SVM
method uses a public-key cryptosystem, which is an extension
of the homomorphic cryptosystem, to ensure the confidentiality
of IoT data. The secure SVM method relies on two different
threat modes: known cipher text and known background. Green
IoT-based farming can benefit from a secure SVM system. The
following steps illustrate the adjustment:
• Agriculture sensor nodes employ Wi-Fi to collect and
transmit crucial data.
• The data from the farm sensor nodes is collected by
each entry point.
• Data is encrypted using partly encryption algorithms
at each entry point.
• The cipher text is recorded on the blockchain by each
entry point.
• The data is validated by each entry point's built-in
consensus mechanism.
B. Blockchain oriented decentralized key management
approach
The BDKMA paradigm uses secure access managers for
creating a multilayer access control mechanism when operating
with Blockchain [11].
• Each farm sensor node generates a secret access key,
an encryption key, a public key after selecting its own
key.
• Each agricultural sensor node locks a secret entry key,
signs a transaction, and distributes it to the access
point.
• Agricultural node systems are monitored by each entry
point in the existing sensors layer.
• The data is verified by each access point built-in agree
process.
• An access query transaction used by the agrim sensor
node to obtain authorization from another location.
• The field sensor node sends the key to improve the
transaction to the acquisition period from time to time
to update the acquisition keys.
C. Blockchain-based access control approach
The blockchain platform is in charge of enforcing access
control. The six benefits of access control are as follows that can
be achieved by applying the proposed design to IoT-based
agriculture: Visibility, adaptability, simplicity, parallelism,
availability, and portability are all desirable characteristics.
• In the fog computing layer, the fog link is activated a
contract that is clever on the blockchain system.
• Each access point in the farm sensors layer requires a
smart contract address to have a manager's credential.
• The policy is implemented at the access point in the
agricultural sensors layer, which processes
transactions towards the smart contract.
• An existing policy is added to the access point in the
agricultural sensors layer.
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D. Blockchain-based trust and reputation approach
For blockchain according to IoT systems, has demonstrated
a reputation and trust system that can be applied to greenhouses.
The recommended method relies on three key steps to
strengthen transactions: the data, the blockchain, application
layer. Following steps illustrate the development of blockchain
oriented greenhouse for building confidence:
• Inside the greenhouse, the IoT gadget repairs blocks
periodically. The public key and signature data sauce
is used to create that code.
• On farm sensors layer, the IoT device moves the
blocks to the greenhouse shaft.
• Number of cores and two block generating nodes used
by Greenhouse miner to strengthen blocks.
E. Blockchain-based authorization and identification
approach
Agricultural-based IoT, a well-selected system called trust
bubbles can be used to enable the ability and reliability of the
visibility of IoT tools in IoT applications. The bubbles of the
trust system, which is based on blockchain technology, create a
secure real space (tubes) that can ensure data availability and
reliability. The Sybil attacks, spoofing attacks, DoS / DDoS
attacks, and replay attacks all conflict with the trust system. As
a result, redesigning the trust bubbles system of green IoT-based
farming involves building a real safe space within the farm
nodes. Every node on the farm sensors layer should only
communicate with the equipment in its place. The transaction is
considered to be a communication between the assets.
F. Blockchain-based secure-SDN approach
Software defined networking (SDN) is used to streamline
hardware and software solutions for IoT farming, allowing
management and management from a central location[12]. The
blockchain-based security SDN architecture is used to detect any
fraudulent data injection. BICS (blockchain-based integrity
checking system) and IDS (intrusion detection system) are two
types of blockchain-based integrity checking systems.
VII. RESULT ANALYSIS
We have developed an IoT and Blockchain based Smart
Agriculture Monitoring and Intelligence Security System for
best irrigation and cultivation for the farmers in order to gain
maximum crops because we have taken maximum security
policy. We can compare our works with [13-17] where they did
only the agriculture system without any security issues. We have
considered overall security such as during data collection, data
processing, data monitoring, data preservation according to
decentralized Blockchain based systems. These are our novelty.
VIII. FUTURE RECOMMENDATION
We will be extended this research works with detection and
prevention of pests in large agricultural field by using sound
analytics.
IX. CONCLUSION
In terms of introducing new services and integrating with
other IoT platforms, we created a system that is versatile and
extendable. It's also horizontally scalable, which means we can
boost performance simply by generating more server instances.
All of the observations and tests suggest that our work, which
includes a remote-controlled automaton, an intelligent drip
irrigation, as well as a smart warehouse system, is a complete
answer to field activities, irrigation issues, and storage issues.
Incorporating an IoT and Blockchain-based smart agriculture
system in agriculture can significantly improve crop yields
while also reducing human labor and increasing production
efficiency.
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